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If I The Sunday Paper i is, as the authors write, "an argument for shifting the topography of journalism and newspaper history and placing it more squarely within media history" (p. 4), then we need to know that "topography." Paul Moore and Sandra Gabriele explain how this happened in I The Sunday Paper: A Media History i by charting the ways in which the Sunday newspaper continually reinvented itself with new inserts and sections and the adoption of technologies that attracted and engaged readers. For most of the twentieth century, the distinctive "thud" of the Sunday newspaper hitting the doorstep (if the paperboy had accurate aim) was the sound of journalism. [Extracted from the article]

Copyright of Rundbrief Fotografie is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Tsavorite's color is not only affected by its internal components, but also by external factors. This paper studies the neutral grey background and cutting on the impact on color. Under a 6504K fluorescent lamp, by changing the Munsell neutral gray backgrounds from N9.5 to N3, we discovered that N9.5 was the best background for tsavorite color grading. In this paper, the feasibility of taking color by photography is studied. The regression models R2 between the photogrammetry (PM) and the colorimeter (CM) were above 86.99% for all of the color parameters (L*, a*, b, C, and h*), allowing the PM data to be used to predict the CM color values. Photographs were taken before and after the cutting to document the color shift. Comparing the L* and C* before and after cutting, the color concentration score was 100–90 if both L* and C* were optimized, 80–70 if only one parameter was optimized, and 70–60 if neither was. The value of ΔL* in the color histogram serves as a measure of the gemstone's color scintillation; the greater the value of ΔL*, the stronger the scintillation. [ABSTRACT FROM AUTHOR]

In this paper, a low-complexity color interpolation algorithm is proposed for the very-large-scale integration (VLSI) implementation in real-time applications. The proposed novel algorithm consists of an edge detector, an anisotropic weighting model, and a filter-based compensator. The anisotropic weighting model is designed to catch more information in horizontal than vertical directions. The filter-based compensation methodology includes a Laplacian and spatial sharpening filters, which are developed to improve the edge information and reduce the blurring effect. In addition, the hardware cost was successfully reduced by hardware sharing and reconfigurable design techniques. The VLSI architecture of the proposed design achieves 200 MHz with 5.2-K gate counts, and its core area is 64~236~\mu m ^{\mathrm {\mathbf {2}}} synthesized by a 0.18- \mu $ m CMOS process. Compared with the previous low-complexity techniques, this paper not only reduces gate counts or power consumption by more than 8% or 91.7%, respectively, but also improves the average color peak signal-to-noise ratio quality by more than 1.6 dB. [ABSTRACT FROM PUBLISHER]

Pathological myopia (PM) is a severe ocular disease leading to blindness. As a traditional noninvasive diagnostic method, fundus color photography (FCP) is widely used in detecting PM due to its high fidelity and precision. However, manual examination of fundus photographs for PM is time-consuming and prone to high error rates. Existing automated detection technologies have yet to study the detailed classification in diagnosing different stages of PM lesions. In this paper, we proposed an intelligent system which utilized Resnet101 technology to multi-categorically diagnose PM by classifying FCPs with different stages of lesions. The system subdivided different stages of PM into eight subcategories, aiming to enhance the precision and efficiency of the diagnostic process. It achieved an average accuracy rate of 98.86% in detection of PM, with an area under the curve (AUC) of 98.96%. For the eight subcategories of PM, the detection accuracy reached 99.63%, with an AUC of 99.98%. Compared with other widely used multi-class models such as VGG16, Vision Transformer (VIT), EfficientNet, this system demonstrates higher accuracy and AUC. This artificial intelligence system is designed to be easily integrated into existing clinical diagnostic tools, providing an efficient solution for large-scale PM screening. [ABSTRACT FROM AUTHOR]

Historical photographs, whether taken from the air or from the ground, are usually synonyms of grayscale or sepia prints. From the very beginning of photography, during the first half of 19th century, people were amazed by this new media that could record all aspects of a scene with great detail. Soon though, everybody started wondering why would such an impressive innovation fail to record colors? A process of trials and errors then started (including the most successful and pioneer one, involving the use of potato starch, by Lumière brothers) aiming to add colors to photographs, till the consolidation of new systems (camera and film) capable to collect photographs directly in color. In the past, before and during this innovative approach, native black and white photographs were painted in the effort to give them life. Today, only few methods are available to convert a panchromatic image into a color one, and they need a number of steps and further development to work properly. The paper tries to present different methods to colorize native black and white photographs, based on available automatic or interactive Artificial Intelligence (Machine Learning or Deep Learning) algorithms, on revised remote sensing procedures and on visual tricks, aiming at exploring the possible improvement in readability and interpretation of photographed contests in the usual analytic process of photo-interpretation. At the same time, colorized historical photographs hold different appeal in the general public and have the potential to attract and involve non-experts in the archaeological/historical reconstruction phases. [ABSTRACT FROM AUTHOR]

Image quality assessment (IQA) is significant for current techniques of image-based computer-aided diagnosis, and fundus imaging is the chief modality for screening and diagnosing ophthalmic diseases. However, most of the existing IQA datasets are single-center datasets, disregarding the type of imaging device, eye condition, and imaging environment. In this paper, we collected a multi-source heterogeneous fundus (MSHF) database. The MSHF dataset consisted of 1302 high-resolution normal and pathologic images from color fundus photography (CFP), images of healthy volunteers taken with a portable camera, and ultrawide-field (UWF) images of diabetic retinopathy patients. Dataset diversity was visualized with a spatial scatter plot. Image quality was determined by three ophthalmologists according to its illumination, clarity, contrast and overall quality. To the best of our knowledge, this is one of the largest fundus IQA datasets and we believe this work will be beneficial to the construction of a standardized medical image database. [ABSTRACT FROM AUTHOR]

Automated detection of retinal structures, such as retinal vessels (RV), the foveal avascular zone (FAZ), and retinal vascular junctions (RVJ), are of great importance for understanding diseases of the eye and clinical decision-making. In this paper, we propose a novel Voting-based Adaptive Feature Fusion multi-task network (VAFF-Net) for joint segmentation, detection, and classification of RV, FAZ, and RVJ in optical coherence tomography angiography (OCTA). A task-specific voting gate module is proposed to adaptively extract and fuse different features for specific tasks at two levels: features at different spatial positions from a single encoder, and features from multiple encoders. In particular, since the complexity of the microvasculature in OCTA images makes simultaneous precise localization and classification of retinal vascular junctions into bifurcation/crossing a challenging task, we specifically design a task head by combining the heatmap regression and grid classification. We take advantage of three different en face angiograms from various retinal layers, rather than following existing methods that use only a single en face. We carry out extensive experiments on three OCTA datasets acquired using different imaging devices, and the results demonstrate that the proposed method performs on the whole better than either the state-of-the-art single-purpose methods or existing multi-task learning solutions. We also demonstrate that our multi-task learning method generalizes across other imaging modalities, such as color fundus photography, and may potentially be used as a general multi-task learning tool. We also construct three datasets for multiple structure detection, and part of these datasets with the source code and evaluation benchmark have been released for public access. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to present a method of color three-dimensional (3D) printing based on color adherence.Design/methodology/approach First, experiments of the color effects of 3D printings using different carriers and different printing methods were performed. Second, the color of a specific point could be calculated through a theory of dimension-reducing, and the color distribution of 3D model was transformed from 3D to 1D color line corresponding with 3D print sequence. At last, the color lines, which were printed on a PE film by silk-screen printing, was carried by a filament and then printed through a fused deposition modeling 3D printer.Findings The printing ink and PE film are suitable as the pigment and carrier under this investigation, respectively. Based on an idea of reducing dimension, the method of 3D color printing through adhering color to a filament is realized. The color saturation of the sample was relatively high through the method.Research limitations/implications It is hard to avoid that there may be some residual color in the nozzle through this method, and the purity of following color will be affected. As a result, continuous improvements should be made to perfect the method.Practical implications An approach of 3D color printing is described in detail, and what kind of model is more applicable is discussed particularly.Originality/value This approach is implemented to print color 3D objects with just one nozzle by means of color adherence. That is, printing the 3D objects using the filament is carried out with 1D color line, which is printed by a traditional printing method. [ABSTRACT FROM AUTHOR]

The article offers information about the journal including the submission of a transaction paper, the style of manuscript and the color photo charges.

This paper presents an algorithm for identifying a pattern in an image, by using the "crosscorrelation" technique. In addition, it shows the difficulties of implementing the algorithm in a video stream context and the solutions applied to remedy these shortcomings. The modified "template matching" algorithm manages to process the image in real-time by using downscaling for restricting the search area. Filtering noise, in real time, has applications in speech and image processing. Considerable interest has arisen in recent years regarding filtering in the wavelet transform domain. This technique has been effective in noise removal with minimum side effects on important features such as image details and edges. In this paper, the effectiveness of both soft and hard thresholding for desired detail levels has been demonstrated. Python implementation is proposed due to its simplicity. This article presents an image conversion method from color space to grayscale, using Fourier transform on luminance and chrominance channels. The method keeps the image chromatic contrast, which could be lost in case of a simple luminance channel extraction. Frequency domain naturally offers the contrast values on all channels, in all spatial scales. Consequently, there are just arithmetic operations necessary to factorize chromatic differences in final intensity of the image, so the image processing speed is raised up considerably. [ABSTRACT FROM AUTHOR]

The most common imaging methods used in dentistry are X-ray imaging and RGB color photography. However, both imaging methods provide only a limited amount of information on the wavelength-dependent optical properties of the hard and soft tissues in the mouth. Spectral imaging, on the other hand, provides significantly more information on the medically relevant dental and oral features (e.g. caries, calculus, and gingivitis). Due to this, we constructed a spectral imaging setup and acquired 316 oral and dental reflectance spectral images, 215 of which are annotated by medical experts, of 30 human test subjects. Spectral images of the subjects' faces and other areas of interest were captured, along with other medically relevant information (e.g., pulse and blood pressure). We collected these oral, dental, and face spectral images, their annotations and metadata into a publicly available database that we describe in this paper. This oral and dental spectral image database (ODSI-DB) provides a vast amount of data that can be used for developing, e.g., pattern recognition and machine vision applications for dentistry. [ABSTRACT FROM AUTHOR]

The present work intends to focus on the examination, analysis and treatment of Pace, a contemporary color photography experimental artwork created by Nino Migliori in 1973. Given the particular nature of the artifact, in which the photographic materials and the media of contemporary art coexist in a complex interaction, an in-depth study of its creation, structure and components was deemed necessary to plan and perform an adequate conservation treatment. The preliminary research was conducted in order to contextualize the artwork within the author's production, to understand the creation process, to identify the photographic technique of the print and the stratigraphic sequencing, and to characterize the constituent materials of each layer through non-invasive and micro-invasive diagnostic analysis. The severe detachments and lifts of the print from the underlying aluminum panel and the subsequent planarity alterations of the photograph, strongly compromised the legibility of the artwork and put its future conservation at risk. Therefore, the elaboration of a minimally invasive intervention methodology was required. Approaching contemporary works of art, which are at the same time also photographic objects, can present some theoretical and practical challenges, and in the near future lots of professionals in the field of art conservation are probably going to face analogue conservation problems on similar objects. The results obtained through the preliminary study phase and the conservation treatment may offer a good starting point for further research on how to examine, analyze and treat this kind of photographic objects. [ABSTRACT FROM AUTHOR]

Photography is dominant illustration technique. Two-thirds of illustrations are realised in this technique most in commonly in the digital photography system. The portrait is one of the most present and most challenging photographic motifs which can be, in a technical sense, analysed primarily through monitoring of the changes in the skin colours. Modern publishing is characterised by increasing number of small circulations created in electrophotographic printing and, parallel, in electronic media. This paper deals with the portrait photography created on the computer monitor and with electrophotographic printing and the question if they can be, for consumers, considered to be the same. The evaluation was attended by the visual comparison based on the principle of memory harmonisation and ΔE00determination. The results point out satisfactory reproduction in the electrophotographic printing of colour portrait photography in comparison to the portrait defined on the computer monitor, although the reproduction results in colour changes for skin colours and primary and secondary colours of additive and subtractive synthesis. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an automatic and effective cloud detection algorithm for color aerial photographs. Based on the properties derived from observations and statistical results on a large number of color aerial photographs with cloud layers, we present a novel progressive refinement scheme for detecting clouds in the color aerial photographs. We first construct a significance map which highlights the difference between cloud regions and noncloud regions. Based on the significance map and the proposed optimal threshold setting, we obtain a coarse cloud detection result which classifies the input aerial photograph into the candidate cloud regions and noncloud regions. In order to accurately detect the cloud regions from the candidate cloud regions, we then construct a robust detail map derived from a multiscale bilateral decomposition to guide us in removing noncloud regions from the candidate cloud regions. Finally, we further perform a guided feathering to achieve our final cloud detection result, which detects semitransparent cloud pixels around the boundaries of cloud regions. The proposed method is evaluated in terms of both visual and quantitative comparisons, and the evaluation results show that our proposed method works well for the cloud detection of color aerial photographs. [ABSTRACT FROM PUBLISHER]

Abstract: Louis Ducos du Huron (1837–1920) dedicated his entire life to the elaboration of physical–chemical processes for color photography. This study aimed at highlighting his unique contribution to three‐color printing through 1) an in‐depth review of the many protocols he published and 2) the synchrotron‐based IR and X‐ray microanalysis of fragments sampled in three artworks. Ducos du Hauron's method relied on the preparation and assembly of three monochromes (red, blue, yellow). This study brings to light complex multistep recipes based on photochemistry (carbon print), organic, and inorganic chemistry. The various ingredients involved (e.g., pigments, dichromate gelatin, collodion, resin) were identified and localized through their spectroscopic signature, confirming the relevance of synchrotron spectromicroscopy for the characterization of historical photographs. The impressive correlation between texts and chemical analyses calls for a wider application to the history of photography. [ABSTRACT FROM AUTHOR]

The imagistic evaluation of non-neovascular age-related macular degeneration (AMD) is crucial for diagnosis, monitoring progression, and guiding management of the disease. Dry AMD, characterized primarily by the presence of drusen and retinal pigment epithelium atrophy, requires detailed visualization of the retinal structure to assess its severity and progression. Several imaging modalities are pivotal in the evaluation of non-neovascular AMD, including optical coherence tomography, fundus autofluorescence, or color fundus photography. In the context of emerging therapies for geographic atrophy, like pegcetacoplan, it is critical to establish the baseline status of the disease, monitor the development and expansion of geographic atrophy, and to evaluate the retina's response to potential treatments in clinical trials. The present review, while initially providing a comprehensive description of the pathophysiology involved in AMD, aims to offer an overview of the imaging modalities employed in the evaluation of non-neovascular AMD. Special emphasis is placed on the assessment of progression biomarkers as discerned through optical coherence tomography. As the landscape of AMD treatment continues to evolve, advanced imaging techniques will remain at the forefront, enabling clinicians to offer the most effective and tailored treatments to their patients. [ABSTRACT FROM AUTHOR]

Age-related macular degeneration (AMD) ranks third among the most common causes of blindness. As the most conventional and direct method for identifying AMD, color fundus photography has become prominent owing to its consistency, ease of use, and good quality in extensive clinical practice. In this study, a convolutional neural network (CSPDarknet53) was combined with a transformer to construct a new hybrid model, HCSP-Net. This hybrid model was employed to tri-classify color fundus photography into the normal macula (NM), dry macular degeneration (DMD), and wet macular degeneration (WMD) based on clinical classification manifestations, thus identifying and resolving AMD as early as possible with color fundus photography. To further enhance the performance of this model, grouped convolution was introduced in this study without significantly increasing the number of parameters. HCSP-Net was validated using an independent test set. The average precision of HCSPNet in the diagnosis of AMD was 99.2%, the recall rate was 98.2%, the F1-Score was 98.7%, the PPV (positive predictive value) was 99.2%, and theNPV (negative predictive value)was 99.6%.Moreover, a knowledge distillation approach was also adopted to develop a lightweight student network (SCSP-Net). The experimental results revealed a noteworthy enhancement in the accuracy of SCSP-Net, rising from 94% to 97%, while remarkably reducing the parameter count to a quarter of HCSP-Net. This attribute positions SCSP-Net as a highly suitable candidate for the deployment of resource-constrained devices, which may provide ophthalmologists with an efficient tool for diagnosing AMD. [ABSTRACT FROM AUTHOR]

In the present paper, we propose an image contrast enhancement method that can enhance the contrast of a color image naturally by taking account of a color space shape. The proposed method realizes the natural enhancement based on two kinds of intensity histograms: a gradient-norm-based histogram and an ideal histogram derived from the shape of a color space. The former histogram is used to suppress over-enhancement in the flat regions of an image and the latter histogram is used to prevent the whole image from being darken. Concretely, the aforementioned intensity histograms are appropriately mixed into a histogram with a weight based on the average intensity of the input image. The contrast enhancement of the input image is realized using the cumulative histogram of the mixed histogram as an intensity transform function. To verify the validity of the proposed method, in experiments, the proposed method is applied to a variety of images and experimental results are evaluated qualitatively and quantitatively. [ABSTRACT FROM AUTHOR]

Super-resolution (SR) is a technology to reconstruct a clear high-resolution image with plausible details according to one or a group of observed low- resolution images. However, many existing methods require the help of 'tools', which results in high time and memory costs for training and storing these 'tools'. This paper proposes an SR method that can be executed without these training 'tools'. This method comprises two stages: color channel adaptive combination and regularization. In the first stage, color channel adaptive combination assembles the textures captured by different color channels into the luminance component. This strategy is helpful in effectively utilizing the luminance information of different light bands. In the second stage, an improved total variation (TV) regularization method is proposed to suppress artifacts and sharpen edges. The TV regularization adds a new item in the iteration formula to enable the edges to be similar to the desired high-resolution image. Next, iterative back projection is used to fit the high-resolution image to the observed low-resolution image. The experimental results demonstrate that the proposed algorithm is superior to many existing learning-based methods and has low time cost. [ABSTRACT FROM AUTHOR]

This paper introduces a new method for detecting and localizing hand landmarks in 2D color images. Location of the hand landmarks is an important source of information for recognizing hand gestures, effectively exploited in a number of recent methods which operate from the depth maps. However, this problem has not yet been satisfactorily solved for 2D color images. Here, we propose to analyze the skin-presence masks, as well as the directional image of a hand using the distance transform and template matching. This makes it possible to detect the landmarks located both at the contour and inside the hand masks. Moreover, we performed an extensive experimental study to compare the proposed method with a number of state-of-the-art algorithms. The obtained quantitative and qualitative results clearly indicate that our approach outperforms other methods, which may help improve the existing gesture recognition systems. [ABSTRACT FROM AUTHOR]

The segmentation of diabetic retinopathy (DR) lesions is important for large-scale screening using color fundus photography (CFP) images. The difficulty of this task is that the DR lesions have various sizes, shapes, and intensities. Traditional handcrafted feature-based approaches are unsatisfactory, and recent deep-learning-based approaches ignore the features of DR lesions. In this paper, we propose a segmentation approach that segments four typical DR lesions simultaneously based on convolutional neural networks (CNN). The raw CFP image is first pre-processed and resized to different sizes. A set of fully convolutional neural networks (FCN) with various input sizes are then trained to extract the lesions from different scales. An auxiliary CNN is then introduced to fuse the output from these FCN and refine the segmentation result. We conducted our experiments on one local dataset and four public datasets including IDRiD, DDR, E-ophtha, and DIARETDB1. The results of the area under the precision–recall-curve (AUPR) and the dice similarity coefficient (DSC) show that our approach achieves competitive performance. The improvement in performance indicates that this approach is beneficial to DR lesion segmentation and has potential in other segmentation tasks. • Designing a novel method for DR lesion segmentation that outperforms current state-of-the-art approaches. • Developing multi-scale segmentation and fusion networks to integrate information from various receptive fields. • Introducing the idea of multi-task learning to segment lesions simultaneously. • Experiments on images captured from various cameras increase the diversity of the distribution. [ABSTRACT FROM AUTHOR]

Purpose: To assess retinal function in areas of presumed fibrosis due to neovascular age-related macular degeneration (nAMD), using multimodal imaging and structure-function correlation. Design: Cross-sectional observational study. Methods: 30 eyes of 30 consecutive patients with nAMD with a minimum history of one year of anti-vascular endothelial growth factor therapy were included. Each patient underwent microperimetry (MP), color fundus photography (CFP), standard spectral-domain-based OCT (SD-OCT), and polarization sensitive-OCT (PS-OCT) imaging. PS-OCT technology can depict retinal fibrosis based on its birefringence. CFP, SD-OCT, and PS-OCT were evaluated independently for the presence of fibrosis at the corresponding MP stimuli locations. MP results and morphologic findings in CFP, SD-OCT, and PS-OCT were co-registered and analyzed using mixed linear models. Results: In total, 1350 MP locations were evaluated to assess the functional impact of fibrosis according to a standardized protocol. The estimated means of retinal areas with signs of fibrosis were 12.60 db (95% confidence interval: 10.44–14.76) in CFP, 11.60 db (95% COI: 8.84–14.36) in OCT, and 11.02 db (95% COI 8.10–13.94) in PS-OCT. Areas evaluated as subretinal fibrosis in three (7.2 db) or two (10.1 db) modalities were significantly correlated with a lower retinal sensitivity than a subretinal fibrosis observed in only one (15.3 db) or none (23.3 db) modality (p < 0.001). Conclusions: CFP, SD-OCT and PS-OCT are all suited to detect areas of reduced retinal sensitivity related to fibrosis, however, a multimodal imaging approach provides higher accuracy in the identification of areas with low sensitivity in MP (i.e., impaired retinal function), and thereby improves the detection rate of subretinal fibrosis in nAMD. [ABSTRACT FROM AUTHOR]

Early detection and timely cure of ocular disease play a vital role to avoid irreversible vision issues in daily life. The technique fundus assessment utilizes color fundus photography, which is a very effective tool though it is expensive. Since rare symptoms of the disease are detected at the initial stage of the disease, still automated and optimized models are in urgent need for the detection of the ocular disease. Additionally, existing systems focus on image-level detection for the treatment of eyes without association employing the left and right eye information. Although they concentrate only on one or two features of the ocular disease at a time. Taking into consideration severity detection and multilabel categorization plays a vital role in ocular disease detection. So, we develop a framework to detect the disease in the early phase. And then apply the classification model for the multilabel classification of the disease. our proposed experimental result proves that the proposed Custom net model provides 99.15% of accuracy compared to the existing baseline model such as Vgg16, 19, Resnet-50 and Inception V3. The performance optimization of the proposed model is evaluated on the public datasets. [ABSTRACT FROM AUTHOR]

Background: Torpedo maculopathy (TM) is a rare, congenital condition characterized by an oval-shaped, chorioretinal lesion in the temporal macula of unknown etiology. To our knowledge, the longest reported follow-up of TM is 5 years. Herein we report 10 years of follow-up on two patients with TM to further characterize the long-term natural history of the condition. Case reports: Two patients with torpedo maculopathy were examined at baseline and then again at 5 years and 10 years from baseline. Eyes were evaluated using color fundus photography, automated perimetry, fundus autofluorescence and spectral domain optical coherence tomography. Visual function of both patients remained stable throughout the observation period. In case 1, there was no evidence of change in lesion morphology over the 10 year observation period. Case 2 showed progression of cystic degeneration of the neurosensory retina within the torpedo lesion. Case 1 reported a history of supernumerary teeth and underwent gene sequence with deletion/duplication analyses of the APC gene but no clinically significant variants were detected. Conclusions: Our findings support the position that TM is a nonprogressive condition with long-term stability of visual function. Genetic analysis of case 1 failed to detect any association with Gardner syndrome. [ABSTRACT FROM AUTHOR]

This 1867 document, akin to a patent application for the US Patent Office, is among the first to describe processes for producing both motion and color photography. It precedes by 20 years Edison's 1888 kinetograph/kinetoscope design, the earliest working prototype of cinema. Its author is Charles Cros, who also outlined a phonograph system in 1877, a few months before Edison displayed his working phonograph. Cros is mostly known as a poet, fiction writer and playwright associated with members of the French Symbolist and Decadent movements (Arthur Rimbaud, Paul Verlaine, Auguste Villiers de l'Isle-Adam). Yet he was an accomplished technician and inspired media innovator who deserves reconsideration in media history. Evidence of his status comes for instance from his close collaboration with Jules-Adrien Carpentier, the very engineer the Lumière Brothers tasked with constructing their Cinématographe camera. Sent to and received by the French Academy of Sciences, this document is in three parts. The first describes with prescient specificity the photographic synthesis of motion. The second offers several ways of achieving the photographic synthesis of color using filters and projection (rather than pigment and print, as later achieved in the 1890s). The last and more cryptic section concerns an ambitious theory of perception. Unpublished in French until 1970, this document will be of wide interest to scholars of media history, cinema and photography studies, literary studies, and modernist studies. The introductory essay makes a strong case for rehabilitating Charles Cros as a key inceptor of modern audiovisual media. [ABSTRACT FROM AUTHOR]

This paper introduces a course titled „Preventative Document Protection" which is currently a part of the „Mediamatics and Cultural Heritage" curriculum in the „Library and Information Studies" program of the University of Žilina and aims to provide students with knowledge and skills related to the protection of documents in institutions dedicated to archiving and heritage protection and preservation. As a part of the most recent iteration of the course, students conducted research on modeling accelerated aging of materials exposed to increased temperature, humidity and light, tested the effect of different chemical compounds and their neutralization on black and white photographs and surveyed color photographs and slides in the funds of the Slovak National Library in Martin and various private collections. Such surveys are helpful when developing a manual for the identification of unprovenanced photographs and slides. We also addressed the issue of color theory using the CIE LAB color space and implementation of the Preservation Index (PI) as proposed by the Image Permanence Institute (Rochester) to estimate the shelf life of unstable materials. The objective of this research is to create a manual for the long-term prognosis of the condition of unstable materials. Students enrolled in this course have made a significant contribution to the creation of this manual. [ABSTRACT FROM AUTHOR]

Color camera characterization, mapping outputs from the camera sensors to an independent color space, such as XY Z, is an important step in the camera processing pipeline. Until now, this procedure has been primarily solved by using a 3 × 3 matrix obtained via a least-squares optimization. In this paper, we propose to use the spherical sampling method, recently published by Finlayson et al., to perform a perceptual color characterization. In particular, we search for the 3 × 3 matrix that minimizes three different perceptual errors, one pixel based and two spatially based. For the pixel-based case, we minimize the CIE ΔE error, while for the spatial-based case, we minimize both the S-CIELAB error and the CID error measure. Our results demonstrate an improvement of approximately 3% for the ΔE error, 7% for the S-CIELAB error and 13% for the CID error measures. [ABSTRACT FROM AUTHOR]

• Early detection of Diabetes-1 and Diabetes-2 from the transfer learning-based CNN architecture on color fundus photography. • Overfitting issue in CNN is resolved using the transfer learning technique and hence small datasets can be used for analysis. • A contrast enhancement pre-processing technique is used to preserve the brightness for effective analysis. Diabetic Retinopathy is a complication based on patients suffering from type-1 or type-2 diabetes. Early detection is essential as complication can lead to vision problems such as retinal detachment, vitreous hemorrhage and glaucoma. The principal stages of diabetic retinopathy are non-Proliferative diabetic retinopathy and Proliferative diabetic retinopathy. In this paper, we propose a transfer learning based CNN architecture on colour fundus photography that performs relatively well on a much smaller dataset of skewed classes of 3050 training images and 419 validation images in recognizing classes of Diabetic Retinopathy from hard exudates, blood vessels and texture. This model is extremely robust and lightweight, garnering a potential to work considerably well in small real time applications with limited computing power to speed up the screening process. The dataset was trained on Google Colab. We trained our model on 4 classes - I)No DR ii)Mild DR iii)Moderate DR iv)Proliferative DR, and achieved a Cohens Kappa score of 0.8836 on the validation set along with 0.9809 on the training set. [ABSTRACT FROM AUTHOR]

Introduction: Age-related macular degeneration (AMD) is an eye disease that occurs in patients over 50 years old. Early diagnosis enables timely treatment to stabilize disease progression. However, the fact that the disease is asymptomatic in its early stages can delay treatment until it progresses. As such, screening in specific contexts can be an early detection tool to reduce the clinical and social impact of the disease. Objective: Assess the effectiveness of screening methods for early detection of AMD in adults aged 50 years or older. Methods: A systematic review of comparative observational studies on AMD screening methods in those aged 50 years or older, compared with no screening or any other strategy. A literature search was conducted in the MEDLINE (via PubMed), Embase, Cochrane Library and Lilacs database. Results: A total of 5,290 studies were identified, three of which met the inclusion criteria and were selected for the systematic review. A total of 8,733 individuals (16,780 eyes) were included in the analysis. The screening methods assessed were based on optical coherence tomography (OCT) compared with color fundus photography, and OCT and telemedicine testing compared to a standard eye exam. Conclusion: The systematized data are limited and only suggest satisfactory performance in early screening of the population at risk of developing AMD. OCT and the telemedicine technique showed promising results in AMD screening. However, methodological problems were identified in the studies selected and the level of evidence was considered low. [ABSTRACT FROM AUTHOR]

Ocular diseases are a prevalent disease among the aging population across the world. The retinal damage and vision loss can be substantially decreased through early-stage diagnosis with computer-aided ocular disease diagnosis. With the use of color fundus photography for obtaining digital retinal fundus images, there is a growth in the online accessibility of digital fundus images. For diagnosing ocular diseases, an attempt was made to model graphs from images for feature learning. Three feature detection algorithms, namely scale-invariant feature transform, binary robust invariant scalable keypoints and oriented fast and rotated BRIEF (ORB) techniques are computed individually. As graphs are represented in the non-Euclidean domain, the graph neural network is used to learn the node embedding to model the network for ocular disease diagnosis. Three distance measures: the Euclidean, Manhattan and Chebyshev distances, are computed for analyzing the discriminative power of the model. The proposed RDD-Net model is trained and evaluated on the ODIR-2019 dataset with eleven different performance indicators. The results show that mapping images to non-Euclidean geometric space have obtained a successful diagnosis of ocular diseases from digital fundus images. The ORB descriptor outperforms the other two feature descriptors as well as the existing algorithms for ocular disease diagnosis. Results of the Chebyshev distance measure show superior performance when compared to the other two distance measures based on computation time and performance evaluation metrics. The proposed RDD-Net achieves an F1-score of 0.9970 and a sensitivity of 0.9969 with the ORB descriptor and shows state-of-the-art performance. [ABSTRACT FROM AUTHOR]

The article offers information related to Pantone Matching System, a color standardization system that helps in color identification and matching. It mentions use of the Pantone numbering system to identify colors, and through this numbering system printer and other equipment manufacturers can match colors without having to contact one another.

Early eye examination based on fundus images effectively prevents visual impairment caused by retinopathy. The laborious and error-prone process of interpreting fundus images and the lack of ophthalmologists have driven research toward automated retinopathy diagnosis. However, most previous studies have focused on single-modality fundus images, disregarding the integration of information from multiple views, rendering the results unsatisfactory and inconsistent with clinical practice due to the incomprehensive lesion features and incomplete fundus fields. To address this issue, we introduce multi-modality and multi-view fundus images into the automated retinopathy diagnosis pipeline. In contrast to single fundus images, sequential relationships in multi-modality and multi-view fundus images contain essential long-range dependency information, which is vital for retinopathy diagnosis. Inspired by the recent success of transformers for excavating long-range dependencies in sequence data, in this paper, we propose a transformer-based automated retinopathy diagnosis framework for pathology classification and symptom report generation by integrating multi-modality and multi-view fundus images. Specifically, we present two transformer-based networks to construct long-range dependencies in different fundus images. Moreover, we adopt two novel modules to aggregate features of different modalities and views by modeling long-range dependencies among different fundus image sequences. Experiments are conducted on two in-house datasets, in which each subject provides one color fundus photography image and four-view fundus fluorescein angiography images. The experimental results of retinopathy classification and report generation tasks indicate that our proposed method is superior to other benchmarking methods, achieving a classification accuracy of 85.49% and a report generation BlEU-1 of 0.422. • A multi-modality and multi-view framework for automated retinopathy diagnosis. • Transformers for modeling intra-modality and intra-view long-range dependency. • A multi-view fusion embedding module for modeling inter-view long-range dependencies. • A multi-modality fusion embedding module for modeling inter-modality long-range dependencies. • Extensive experiments on three different tasks demonstrate the effectiveness of our models. [ABSTRACT FROM AUTHOR]

Outdoor images are often degraded by haze, resulting in a distinctive gray or bluish hue which diminishes visibility. Of the existing haze removal methods, the ones that are effective are computationally complex and memory intensive. In this paper, we propose a simple haze removal technique, whose computational complexity is that of a simple convolution. To this purpose, a center surround filter is employed to improve speed and memory requirements of the transmission estimation in image dehazing. This can be useful for real time applications such as driver assistance, runway hazard detection and surveillance. The proposed technique relies on deriving an alternative transmission estimate by filtering the input image in three different color spaces, namely RGB, Lab and HSV. The effectiveness of the proposed method is compared with that of other state of the art methods using a subjective quality assessment method and a number of objective quality assessment methods. [ABSTRACT FROM AUTHOR]

Modifying the colors of an image is a fundamental editing task with a wide range of methods available. Manipulating multiple images to share similar colors is more challenging, with limited tools available. Methods such as color transfer are effective in making an image share similar colors with a target image; however, color transfer is not suitable for modifying multiple images. Approaches for color consistency for photo collections give good results when the photo collection contains similar scene content, but are not applicable for general input images. To address these gaps, we propose an application framework for achieving color consistency for multi-image input. Our framework derives a group color theme from the input images′ individual color palettes and uses this group color theme to recolor the image collection. This group-theme recoloring provides an effective way to ensure color consistency among multiple images and naturally lends itself to the inclusion of an additional external color theme. We detail our group-theme recoloring approach and demonstrate its effectiveness on a number of examples. [ABSTRACT FROM AUTHOR]

Coral reef monitoring is a reliable tool to assess the effect of climate change as corals are sensitive to increases in water temperatures between 30 °C and 35 °C resulting in bleaching - a whitening process when the corals lose their color and the reefs begin to die. Existing satellite-based monitoring products facilitate coral bleaching monitoring over large spatial scales, but their use in predicting local scale stress that influences the bleaching severity across reefs is limited. In this paper, we describe a Stationary Reef Monitoring System (SRMS) that monitors the time evolution of coral reefs through the photography of nearby coral clusters. Simultaneously, the SRMS measures and records environmental parameters such as temperature, solar irradiance (PAR), and salinity in the waters surrounding the coral colonies. When deployed in the sea, the SRMS detected a 0.1–0.4 °C variability in temperature between the in situ and satellite datasets. The SRMS uses color photography along with quantitative data on environmental parameters to monitor the health of corals and eliminates the need for physical/visual verification of coral health by a diver. By this approach, one can determine the stress thresholds of corals and identify the vulnerable and resilient reefs so as to prioritize conservation efforts. • The Stationary reef monitoring system is an automated tool to monitor coral reefs. • The SRMS can transmit data directly to shore lab using GSM signals and radio link. • The SRMS uses color photography and minimize the need for SCUBA diver monitoring. • SRMS provides accurate sea truth data for calibrating/validating satellite sensors. [ABSTRACT FROM AUTHOR]

Purpose: To observe fundus autofluorescence (FAF) lifetimes and peak emission wavelength (PEW) of drusen with respect to the pathology of the overlying RPE in the follow‐up of AMD‐patients. Methods: Forty eyes of 38 patients (age: 75.1 ± 7.1 years) with intermediate AMD were included. FAF lifetimes and PEW were recorded by fluorescence lifetime imaging ophthalmoscopy (FLIO). Twenty‐six eyes had a follow‐up investigation between months 12 and 36, and 10 at months 37–72. AMD progression was retrieved from color fundus photography (CFP) and OCT. Drusen were classified with respect to changes in the overlying RPE into groups no, questionable or faint, and apparent hyperpigmentation based on CFP. Results: Among the 210 hyperautofluorescent drusen found at baseline, those with hyperpigmentation had longer lifetimes and shorter PEW than those without. Drusen without hyperpigmentation had shorter lifetimes and PEW than neighboring RPE (all p < 0.001) at baseline, but drusen lifetimes increased, and PEW shortened further over follow‐up. Eyes, showing AMD progression, had significantly longer FAF lifetimes at baseline than non‐progressing eyes: 282 ± 102 ps versus 245 ± 98 ps, p < 0.001 and 365 ± 44 ps vs. 336 ± 48 ps, p = 0.025 for short and long wavelength FLIO channel, respectively. Conclusions: Depending on hyperpigmentation properties, drusen show lifetimes and PEW different from that of adjacent RPE which change over the natural history of AMD. This difference and change, however, might reflect progressive dysmorphia of the RPE rather than representing fluorescence of drusen material itself. Nevertheless, the observed FAF changes could make FLIO a useful tool for the early detection of AMD progression risk. [ABSTRACT FROM AUTHOR]

Introduction: Few studies have explored MultiColor™ imaging (MCI) in evaluating retinal vascular diseases, particularly branch retinal vein occlusion (BRVO). This study aimed to compare the identification of retinal vessel whitening in BRVO using MCI by scanning confocal laser versus conventional white-flash color fundus photography (CFP). Methods: Paired images of consecutive patients diagnosed with BRVO who underwent same-day MCI and CFP were reviewed. Visualization of vessel whitening on MCI and CFP was graded and scored using a scale by two masked graders. A longitudinal analysis of the vessel grading score was performed to evaluate the vessel whitening detection by MCI. A correlation analysis was conducted between vessel whitening on MCI and the measured area of retinal ischemia on fluorescein angiography to evaluate the MCI performance. Results: Forty-four eyes of 41 patients (mean age 69 ± 14 years; 61% female) were analyzed. MCI demonstrated superior vessel whitening visibility score than CFP (p < 0.001). Longitudinal analysis showed no significant changes in vessel whitening visibility scores over a mean follow-up time of 430 ± 648 days (p = 0.655). There was a significantly positive correlation between the grading score of vessels whitening by MCI and the area of ischemia by fluorescein angiography (r2 = 0.15; p = 0.036). Conclusion: MCI appears to provide a superior detection of whitening BRVO compared to CFP, serving as a rapid and non-invasive correlate of retinal ischemia. [ABSTRACT FROM AUTHOR]

Retinal sensitivity may vary by subtypes of cuticular drusen. This retrospective study included 52 eyes of 32 patients with cuticular drusen. All the patients underwent assessment of best-corrected visual acuity (BCVA), spectral-domain optical coherence tomography (SD-OCT), color fundus photography, fluorescein angiography, fundus autofluorescence, and microperimetry. The area occupied by drusen was counted using microperimetry. The cuticular drusen subtype was classified into 3 groups based on the SD-OCT findings. Age, BCVA, pattern standard deviation, area occupied by drusen, pupil size, and the false-positive rate were not significantly different (p > 0.05) according to the cuticular drusen type. The mean retinal sensitivity (MRS) (p = 0.063) and mean deviation (MD) (p = 0.098) showed marginally significant differences among the groups. In the subgroup analyses, type 1 and type 3 cuticular drusen showed significant differences in the MD (− 1.8 ± 2.1 vs − 5.1 ± 5.3; p = 0.011) and MRS (25.1 ± 2.2 vs 21.3 ± 5.7; p = 0.016) without differences in age, BCVA, or the area occupied by drusen (p > 0.05). The results indicate that depending on the subtypes of cuticular drusen type, the deterioration of retinal sensitivity is more likely to occur than decreased vision. [ABSTRACT FROM AUTHOR]

We report on a case series that revealed flat, choroidal lesions on optical coherence tomography (OCT) and on enface MultiColor® (MCI) imaging of the fundus but were not noticeable on clinical examination or conventional color fundus images. This observational study included 12 eyes from 11 patients who had distinct, orange-colored lesions on MCI. Retinal imaging was conducted using conventional color fundus photography and OCT. On the color fundus images and the blue and green reflectance channels of MCI, each of the lesions was difficult to distinguish. On the infrared channel, the lesion was identified as bright white in color and bright orange on the multicolor image. The lesion was identified on OCT as a flat, homogeneous hyperreflective lesion involving the choroid, with an intact overlying retinal pigment epithelium and retinal layers. A comparison of the clinical and imaging features with other known entities led to the conclusion that the lesion was a distinct clinical entity. The presence of melanin in the lesion was confirmed based on the retinal imaging findings and the light absorption properties of melanin. As a result, the lesion was named as 'choroidal melanocytic hamartoma'. A longer follow-up is required to confirm the benign nature of this clinical entity. [ABSTRACT FROM AUTHOR]

This paper designs and implements the monitoring and control systems for tap changer of the distribution transformers by using GSM (global system for mobile) network. The proposed method comprises an embedded system which collects and processes the transformer parameters such as temperature, humidity, silicone gel color, Buchholz relay status, the status of input and output phases, the current flow in each phase and power of each phase. If the parameters exceed the permitted level, the system sends all parameters using the GSM modem through GSM network to the control center, and the center receives and processes them by the GSM modem, and then they are displayed on computer. Furthermore, some commands are sent from the center to change the tap changer position, denoting the transformer position and making report on the transformer parameters. Some advantages of this system can be denoted as extending the lifetime of the transformer, consumers, wires and facilities, no need to the operator, simplifying the troubleshooting in distribution network, balancing the loads and providing customers with proper service. [ABSTRACT FROM AUTHOR]

Simple Summary: Caterpillars and pupae are important sources of evidence for the identification of primitive moths, and they can often provide quite different but useful morphological characters from those of adults. Incurvariidae is one of the most primitive groups of extant Lepidoptera, but half of the genera lack any information on caterpillars and pupae. It is important to increase the knowledge on the immature stages of Incurvariidae. Subclemensia Kozlov, 1987 is one of the monotypic genera in Incurvariidae. In this study, the caterpillar and pupa of the type species of Subclemensia are reported for the first time. The leaf mine, host plant and its biological characteristics are also provided. DNA barcodes were generated to help with the species delimitation. The adult male and female genitalia are re-illustrated by color photography to supplement the original line drawings. The immature stages of primitive Lepidoptera can provide quite different but often useful morphological evidence and synapomorphies from those of adults. Incurvariidae is one of the most primitive lineages of extant Lepidoptera, which is species-poor but highly diverse, but half of the genera lack any information on immature stages. New knowledge on the immature stages of the family is expected to provide useful morphological evidence and synapomorphies to stabilize the generic nomenclature. Subclemensia Kozlov, 1987 is one of the monotypic genera in Incurvariidae. In this study, the immature stages of the type species of Subclemensia are reported for the first time. The leaf mine, host plant and its biological characteristics are also provided. DNA barcodes were generated to aid the species delimitation. The adult male and female genitalia are re-illustrated by color photography to supplement the original line drawings. The generic concepts of Subclemensia and other related genera are discussed based on immature characters. [ABSTRACT FROM AUTHOR]

From the front cover to the back cover there is an artistic flare and a concentrated effort to reproduce stunning photos of minerals. I Pass the Sangiovese and sit a spell to take in a beautifully put together magazine ... i I must confess right off that I have known about this magazine for years but picked it up only in passing at various shows. The format changed again in 1981 to include more color photography and to feature a mineral photograph in color on the cover rather than the club logo. [Extracted from the article]