46 results on '"Gamma correction"'
Search Results
2. Effectual Single Image Dehazing with Color Correction Transform and Dark Channel Prior
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Thomas, Jeena, Raj, Ebin Deni, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Venugopal, K. R., editor, Shenoy, P. Deepa, editor, Buyya, Rajkumar, editor, Patnaik, L. M., editor, and Iyengar, Sitharama S., editor more...
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- 2021
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Catalog
3. Evolution of Contrast and Illumination Adjustment Techniques for Dental Imaging to Assist Effective Implant
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Shashikala, J., Thangadurai, N., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, and Silhavy, Radek, editor more...
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- 2021
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4. Robust Retinal Vessel Segmentation from a Data Augmentation Perspective
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Sun, Xu, Fang, Huihui, Yang, Yehui, Zhu, Dongwei, Wang, Lei, Liu, Junwei, Xu, Yanwu, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Fu, Huazhu, editor, Garvin, Mona K., editor, MacGillivray, Tom, editor, Xu, Yanwu, editor, and Zheng, Yalin, editor more...
- Published
- 2021
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5. Improved Image Enhancement Method Based on Retinex Algorithm
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Zhang, Tingting, Zhu, Weiduo, Li, Yujie, Li, Yun, Li, Bin, Kacprzyk, Janusz, Series Editor, and Lu, Huimin, editor
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- 2020
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6. Artificial Bee Colony-Optimized Contrast Enhancement for Satellite Image Fusion
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Asokan, Anju, Anitha, J., van der Meer, Freek D., Series Editor, Jarocińska, Anna, Series Editor, and Hemanth, D. Jude, editor
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- 2020
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7. Efficient Segmentation Using Gamma Correction with Complement Image of Chinese Rubbing Image
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Huang, Han, Ma, Yong-Li, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Huang, De-Shuang, editor, Bevilacqua, Vitoantonio, editor, and Hussain, Abir, editor more...
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- 2020
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8. Fog Removal of Aerial Image Based on Gamma Correction and Guided Filtering
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Liu, Xinggang, Liu, Changjiang, Lan, Hengyou, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, McDaniel, Troy, editor, Berretti, Stefano, editor, Curcio, Igor D. D., editor, and Basu, Anup, editor more...
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- 2020
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9. A Simple and Enhanced Low-Light Image Enhancement Process Using Effective Illumination Mapping Approach
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Vijay, Vallabhuni, Siva Nagaraju, V., Sai Greeshma, M., Revanth Reddy, B., Suresh Kumar, U., Surekha, C., Tavares, João Manuel R.S., Series Editor, Jorge, Renato Natal, Series Editor, Pandian, Durai, editor, Fernando, Xavier, editor, Baig, Zubair, editor, and Shi, Fuqian, editor more...
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- 2019
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10. Concatenated Frame Image Based CNN for Visual Speech Recognition
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Saitoh, Takeshi, Zhou, Ziheng, Zhao, Guoying, Pietikäinen, Matti, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Chen, Chu-Song, editor, Lu, Jiwen, editor, and Ma, Kai-Kuang, editor more...
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- 2017
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11. Image Enhancement
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Bauer, Jan, Sycev, Andrej, Blankenbach, Karlheinz, Chen, Janglin, editor, Cranton, Wayne, editor, and Fihn, Mark, editor
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- 2016
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12. Experimental Evaluation of Rigid Registration Using Phase Correlation Under Illumination Changes
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Alba, Alfonso, Arce-Santana, Edgar, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Bebis, George, editor, Boyle, Richard, editor, Parvin, Bahram, editor, Koracin, Darko, editor, Pavlidis, Ioannis, editor, Feris, Rogerio, editor, McGraw, Tim, editor, Elendt, Mark, editor, Kopper, Regis, editor, Ragan, Eric, editor, Ye, Zhao, editor, and Weber, Gunther, editor more...
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- 2015
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13. Color in Image and Video
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Li, Ze-Nian, Drew, Mark S., Liu, Jiangchuan, Gries, David, Series editor, Schneider, Fred B., Series editor, Li, Ze-Nian, Drew, Mark S., and Liu, Jiangchuan
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- 2014
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14. DICOM Calibration and GSDF
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Pianykh, Oleg S. and Pianykh, Oleg S., Series editor
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- 2014
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15. Image Display
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Pianykh, Oleg S. and Pianykh, Oleg S., Series editor
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- 2014
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16. Image Enhancement Using Geometric Mean Filter and Gamma Correction for WCE Images
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Suman, Shipra, Hussin, Fawnizu Azmadi, Malik, Aamir Saeed, Walter, Nicolas, Goh, Khean Lee, Hilmi, Ida, Ho, Shiaw hooi, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Loo, Chu Kiong, editor, Yap, Keem Siah, editor, Wong, Kok Wai, editor, Beng Jin, Andrew Teoh, editor, and Huang, Kaizhu, editor more...
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- 2014
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17. Colorimetric Color Spaces
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Mark J. Burge and Wilhelm Burger
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Color calibration ,business.industry ,Computer science ,Photography ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Color space ,White point ,Color model ,Primary color ,Gamma correction ,Computer vision ,Digital printing ,Artificial intelligence ,business ,ComputingMethodologies_COMPUTERGRAPHICS - Abstract
In any application that requires precise, reproducible, and deviceindependent presentation of colors, the use of calibrated color systems is an absolute necessity. For example, color calibration is routinely used throughout the digital print work flow but also in digital film production, professional photography, image databases, etc. One may have experienced how difficult it is, for example, to render a good photograph on a color laser printer, and even the color reproduction on monitors largely depends on the particular manufacturer and computer system. more...
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- 2022
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18. Evolution of Contrast and Illumination Adjustment Techniques for Dental Imaging to Assist Effective Implant
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J. Shashikala and N. Thangadurai
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Dental radiography ,medicine.diagnostic_test ,business.industry ,Image quality ,Computer science ,Radiography ,media_common.quotation_subject ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Process (computing) ,Gamma correction ,Histogram ,medicine ,Contrast (vision) ,Computer vision ,Artificial intelligence ,business ,Histogram equalization ,media_common - Abstract
Dental radiography often suffers from problems associated with low contrast and uneven illumination. The contrast enhancement over low-resolution and poor-quality dental images provide a better interpretation of hidden diagnostic information for carrying out precise pre-operative assessments. However, image-quality is a subjective measure. Therefore, the selection of contrast and illumination adjustment techniques depends on the image of interest and treatment objectives. The proposed study introduced an efficient computational model that automates the process of addressing image quality issues using different pre-processing techniques gamma correction, histogram equalization, linear and non-linear filtering, ROI extraction, and low light image enhancement techniques. The proposed system offers a flexible approach that would enable dental practitioners to select the most suitable enhanced radiographic images to carry out the effective pre-operative assessment, identifying complications and treatment planning towards appropriate implantation. The efficiency of enhancement techniques is validated based on qualitative and quantitative analysis through, PSNR as a performance metrics. more...
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- 2021
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19. Robust Retinal Vessel Segmentation from a Data Augmentation Perspective
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Junwei Liu, Dongwei Zhu, Xu Sun, Yang Yehui, Yanwu Xu, Wang Lei, and Huihui Fang
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Source code ,Computer science ,business.industry ,media_common.quotation_subject ,Perspective (graphical) ,Inference ,Pattern recognition ,Convolutional neural network ,Tree (data structure) ,Gamma correction ,Robustness (computer science) ,Segmentation ,Artificial intelligence ,business ,media_common - Abstract
Retinal vessel segmentation is a fundamental step in screening, diagnosis, and treatment of various cardiovascular and ophthalmic diseases. Robustness is one of the most critical requirements for practical utilization, since the test images may be captured using different fundus cameras, or be affected by various pathological changes. We investigate this problem from a data augmentation perspective, with the merits of no additional training data or inference time. In this paper, we propose two new data augmentation modules, namely, channel-wise random Gamma correction and channel-wise random vessel augmentation. Given a training color fundus image, the former applies random gamma correction on each color channel of the entire image, while the latter intentionally enhances or decreases only the fine-grained blood vessel regions using morphological transformations. With the additional training samples generated by applying these two modules sequentially, a model could learn more invariant and discriminating features against both global and local disturbances. Experimental results on both realworld and synthetic datasets demonstrate that our method can improve the performance and robustness of a classic convolutional neural network architecture. The source code is available at https://github.com/PaddlePaddle/Research/tree/master/CV/robust_vessel_segmentation. more...
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- 2021
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20. An Unsupervised Approach for Extraction of Blood Vessels from Fundus Images
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Dash, Jyotiprava and Bhoi, Nilamani
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- 2018
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21. Algorithm Oriented to the Detection of the Level of Blood Filling in Venipuncture Tubes Based on Digital Image Processing
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Nelson Apfata, Jorge Castillo, and Guillermo Kemper
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Pixel ,Computer science ,Region of interest ,Gamma correction ,Digital image processing ,Image processing ,Segmentation ,Image segmentation ,Thresholding ,Algorithm - Abstract
This article proposes an algorithm oriented to the detection of the level of blood filling in patients, with detection capacity in millimeters. The objective of the software is to detect the amount of blood stored into the venipuncture tube and avoid coagulation problems due to excess fluid. It also aims to avoid blood levels below that required, depending on the type of analysis to be performed. The algorithm acquires images from a camera positioned in a rectangular structure located within an enclosure, which has its own internal lighting to ensure adequate segmentation of the pixels of the region of interest. The algorithm consists of an image improvement stage based on gamma correction, followed by a segmentation stage of the area of pixels of interest, which is based on thresholding by HSI model, in addition to filtering to accentuate the contrast between the level of filling and staining, and as a penultimate stage, the location of the filling level due to changes in the vertical tonality of the image. Finally, the level of blood contained in the tube is obtained from the detection of the number of pixels that make up the vertical dimension of the tube filling. This number of pixels is then converted to physical dimensions expressed in millimeters. The validation results show an average percentage error of 0.96% by the proposed algorithm. more...
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- 2020
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22. Hybrid Krill Herd Algorithm with Particle Swarm Optimization for Image Enhancement
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Elham Pashaei, Nizamettin Aydin, and Elnaz Pashaei
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business.industry ,Computer science ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Particle swarm optimization ,Pattern recognition ,Image processing ,Fuzzy logic ,Screened Poisson equation ,Gamma correction ,Entropy (information theory) ,Mean-shift ,Artificial intelligence ,business ,Histogram equalization - Abstract
Image enhancement, aimed at improving the image contrast and information quality, is one of the most critical steps in image processing. Due to insufficient enhancement and the mean shift problem of conventional image enhancement techniques, new artificial intelligence-based image enhancement approaches have become an inevitable need in image processing. This paper employs the krill herd algorithm (KHA) and particle swarm optimization (PSO) to suggest a novel hybrid approach, called (PSOKHA) for image enhancement. The suggested PSOKHA method is used in search of optimum transfer function parameters to increase the quality of the images. For comparative evaluation, the performance of the PSOKHA is compared with six latest successful enhancement methods: PSO, KHA, screened Poisson equation (SPE), histogram equalization (HE), brightness preserving dynamic fuzzy HE (BPDFHE), and adaptive gamma correction weighted distribution (AGCWD). Experiments results in testing images include a medical image, a satellite image, and a handwritten image, demonstrate that the suggested strategy can produce better enhanced images in terms of several measurement criteria such as contrast, PSNR, entropy, and structure similarity index (SSIM). more...
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- 2020
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23. Fog Removal of Aerial Image Based on Gamma Correction and Guided Filtering
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Changjiang Liu, Hengyou Lan, and Xinggang Liu
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Color constancy ,business.industry ,Computer science ,media_common.quotation_subject ,020207 software engineering ,02 engineering and technology ,Filter (signal processing) ,Image (mathematics) ,Light intensity ,Gamma correction ,Histogram ,0202 electrical engineering, electronic engineering, information engineering ,Contrast (vision) ,020201 artificial intelligence & image processing ,Computer vision ,Artificial intelligence ,business ,Aerial image ,media_common - Abstract
In order to improve the pilots’ perception of the runway and the surrounding things in foggy days and improve the visual effect of aerial images, a combination of Gamma correction and Retinex de-fogging algorithm is proposed for aerial foggy images. First of all, the original image is corrected by Gamma as the guided map, and the light intensity of the aerial image is estimated by the guided filter, and the preliminary fog removal image is obtained by Retinex. In combination with the histogram truncation technique, the output of the image is mapped to between 0 and 255, then a de-fogging enhanced image is achieved. Compared with other de-fogging algorithms, this algorithm has higher contrast and color consistency. more...
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- 2020
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24. Efficient Segmentation Using Gamma Correction with Complement Image of Chinese Rubbing Image
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Han Huang and Ma Yongli
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business.industry ,Computer science ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Image segmentation ,Grayscale ,Thresholding ,Rubbing ,Background noise ,Gamma correction ,Computer vision ,Segmentation ,Artificial intelligence ,Noise (video) ,business - Abstract
For Chinese rubbing image under the complex background, to against its characteristic of low contrast and large noise, we develop a gamma correction enhancement algorithm in which the grayscale space is being conducted before the Otsu’s binarization, experiments on multiple pictures show the superiority of the algorithm. At first, the global contrast is enhanced based on the gamma correct algorithm for the complement image of the Chinese rubbing image. After that, we have implemented optimum global thresholding using Otsu’s method for image segmentation. The experimental results show that our algorithm could correct the background noise of the image and enhance the stroke in the low contrast Chinese rubbing image, and there is no need to denoise in advance. The performance of the algorithm is simple, fast, and produces very good segmentation. more...
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- 2020
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25. Improved Gamma Corrected Layered Adaptive Background Model
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Masashi Nishiyama, Yoshio Iwai, Hiroki Yoshimura, and Kousuke Sakamoto
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Background subtraction ,Pixel ,business.industry ,Covariance matrix ,Computer science ,Oscillation ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,020206 networking & telecommunications ,Improved method ,02 engineering and technology ,Gamma correction ,Shadow ,0202 electrical engineering, electronic engineering, information engineering ,Artificial intelligence ,Hardware_ARITHMETICANDLOGICSTRUCTURES ,business ,Algorithm - Abstract
This paper proposes a method for pixel-based background subtraction with improved gamma correction and a layered adaptive background model (IGLABM). The main problems of background subtraction are background oscillation and shadow. To solve these problems, we have proposed the gamma corrected layered adaptive background model (GLABM), however the performance of GLABM is not sufficient for real scenes. We hence improve the gamma estimation and prepossessing step of GLABM in this study using the covariance matrix of each pixel. We demonstrate the performance of the proposed improved method by comparing it with GLABM and other pixel-based background subtraction methods. more...
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- 2020
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26. Exposure Compensation from a Single Image
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Yuta Muraki, Toshiaki Kondo, Ryo Akamatsu, Ken-ichi Kobori, and Keitaro Kawamori
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Channel (digital image) ,Dynamic range ,business.industry ,Computer science ,media_common.quotation_subject ,Process (computing) ,Luminance ,Image (mathematics) ,Gamma correction ,Contrast (vision) ,Exposure compensation ,Adaptive histogram equalization ,Computer vision ,Artificial intelligence ,business ,media_common - Abstract
We propose a method to convert underexposed/overexposed images to appropriately exposed image from a single image. Digital cameras have a limited dynamic range which is smaller than one in the real world, so that it often takes overexposed/underexposed images. The HDR method synthesizes images with different exposures into an image to improve visibility of a narrow dynamic range image. However, HDR has several limitations to get good images. One of them is difficult to take the appropriate multiple exposed images. Because When taking the multiple exposed images, the camera and object must not move to avoid the ghost effect. The proposed method can improve the narrow dynamic range with a single image. In addition, it can avoid to generate ghost effect in the output image. Our method generates three of the pseudo multiple exposed images from a single image. In the process of generating pseudo high exposed and low exposed image, our method uses gamma correction to adjust luminance of input image. Moreover, gamma correction can enhance the difference between each color channel in the dark or bright area of the input image. Because of gamma correction, the contrast of the input image is properly improved. We utilize the Contrast Limited Adaptive Histogram Equalization (CLAHE) to make the pseudo middle exposed image. Three types of pseudo exposed images generated will be synthesized into an output image which is high quality image as same as HDR image. more...
- Published
- 2020
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27. Development of Framework for Greenness Identification
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Chandrika Dabariya and Rajeev Kumar Singh
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Identification (information) ,Index (economics) ,Gamma correction ,Initial phase ,medicine ,food and beverages ,Agricultural engineering ,Vegetation Index ,medicine.symptom ,Vegetation (pathology) ,Leaf development ,Mathematics - Abstract
In this paper, an enhanced approach for greenness identification from organic carrot crop while the carrot plants were in the initial phase of authentic leaf development is proposed. This paper proposes an enhancement gamma correction and optimization contrast techniques which is worked with vegetation index-based methods for identification of greenness. In this paper, the enhancement of vegetation index-based methods examined its efficiency by comparing it with performances of vegetative index-based methods that have lately been commonly used. The findings showed that the accuracy of vegetation extraction was considerably better than existing methods by the proposed method. more...
- Published
- 2020
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28. Artificial Bee Colony-Optimized Contrast Enhancement for Satellite Image Fusion
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J. Anitha and Anju Asokan
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Discrete wavelet transform ,Image fusion ,Mean squared error ,business.industry ,Computer science ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Pattern recognition ,Gamma correction ,Computer Science::Computer Vision and Pattern Recognition ,Entropy (information theory) ,Artificial intelligence ,business ,Change detection ,Histogram equalization ,Hue - Abstract
Image fusion combines two or more images to a single image to extract all the necessary information from the source images. It minimizes the redundant information present in the source images. Fused images find wide applications in medical imaging, computer vision, remote sensing, change detection, and military applications. The success of the fusion technique is limited by the noise present in the source images. In order to overcome this limitations, an artificial bee colony (ABC)-optimized contrast enhancement for satellite image fusion is proposed to fuse two multitemporal satellite images. The ABC-optimized source images are given as input to the fusion stage. A hybrid contrast enhancement technique combining the histogram equalization and gamma correction techniques is used for the contrast enhancement of the source images. The contrast-enhanced images are fused using Discrete Wavelet Transform (DWT), Principle Component Analysis (PCA), and Intensity, Hue, Saturation Transform (IHS) individually. The proposed work further compares these conventional fusion techniques by computing performance measures for image fusion such as Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), entropy, Structural Similarity Index (SSIM), and Feature Similarity Index (FSIM). The experimental results show that the IHS-based image fusion technique outperforms the PCA- and DWT-based fusion techniques. Also, this method is computationally effective and simple in its implementation. more...
- Published
- 2019
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29. Analysis of Structural MRI Using Functional and Classification Approach in Multi-feature
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V. Sathya Preiya, A. P. Vijayakumar, and Devi Ramakrishnan
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Contrast enhancement ,medicine.diagnostic_test ,Pixel ,business.industry ,Iterative method ,Computer science ,Cumulative distribution function ,Magnetic resonance imaging ,Pattern recognition ,Gamma correction ,medicine ,Segmentation ,Artificial intelligence ,Cluster analysis ,business - Abstract
Magnetic resonance imaging (MRI) is adjacent to nature and a multi-modality practice which provides the complementary in sequence about dissimilar aspects of diseases. As a competent image (CET) contrast enhancement tool, (AGC) adaptive gamma correction control which was relating with gamma parameter and (CDF) cumulative distribution function in the conventional method which is to engender the function of the pixel gray levels contained by an image. AGC should deals well within the most dimmed images, but fails for worldwide intense images and also the dimmed images within the local bright regions. Such two categories of images which are observed from MRIs, the brightness-distorted images are widespread in genuine scenario, such as to the improper exposure and to the white object regions. To attenuate such kind of deficiencies here we intend an improved the aspects by two methods which are (RIC) region by iteration method of convolution and (S-KC) segmentation by k-levels of clustering. In this proposed work the above given two methods are used by iteration method and the other segmentation in multiple levels of clustering which is to enhance the required response of the MRIs. Both the levels and methods are analyzed in a closed system which to eliminate the unwanted signals and to get the better performance in the MRIs imaging. more...
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- 2019
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30. Improved Image Enhancement Method Based on Retinex Algorithm
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Bin Li, Tingting Zhang, Yun Li, Weiduo Zhu, and Yujie Li
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Retinex algorithm ,Brightness ,Color constancy ,Computer science ,business.industry ,Visibility (geometry) ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,020206 networking & telecommunications ,02 engineering and technology ,Image (mathematics) ,Gamma correction ,Iterative refinement ,Computer Science::Computer Vision and Pattern Recognition ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Computer vision ,Artificial intelligence ,business ,Histogram equalization - Abstract
In order to improve the visibility of foggy images, this paper uses two models to iteratively refine the image. In the first model, the image is first enhanced by histogram equalization and then enhanced by the Retinex algorithm. In the second model, the image is firstly enhanced with the Retinex algorithm, and then the gamma correction is used to adjust the brightness. From a theoretical analysis and practical experiments, this method improves the sharpness of the image while enhancing the image detail information and restoring the image color. more...
- Published
- 2019
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31. Speckle Reduction for Fourier Ptychographic Reconstruction Using Gamma-Correction and Reshaped Wirtinger Flow Optimization
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Desheng Wen, Zongxi Song, Xin Wei, Zhixin Li, Gang Liu, Tuochi Jiang, and Weikang Zhang
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Computer science ,business.industry ,Speckle noise ,02 engineering and technology ,021001 nanoscience & nanotechnology ,01 natural sciences ,Ptychography ,010309 optics ,Reduction (complexity) ,Noise ,Speckle pattern ,symbols.namesake ,Fourier transform ,Gamma correction ,0103 physical sciences ,symbols ,Computer vision ,Artificial intelligence ,0210 nano-technology ,Phase retrieval ,business - Abstract
Fourier ptychography is a newly reported computational imaging technique, which is used for long-distance, sub-diffraction imaging recently. Compared to conventional Fourier ptychographic microscopy, there is pronounced laser speckle noise in captured images. In this work, a new framework is proposed to suppress speckle noise and reconstruct the high-resolution image for diffuse object. We introduce a random phase to simulate the effects of rough surface during imaging process, and then recover the high-resolution spectrum following two steps: the first is to promote the noisy captured images using Gamma-correction, and the second step is to recover the Fourier spectrum using reshaped Wirtinger flow optimization. Experiments on both simulation and real data demonstrate that the proposed method incorporates speckle noise reduction into reconstruction process, which can achieve better results on both visual and quantitative metrics compared to previous work. more...
- Published
- 2019
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32. A Simple and Enhanced Low-Light Image Enhancement Process Using Effective Illumination Mapping Approach
- Author
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Vallabhuni Vijay, C. Surekha, M. Sai Greeshma, B. Revanth Reddy, V. Siva Nagaraju, and U. Suresh Kumar
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Brightness ,Pixel ,Noise (signal processing) ,Computer science ,business.industry ,media_common.quotation_subject ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Filter (signal processing) ,Transformation (function) ,Gamma correction ,Computer Science::Computer Vision and Pattern Recognition ,Contrast (vision) ,Computer vision ,Artificial intelligence ,Visibility ,business ,media_common - Abstract
When an image is captured in low-light, it gets the low visibility. To overcome the low visibility of the image, some operations are to be performed. But in this paper, image enhancement is introduced using illumination mapping. First, R, G, B maximum values in each pixel of the considered image are to be calculated and then convert it into a grey scale image by applying the formulae. Some filters are used to remove the noise, the choice of filter depends on the type of noise, and then the image is preprocessed. The logarithmic transformation helps to increase the brightness and contrast of the image with a certain amount. Earlier there were some methods to enhance the low-light image, but illumination map existence is chosen. In this illumination, the image will be enhanced with the good quality and efficiency. The illumination technique will be the more efficient and more quality. The illumination corrects the R, G, B values to get the desired image, then Gamma Correction is applied. The Gamma Correction is a non-linear power transform, it helps to increase or decrease the brightness of the desired image when a low value of gamma is taken, the brightness will be increased and when a high value of gamma is taken, and the brightness will be decreased. The proposed system is implemented using MATLAB software. When different types of images are applied, different contrast and brightness levels that depend on the type of image are observed. more...
- Published
- 2019
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33. An adaptive gamma correction for image enhancement
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Rahman, Shanto, Rahman, Md Mostafijur, Abdullah-Al-Wadud, M., Al-Quaderi, Golam Dastegir, and Shoyaib, Mohammad
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- 2016
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34. BrainMRI Enhancement as a Pre-processing: An Evaluation Framework Using Optimal Gamma, Homographic and DWT Based Methods
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G. F. Ali Ahammed and S. Harish
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Discrete wavelet transform ,Pixel ,business.industry ,Computer science ,media_common.quotation_subject ,Pattern recognition ,02 engineering and technology ,Filter (signal processing) ,030218 nuclear medicine & medical imaging ,03 medical and health sciences ,0302 clinical medicine ,Wavelet ,Transformation (function) ,Gamma correction ,0202 electrical engineering, electronic engineering, information engineering ,Medical imaging ,Contrast (vision) ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,media_common - Abstract
The domain of medical imaging has been extensively studied for various parts of human bodies. Study on Brain MRI is quite helpful for the diagnosis of brain related diseases. The availability of noises and less clarity of the input Brain MRI brings ambiguity while analysis. This paper proposes optimized gamma correction, homographic filter and discrete wavelet transformation. The performance evaluation of these methods is analysed with parameters global contrast factor (GCF), contrast per pixel (CPP), contrast (C) and sharpness (S) values. more...
- Published
- 2018
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35. Patch-Based Methods for Video Denoising
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Jose Luis Lisani and Antoni Buades
- Subjects
Motion compensation ,business.industry ,Computer science ,Noise reduction ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Optical flow ,Video camera ,White noise ,law.invention ,Gamma correction ,law ,Computer vision ,Video denoising ,Noise (video) ,Artificial intelligence ,business - Abstract
Video denoising is an important and open problem, which is less treated than the single-image case. Most image sequence denoising techniques rely on still image denoising algorithms; however, it is possible to take advantage of the redundant information contained in the sequence to improve the denoising results. Most recent algorithms are patch based. These methods have two clearly differentiated steps: select similar patches to a reference one and estimate a noise-free version from this group. We review selection and estimation strategies. In particular, we show that the performance is improved by introducing motion compensation. We use as example a recent video denoising technique inspired by fusion algorithms that use motion compensation by regularized optical flow methods, which permits robust patch comparison in a spatiotemporal volume. The use of principal component analysis ensures the correct preservation of fine texture and details, provided that the noise is Gaussian and white, with known variance. Video acquired by any video camera or mobile phone undergoes several processings from the sensor to the final output. This processing, including at least demosaicking, white balance, gamma correction, filtering, and compression, makes a white noise model unrealistic. Indeed, real video captured in dark environments has a very poor quality, with severe spatially and temporally correlated noise. We discuss a denoising framework including realistic noise estimation, multiscale processing, variance stabilization, and white noise removal algorithms. We illustrate the performance of such a chain with real dark and compressed movie sequences. more...
- Published
- 2018
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36. CT–SPECT Analyzer - A Tool for CT and SPECT Data Fusion and Volumetric Visualization
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Maria Laszczyńska, Maria H. Listewnik, Bozena Birkenfeld, Krzysztof Safranow, Maria Chosia, Hanna Piwowarska-Bilska, Jacek Iwanowski, Marek Ostrowski, and Przemysław Mazurek
- Subjects
Spectrum analyzer ,Computer science ,business.industry ,0206 medical engineering ,Value (computer science) ,Pattern recognition ,02 engineering and technology ,Sensor fusion ,020601 biomedical engineering ,Visualization ,Software ,Gamma correction ,Artificial intelligence ,business - Abstract
Data fusion and specific visualization of CT and SPECT are important for diagnosis and research purposes. Selected problems are considered in the paper and are related to the developed CT–SPECT Analyzer software. Hierarchical mapping with SPECT priority for maximum value of rays is applied in this software. Three variants of color mappings are presented. Some practical aspects related to low quality of CT are considered also. The most promising is the rainbow gradient with gamma curve adjustment. more...
- Published
- 2017
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- View/download PDF
37. Concatenated Frame Image Based CNN for Visual Speech Recognition
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Takeshi Saitoh, Ziheng Zhou, Matti Pietikäinen, and Guoying Zhao
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0209 industrial biotechnology ,Sequence ,Computer science ,Speech recognition ,Frame (networking) ,02 engineering and technology ,Data type ,Convolutional neural network ,Image (mathematics) ,Task (computing) ,020901 industrial engineering & automation ,Gamma correction ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Image based - Abstract
This paper proposed a novel sequence image representation method called concatenated frame image (CFI), two types of data augmentation methods for CFI, and a framework of CFI-based convolutional neural network (CNN) for visual speech recognition (VSR) task. CFI is a simple, however, it contains spatial-temporal information of a whole image sequence. The proposed method was evaluated with a public database OuluVS2. This is a multi-view audio-visual dataset recorded from 52 subjects. The speaker independent recognition tasks were carried out with various experimental conditions. As the result, the proposed method obtained high recognition accuracy. more...
- Published
- 2017
- Full Text
- View/download PDF
38. An Image Enhancement Algorithm Based on Fractional-Order Relaxation Oscillator
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Hongbin Tang, Ying Qi, Shangbo Zhou, and Xiaoran Lin
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Physics ,Quantitative Biology::Neurons and Cognition ,Oscillation ,Mathematical analysis ,Relaxation oscillator ,Order (ring theory) ,02 engineering and technology ,Image enhancement ,03 medical and health sciences ,0302 clinical medicine ,Low contrast ,Gamma correction ,0202 electrical engineering, electronic engineering, information engineering ,Curve fitting ,020201 artificial intelligence & image processing ,030217 neurology & neurosurgery - Abstract
In this paper, a cortex rhythms mimicking in fractional-order Relaxation oscillator is implemented and the existence of the rhythm is proved. Furthermore, the Quasi Gamma Curve (QGC) model is established based on the fraction-order Relaxation oscillator in the rhythm oscillation and we certify that the property of QGC model is similar to that of Gamma Curve by curve fitting methods. The proposed model is utilized to enhance the low contrast images. Different quantity measures demonstrate that the proposed model is effective. more...
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- 2017
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39. Novel Image Correction Method Based on Swarm Intelligence Approach
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Marcin Woźniak
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Brightness ,Computer science ,business.industry ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Contrast (statistics) ,020206 networking & telecommunications ,Image processing ,02 engineering and technology ,Image correction ,Swarm intelligence ,Image (mathematics) ,Set (abstract data type) ,Gamma correction ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Computer vision ,Artificial intelligence ,business - Abstract
In the article an approach toward novel method for image features correction is proposed. For the input image developed swarm intelligence technique is applied to improve brightness, contrast, sharpen presentation and improve gamma correction. The following sections present proposed model of the correction techniques with applied swarm intelligence approach. Experimental results on a set of test images are presented with a discussion of achieved improvements. more...
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- 2016
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40. Enhancement of Dental Digital X-Ray Images based On the Image Quality
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B. Rajeshwari and Hema P Menon
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Flexibility (engineering) ,Image quality ,Computer science ,business.industry ,media_common.quotation_subject ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Process (computing) ,020206 networking & telecommunications ,02 engineering and technology ,Automation ,Field (computer science) ,Gamma correction ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Quality (business) ,Computer vision ,Artificial intelligence ,business ,Histogram equalization ,media_common - Abstract
Medical Image Enhancement has made revolution in medical field, in improving the image quality helping doctors in their analysis. Among the various modalities available, the Digital X-rays have been extensively utilized in the medical world of imaging, especially in Dentistry, as it is reliable and affordable. The output scan pictures are examined by practitioners for scrutiny and clarification of tiny setbacks. A technology which is automated with the help of computers to examine the X-Ray images would be of great help to practitioners in their diagnosis. Enhancing the visual quality of the image becomes the prerequisite for such an automation process. The image quality being a subjective measure, the choice of the methods used for enhancement depends on the image under concern and the related application. This work aims at developing a system that automates the process of image enhancement using methods like Histogram Equalization(HE), Gamma Correction(GC),and Log Transform(LT). The decision of the enhancement parameters and the method used is chosen, with the help of the image statistics (like mean, variance, and standard deviation). This proposed system also ranks the algorithms in the order of their visual quality and thus the best possible enhanced output image can be used for further processing. Such an approach would give the practitioners flexibility in choosing the enhanced output of their choice. more...
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- 2016
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41. User Aided Approach for Shadow and Ghost Removal in Robust Video Analytics
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S. Vasavi, I. Lakshmi Narayana, and V. Srinivasa Rao
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business.industry ,Computer science ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Boundary (topology) ,Lossy compression ,computer.software_genre ,Object detection ,Spline (mathematics) ,Information extraction ,Gamma correction ,Shadow ,Probability distribution ,Computer vision ,Artificial intelligence ,business ,computer ,ComputingMethodologies_COMPUTERGRAPHICS - Abstract
In almost all computer vision applications moving objects detection is the crucial step for information extraction. Shadows and ghosts will often introduce errors that will certainly effect the performance of computer vision algorithms, such as object detection, tracking and scene understanding. This paper studies various methods for shadows and ghost detection and proposes a novel user-aided approach for texture preserving shadows and ghost removal from surveillance video. The proposed algorithm addresses limitations in uneven shadow and ghost boundary processing and umbra recovery. This approach first identifies an initial shadow/ghost boundary by growing a user specified shadow outline on an illumination-sensitive image. Interval-variable pixel intensity sampling is introduced to eliminate anomalies, raised from unequal boundaries. This approach extracts the initial scale field by applying local group intensity spline fittings around the shadow boundary area. Bad intensity samples are substituted by their nearest intensities based on a log-normal probability distribution of fitting errors. Finally, it uses a gradual colour transfer to correct post-processing anomalies such as gamma correction and lossy compression. more...
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- 2015
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42. Experimental Evaluation of Rigid Registration Using Phase Correlation Under Illumination Changes
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Alfonso Alba and Edgar R. Arce-Santana
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Robustness (computer science) ,Computer science ,business.industry ,Gamma correction ,Image alignment ,Phase correlation ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Image registration ,Computer vision ,Artificial intelligence ,business ,Rigid transformation - Abstract
The phase correlation method is a computationally-efficient technique for image alignment. Presently, the method is capable of performing rigid image registration with sub-pixel accuracy, and is fairly robust to noise and long translations. However, there are also cases when the images to be aligned were taken at different times or come from different sensors, and may present differences in intensity values or illumination. Many algorithms exist to deal with these issues; however, most of them are computationally expensive. In this article, we explore the robustness of the phase correlation method to illumination and/or intensity changes by means of a quantitative evaluation using artificially-generated rigid transformations. Our results suggest that rigid registration using phase correlation may be fairly robust to gamma correction, quantization and multi-spectral acquisition, but more sensitive to differences in illumination and lighting conditions between the input images. more...
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- 2015
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43. Fast-Speed, High-Accuracy and Real-Time 3D Imaging with Fringe Projection Technique
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Minh Le, Hieu Pham Trung Nguyen, Hien Kieu, and Zhaoyang Wang
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Scheme (programming language) ,Data processing ,Fast speed ,Computer science ,business.industry ,Structured-light 3D scanner ,Gamma correction ,Calibration ,Computer vision ,Artificial intelligence ,business ,Ultrashort pulse ,computer ,computer.programming_language - Abstract
In recent years, improving and extending the capabilities of the three-dimensional (3D) imaging to fast-speed and high-accuracy performance has been a very active research topic. Although the latest advances may help provide real-time and high-resolution measurements, to simultaneously achieve high-accuracy performance is still a big challenge. In this paper, we describe a novel 3D shape measurement and 3D imaging system based on using the fringe projection technique. It employs a generalized system setup, an ultrafast multiple-frequency phase-unwrapping algorithm, a flexible system calibration method, a robust gamma correction technique, and a graphical-programming-unit-based (GPU-based) data processing scheme to achieve fast-speed, high-accuracy and fast-speed 3D shape measurement and 3D imaging performance. The real-time system can operate at a speed of 45 3D-frames/second with relative accuracy of 1/2,500 or at a reduced speed of 10 3D-frames/second with enhanced accuracy of 1/10,000. more...
- Published
- 2014
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44. Image Enhancement Using Geometric Mean Filter and Gamma Correction for WCE Images
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Shiaw Hooi Ho, Aamir Saeed Malik, Ida Hilmi, Nicolas Walter, Shipra Suman, Fawnizu Azmadi Hussin, and Khean-Lee Goh
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Color image ,Computer science ,business.industry ,Filter (signal processing) ,Peak signal-to-noise ratio ,Noise ,symbols.namesake ,Signal-to-noise ratio ,Gamma correction ,Gaussian noise ,symbols ,Computer vision ,Artificial intelligence ,Geometric mean ,business ,Arithmetic mean - Abstract
The application of image enhancement technology to Wireless capsule Endoscopy (WCE) could extremely boost its diagnostic yield. WCE based detection inside gastrointestinal tract has been carried out over a great extent for the seek of the presence of any kind of etiology. However, the quality of acquired images during endoscopy degraded due to factors such as environmental darkness and noise. Hence, decrease in quality also resulted into poor sensitivity and specificity of ulcer and diagnosis. In this paper, a method based on color image enhancement through geometric mean filter and gamma correction is proposed. The developed method used geometric mean filtering to reduce Gaussian noise present in WCE images and achieved better quality images in contrast to arithmetic mean filtering, which has blurring effect after filtration. Moreover, Gamma correction has been applied to enhance small details, texture and contrast of the images. The results shown improved images quality in terms of SNR (Signal to Noise Ratio) and PSNR (Peak Signal to Noise Ratio) which is beneficial for automatic detection of diseases and aids clinicians to better visualize images and ease the diagnosis. more...
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- 2014
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- View/download PDF
45. Live Face Detection by Combining the Fourier Statistics and LBP
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Cao Yu, Xu Xiao, Yaxi Hou, Lifang Wu, and Wei Qi
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Biometrics ,business.industry ,Local binary patterns ,Computer science ,Feature vector ,Liveness ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Pattern recognition ,symbols.namesake ,Fourier transform ,Gamma correction ,Computer Science::Computer Vision and Pattern Recognition ,Face (geometry) ,Statistics ,symbols ,Artificial intelligence ,business ,Face detection - Abstract
With the development of E-Commerce, biometric based on-line authentication is more competitive and is paid more attentions. It brings about one of hot issues of liveness detection recently. In this paper, we propose a liveness detection scheme to combine Fourier statistics and local binary pattern (LBP). First, The Gamma correction and DoG filtering are utilized to reduce the illumination variation and to preserve the key information of the image. Then the Fourier statistics and LBP are combined together to form a new feature vector. Finally, a SVM classifier is trained to discriminate the live and forge face image. The experimental results on the NUAA demonstrate that the proposed scheme is efficient and robust. more...
- Published
- 2014
- Full Text
- View/download PDF
46. DICOM Calibration and GSDF
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Oleg Pianykh
- Subjects
DICOM ,Computer science ,Gamma correction ,Calibration (statistics) ,Computer graphics (images) ,Dicom Standard - Abstract
You might have heard about DICOM calibration a million times. But what is it doing, really?
- Published
- 2013
- Full Text
- View/download PDF
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