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This paper deals with the colorization-based image coding algorithm. In this algorithm, a color image is compressed by encoding its luminance image by a standard coding method such as JPEG coding and by storing several color pixels called as representative pixels (RPs). In decoding phase, a color image is restored from a luminance image and some color information of RPs using the image colorization technique. While previous studies have achieved a high coding performance, the compression method of RPs has not been considered because the positions of RPs are inhomogeneous. In order to improve the image coding performance, this paper proposes the RPs compression algorithm using the graph Fourier transform, where the chrominance image is transformed to graph spectrum and compressed. Using this RPs compression algorithm and a colorization technique, a new colorization-base image coding algorithm is proposed. Numerical results show that the proposed algorithm achieves better performance than some previous studies and JPEG2000 coding.

Altres ajuts: acords transformatius de la UAB The advent of new technologies such as high dynamic range or 8K screens has enhanced the quality of digital images but it has also increased the codecs' computational demands to process such data. This paper presents a video codec that, while providing the same coding features and performance as those of JPEG2000, can process 16K video in real time using a consumer-grade GPU. This high throughput is achieved with a technique that introduces complexity scalability to a bitplane coding engine, which is the most computationally complex stage of the coding pipeline. The resulting codec can trade throughput for coding performance depending on the user's needs. Experimental results suggest that our method can double the throughput achieved by CPU implementations of the recently approved High-Throughput JPEG2000 and by hardwired implementations of HEVC in a GPU.

In this paper, we propose an entropy minimization histogram mergence (EMHM) scheme that can significantly reduce the number of grayscales with nonzero pixel populations (GSNPP) without visible loss to image quality. We proved in theory that the entropy of an image is reduced after histogram mergence and that the reduction in entropy is maximized using our EMHM. The reduction in image entropy is good for entropy encoding considering that the minimum average code word length per source symbol is the entropy of the source signal according to Shannon’s first theorem. Extensive experimental results show that our EMHM can significantly reduce the code length of entropy coding, such as Huffman, Shannon, and arithmetic coding, by over 20% while preserving the image subjective and objective quality very well. Moreover, the performance of some classic lossy image compression techniques, such as the Joint Photographic Experts Group (JPEG), JPEG2000, and Better Portable Graphics (BPG), can be improved by preprocessing images using our EMHM.

Since few decades ago, Discrete Cosine Transform (DCT) based digital image signal compression had been adopted as the JPEG international standard. Later, Wavelet Transform (WT) has replaced the DCT and its being applied in medical image compression. JPEG 2000, the international standardization of WT is using separable lifting structure where the multidimensional image signal is transformed separately in its horizontal and vertical direction. Besides that, each process is realized by cascading in lifting calculation. However, the necessity of waiting for previous step before calculating to the next step will make the overall delay time become longer. The delay time between input and output of WT is reduced as the proposed method reduces its lifting steps. Since the lifting step contains a rounding operation, variance of the rounding noise generated due to the rounding operation inside the transform is reduced. In this paper, unlike the conventional separable structure, the proposed non-separable structure reduces the rounding noise inside the transform, which will lead to the increasing of coding performance. The proposed wavelet transform has a merit that its output signal, apart from the rounding noise, is exactly the same as the conventional separable structure which is a cascade of 1D structure. As a result of experiments, it was observed that the proposed method reduces the rounding noise as well as increases the performance of data compression of various 4D input signals.

Cognitive Radio is an efficient way of spectrum utilization since secondary users with bandwidth-demanding applications such as multimedia can get access to licensed frequency resources opportunistically and resolve their bandwidth limitations. Among all multimedia formats, JPEG 2000 is a suitable candidate for cognitive radio networks thanks to its unique features. In conventional resource allocations for Cognitive Radio systems, all data bits are assumed equally important. However, different parts of the JPEG 2000 bit stream have different contributions to the quality of the received image. Therefore, in this paper, an unequal power allocation method is used to allocate the available power to the coded bits based on their importance in the image quality. Simulated annealing method is used to solve the unequal power allocation problem. Furthermore, bits with higher significance are further protected by using sub-channels with better channel quality. Thus, the likelihood of significant bits being received correctly is increased. The optimal solution is obtained by minimizing the image distortion without violating the interference constraint to the primary users. The performance of the proposed method is demonstrated by simulation results.

The goal of forensic investigators is to reveal the processing history of a digital image. Many forensic techniques are devoted to detecting the intrinsic traces left by image processing and tampering. However, existing forensic techniques are easily defeated in presence of pre- and post-processing. In real scenarios, images may be sequentially manipulated by a series of operations (the so called operation chain). This paper addresses the operation chain consisting of JPEG compression and resampling. The transformed block artifacts (TBAG) characterizing this operation chain are analysed at both the pixel and discrete cosine transforms (DCT) domain and are utilized to design the detection scheme. Both theoretical analysis and experimental results show the effectiveness of our proposed scheme on identifying the resampled JPEG images as well as the JPEG images undergone resampling and then JPEG recompression. Moreover, the proposed approach can be used to estimate the resampling factors for restoring the whole operation chain. HighlightsOperation chain consists of JPEG compression and Resampling.Detection relies on TBAG and DCTR.Resampling factor can be estimated.

Time/space varying filter banks (FBs) are useful for non-stationary images. Lifting factorization of FBs results in structural perfect reconstruction even during the transition from one FB to other. This allows spatial switching between arbitrary FBs, avoiding the need to design border FBs. However, we show that lifting based switching between arbitrarily designed FBs induces spurious transients in the subbands during the transition. In this paper, we study the transients in lifting based switching of two-channel FBs. We propose two solutions to overcome the transients. One solution consists of a boundary handling mechanism to switch between any arbitrarily designed FBs, while the other solution proposes to design the FBs with a set of conditions applied on lifting steps. Both solutions maintain good frequency response during the transition and eliminate the transients. Using the proposed methods, we develop a spatial adaptive transform by switching between the long length FBs (either the JPEG2000 9/7 FB or the newly designed 13/11 FB) and the short length FBs (JPEG2000 5/3 FB) for lossy image compression. This adaptive transform shows PSNR improvement for images over JPEG2000 9/7 FB in low bit rate region (up to 0.2bpp) and subjective improvements with reduced ringing up to medium bit rates (up to 0.6bpp). HighlightsShows that transients are induced during switching between arbitrary lifting based filter banks.Proposes a boundary handling mechanism to switch between given filter banks.Proposes filter bank design method that do not induce transients.Develops a spatial adaptive transform (SPADDWT) by switching between long length and short length FBs.SPADDWT improves PSNR for bit rates up to 0.2 bpp and improves visual quality for bit rates up to 0.6 bpp over JPEG2000 9/7 FB.

Partial differential equations (PDEs) are able to reconstruct images accurately from a small fraction of their image points. The inpainting capabilities of sophisticated anisotropic PDEs allow compression codecs with suboptimal data selection approaches to compete with transform-based methods like JPEG2000. For simple linear PDEs, optimal known data can be found with powerful optimisation strategies. However, the potential of these linear methods for compression has so far not yet been determined.As a remedy, we present a compression framework with homogeneous, biharmonic, and edge-enhancing diffusion (EED) that supports different strategies for data selection and storage: on the one hand, we find exact masks with optimal control or stochastic sparsification and store them with a combination of PAQ and block coding. On the other hand, we propose a new probabilistic strategy for the selection of suboptimal known data that can be efficiently stored with binary trees and entropy coding.This new framework allows us a detailed analysis of the strengths and weaknesses of the three PDEs. Our investigation leads to surprising results: at low compression rates, the simple harmonic diffusion can surpass its more sophisticated PDE-based competitors and even JPEG2000. For high compression rates, we find that EED yields the best result due to its robust inpainting performance under suboptimal conditions. HighlightsPDEs for compression can only be properly evaluated in the context of actual codecs.Simple linear PDEs can be competitive with optimised known data.Sophisticated anisotropic PDEs are well-suited for suboptimal known data.

Fast content access and content based retrieval of images are among the common web and signal processing applications; on the other hand, JPEG is the dominant format for image compression in a wide range of applications. In this paper, a simple and fast method for content access and retrieval of JPEG coded images is presented which does not require complete decompression of coded images. The presented method uses DCT coefficients of coded blocks in the JPEG bit stream to extract average values of various size picture blocks namely DC values. The DC values provide an approximation of the coded image, which can be employed to construct a lower resolution picture or color histogram of the JPEG coded image for retrieval and other applications without full decompression of the image. A novel fast algorithm to access the content of JPEG compressed images is presented.Extracting 2×2 and 4×4 sub-block averages from JPEG bitstream without full decompression.The extracted sub-block averages can directly construct color histogram or an approximated picture.The presented method can be efficiently used for fast exploring or retrieval of JPEG coded images.Finding block averages from JPEG bitstream at the same accuracy as earlier works but faster.

Wedgelet approximation of an image block is classically obtained by an exhaustive search in a predefined dictionary where representation error of all basis elements is examined. Although this strategy leads to the selection of the best atom, due to intolerable computational complexity, the practical applications of classical wedgelet transform is severely limited. In this paper, by employing non-linear least squares and discontinuity relaxation, we suggest an iterative estimation procedure to speed up computation of the second-order wedgelet transform. Accuracy and speed of this wedgelet computation approach is studied by an image compression framework which utilizes both wedgelets and platelets to approximate image blocks. The M-term approximation of second-order wedgelets and second-order platelets is studied in this framework and is concluded to be O ( M - 3 ) . Our proposed wedgelet computation surpasses the state of the art Moments-based Second-order Wedgelet Transform in accuracy while achieving roughly the same speed. It also achieved noticeable quality improvement over JPEG2000 in compression of disparity images (5dB at 0.15bpp). Graphical abstractDisplay Omitted HighlightsWe will use non-linear least squares to approximate image by relaxed second-order wedgelets.Rate-distortion analysis for tree-based coding of second-order platelets will be presented.Performance will be evaluated in compression of both natural images and disparity images.Our method is fast and provides better quality comparing to moments-based approach.

Image compression systems that exploit the properties of the human visual system have been studied extensively over the past few decades. For the JPEG2000 image compression standard, all previous methods that aim to optimize perceptual quality have considered the irreversible pipeline of the standard. In this work, we propose an approach for the reversible pipeline of the JPEG2000 standard. We introduce a new methodology to measure visibility of quantization errors when reversible color and wavelet transforms are employed. Incorporation of the visibility thresholds using this methodology into a JPEG2000 encoder enables creation of scalable codestreams that can provide both near-threshold and numerically lossless representations, which is desirable in applications where restoration of original image samples is required. Most importantly, this is the first work that quantifies the bitrate penalty incurred by the reversible transforms in near-threshold image compression compared to the irreversible transforms.

As a novel virtual reality (VR) format, panorama maps are attracting increasing attention, while the compression of panorama images is still a concern. In this paper, a densely connected convolutional network block (dense block) based autoencoder is proposed to compress panorama maps. In the proposed autoencoder, dense blocks are specially designed to reuse feature maps and reduce redundancy of features. Meanwhile, a loss function, which imports a position-dependent weight item for each pixel, is proposed to train and adjust network parameters, in order to make the autoencoder fit to properties of panorama maps. Based on the proposed autoencoder and the weighted loss function, a greedy block-wise training scheme is also designed to avoid gradient vanishing problem and speed up training. During training process, the autoencoder is divided into several sub-nets. After each sub-net is trained separately, the whole network is fine-tuned to achieve the best performance. Experimental results demonstrate that the proposed autoencoder, compared with JPEG, saves up to 79.69 % bit rates, and obtains 7.27dB gain in BD-WS-PSNR or 0.0789 gain in BD-WS-SSIM. The proposed autoencoder also outperforms JPEG 2000, HEVC and VVC in both BD-WS-PSNR and BD-WS-SSIM. Meanwhile, subjective results show that the proposed autoencoder can recover details of panorama images, and reconstruct maps with high visual quality.

In a previous study, we noticed that the lifting step of a color space transform might increase the amount of noise that must be encoded during compression of an image. To alleviate this problem, we proposed the replacement of lifting steps with reversible denoising and lifting steps (RDLS), which are basically lifting steps integrated with denoising filters. We found the approach effective for some of the tested images. In this study, we apply RDLS to discrete wavelet transform (DWT) in JPEG 2000 lossless coding. We evaluate RDLS effects on bitrates using various denoising filters and a large number of diverse images. We employ a heuristic for image-adaptive RDLS filter selection; based on its empirical outcomes, we also propose a fixed filter selection variant. We find that RDLS significantly improves bitrates of non-photographic images and of images with impulse noise added, while bitrates of photographic images are improved by below 1% on average. Considering that the DWT stage may worsen bitrates of some images, we propose a couple of practical compression schemes based on JPEG 2000 and RDLS. For non-photographic images, we obtain an average bitrate improvement of about 12% for fixed filter selection and about 14% for image-adaptive selection. Denoising is integrated with DWT lifting steps in lossless JPEG 2000.A heuristic is used for image-adaptive selection of denoising filters.Significant bitrate improvements are obtained for nonphotographic images.Consistently good performance is observed on images with impulse noise.Compression schemes with various bitrate-complexity tradeoffs are proposed.

The amount of image data generated each day in health care is ever increasing, especially in combination with the improved scanning resolutions and the importance of volumetric image data sets. Handling these images raises the requirement for efficient compression, archival and transmission techniques. Currently, JPEG 2000's core coding system, defined in Part 1, is the default choice for medical images as it is the DICOM-supported compression technique offering the best available performance for this type of data. Yet, JPEG 2000 provides many options that allow for further improving compression performance for which DICOM offers no guidelines. Moreover, over the last years, various studies seem to indicate that performance improvements in wavelet-based image coding are possible when employing directional transforms. In this paper, we thoroughly investigate techniques allowing for improving the performance of JPEG 2000 for volumetric medical image compression. For this purpose, we make use of a newly developed generic codec framework that supports JPEG 2000 with its volumetric extension (JP3D), various directional wavelet transforms as well as a generic intra-band prediction mode. A thorough objective investigation of the performance-complexity trade-offs offered by these techniques on medical data is carried out. Moreover, we provide a comparison of the presented techniques to H.265/MPEG-H HEVC, which is currently the most state-of-the-art video codec available. Additionally, we present results of a first time study on the subjective visual performance when using the aforementioned techniques. This enables us to provide a set of guidelines and settings on how to optimally compress medical volumetric images at an acceptable complexity level. HighlightsWe investigated how to optimally compress volumetric medical images with JP3D.We extend JP3D with directional wavelets and intra-band prediction.Volumetric wavelets and entropy-coding improve the compression performance.Compression gains for medical images with directional wavelets are often minimal.We recommend further adoption of JP3D for volumetric medical image compression.

This paper presents a secure MQ coder (SMQ) for efficient selective encryption of JPEG 2000 images. Being different from existing schemes where encryption overhead is proportional to the size of plain image, SMQ only selectively encrypts tiny and constant volume of data in JPEG 2000 coding regardless of image size. It is extremely fast and suitable for protecting JPEG 2000 images in wireless multimedia sensor networks (WMSNs). Theoretical analysis and experimental results show that SMQ can achieve a balance between security and efficiency, while keeping comparable compression performance and energy consumption with standard JPEG 2000 coding. HighlightsWe propose an efficient encryption algorithm for protecting JPEG 2000 images.Our algorithm is quite fast and energy-saving when handling massive data in WMSNs.We solve the vulnerability to chosen-plaintext attack in a novel and effective way.The proposed algorithm and its superiorities are most related existing schemes.

As a practical and novel application of watermarking, this paper presents a zero-watermarking based objective reduced-reference stereoscopic image quality assessment (RR-SIQA) method. In the proposed method, two kinds of zero-watermarks are constructed according to the characteristics of image structure and stereoscopic perception. Concretely, two view zero-watermarks, which are constructed by judging the relation of the horizontal and vertical components of gradient vectors with respect to the two views, are used to reflect the image structure variation of the stereoscopic image. Meanwhile, a disparity zero-watermark, which is constructed with disparity map of the stereoscopic image, is used to reflect the stereoscopic perception quality variation. Then, the quality of stereoscopic image is objectively assessed by pooling the recovering rates of the detected zero-watermarks. The experimental results show that the stereoscopic image quality evaluation results assessed with the proposed RR-SIQA method are well consistent with subjective assessment, and the proposed method achieves better performance than the widely used full-reference stereoscopic image quality assessment method PSNR in assessing quality of stereoscopic images compressed with JPEG and JPEG2000.

This paper proposes a Joint Source Channel Coding solution optimized for a wireless JPEG 2000 (JPWL ISO/IEC 15444-11) image transmission scheme over a MIMO channel. To ensure robustness of the transmission, channel diversity is exploited with a Closed-Loop MIMO-OFDM scheme. This relies on the Channel State Information (CSI) knowledge on the transmitter side, which allows the MIMO channel to be decomposed into several hierarchical SISO subchannels. In the proposed scheme, the JPWL codestream is divided into hierarchical quality layer passing through the SISO subchannels. With the CSI, a global and optimal method for adjusting all the system parameters of each SISO subchannel is provided. Accordingly, adaptive modulation, Unequal Error Protection (UEP), Unequal Power Allocation (UPA) and source coding rate is provided for each quality layers. The major strength of this work is to provide an optimal method that parameterizes several variables. These have an effect on the rate-distortion trade-off under bitrate, Quality of Service (QoS) and power constraints. Finally, the proposed work allows flexible and reactive coding of a JPWL codestream adapted to the instantaneous channel status. The performance of this technique is evaluated over a realistic time-varying MIMO channel provided by a 3D-ray tracing propagation model. A significant improvement in the quality of the image is demonstrated.

International audience; For the last 15 years, there has been various research and great advances in the field of content-based search and retrieval of images. In this paper, we present an overview of the JPSearch Standard, which is a recently published set of international standards providing interoperable framework for image search and sharing. The JPSearch standard is composed of six parts, which are Part 1: System framework and components, Part 2: Registration, identification and management of schema and ontology, Part 3: Query format, Part 4: File format for metadata embedded in image data (JPEG and JPEG 2000), Part 5: Data interchange format between image repositories, Part 6: Reference software. The Part 1 provides motivation and overview of the JPSearch framework. The Part 2 supports interoperability among various metadata specifications and social tagging using the specification of core metadata and translation rule description language. The Part 3 provides powerful image query language for interoperability among multiple image databases. The Part 4 specifies a file format based on JPEG and JPEG 2000 file format in which arbitrary number of metadata description of a image can be embedded. The Part 5 supports interoperability in interchanging images with metadata between image repositories. Finally, the Part 6 provides reference and utility softwares based on which the JPSearch compliant systems can be easily developed. In this paper, summaries and usage examples for each part of the JPSearch standard are presented.

This paper proposes a joint data-hiding and data modulation scheme to serve the purpose of quality access control of image(s) using quantization index modulation (QIM). The combined effect of external information embedding and data modulation cause visual degradation and may be used in access control through reversible process. The degree of deterioration depends on the amount of external data insertion, amount of data modulation as well as step size used in QIM. A weight function (q) and the quantization step size (@D"b) of JPEG 2000 are used for defining the step size of QIM. Lifting based discrete wavelet transform (DWT), instead of conventional DWT, is used to decompose the original image in order to achieve advantages, namely low loss in image quality due to QIM, better watermark decoding reliability and high embedding capacity for a given embedding distortion. At the decoder, data are demodulated first and watermark bits are then extracted using minimum distance decoding. Extracted watermark is used to suppress self-noise (SN) that provides better quality of image. Simulation results have shown that an improvement in peak-signal-to-noise-ratio (PSNR), mean structural-similarity-index-measure (MSSIM) and Watson distance by an amount of about 30%, 12% and 77%, respectively, are gained by authorized user when 50% coefficients of high-high (HH) coefficients are modulated.

In this paper, we propose a framework for unequal error protection (UEP) of image and video streaming over a wireless channel. Our framework of allocating the parity symbols associated with error control coding to the image or video codestream takes advantage of the different levels of importance that particular spatial regions of visual multimedia content has to human observers. As such, it provides stronger protection against transmission impairments to those parts of an image or video stream that correspond to the regions of interest (ROIs) while weaker protection is applied to the background (BG). For this purpose, an image or video stream represented by a sequence of packets is split into smaller cells in such a way that certain cells contain the parts of a codestream that represent ROIs and the last cell carries solely BG information. The available parity budget obtained from the given code rate is then distributed among these cells based on their contribution to the overall perceptual quality of a reconstructed image or video. A dynamic programming approach is utilized to facilitate optimal allocation of parity to ROIs and BG for ROI based UEP. The performance of the proposed ROI based UEP scheme is analyzed and compared with both the optimal UEP without ROI processing and equal error protection (EEP) in terms of an objective perceptual quality metric, the structural similarity (SSIM) index. Performance results validate the effectiveness of our framework and the superior performance of the proposed UEP scheme compared to EEP. The performance of the proposed UEP scheme matches well with that of the optimal UEP without ROI processing, especially, for multiple spatial description image and video coding while computational complexity can be kept much lower.

No-reference (NR) image quality assessment (QA) presumes no prior knowledge of reference (distortion-free) images and seeks to quantitatively predict visual quality solely from the distorted images. We develop kurtosis-based NR quality measures for JPEG2000 compressed images in this paper. The proposed measures are based on either 1-D or 2-D kurtosis in the discrete cosine transform (DCT) domain of general image blocks. Comprehensive testing demonstrates their good consistency with subjective quality scores as well as satisfactory performance in comparison with both the representative full-reference (FR) and state-of-the-art NR image quality measures.

In this paper, a reversible integer to integer time domain lapped transform (RTDLT) is introduced. TDLT can be taken as a combination of time domain pre- and post-filter modules with discrete cosine transform (DCT). Different from TDLT, the filters and DCT in our proposed RTDLT are realized from integer to integer by multi-lifting implementations after factorizing the filtering and transforming matrixes into triangular elementary reversible matrices (TERMs). Lifting implementations are realized by only shift and addition without any floating-point multiplier to reduce complexity. The proposed method can realize progressive lossy-to-lossless image compression with a single bit-stream. Simulation results show that RTDLT-based compression system obtains comparable or even higher compression-ratio in lossless compression than that of JPEG2000 and JPEG-LS, as well as gratifying rate distortion performance in lossy compression. Besides, RTDLT keeps low-complexity in hardware realization because it can be parallel implemented on the block level.

No-reference measurement of perceptual image quality is a crucial and challenging issue in modern image processing applications. One of the major difficulties is that some inherent features of natural images and artifacts are possibly rather ambiguous. In this paper, we tackle this problem using statistical information on image gradient profiles and propose a novel quality metric for JPEG2000 images. The key part of the metric is a histogram representing the sharpness distribution of the gradient profiles, from which a blur metric that is insensitive to inherently blurred structures in the natural image is established. Then a ringing metric is built based on ringing visibilities of regions associated with the gradient profiles. Finally, a combination model optimized through plenty of experiments is developed to predict the perceived image quality. The proposed metric achieves performance competitive with the state-of-the-art no-reference metrics on public datasets and is robust to various image contents.

JPEG 2000 and HD Photo (JPEG XR) enable the coding of images with several adaptivity provisions. These provisions allow taking into account the constraints of diverse usage environments. However, the actual adaptation of the coded bitstreams requires additional system complexity. This paper investigates how JPEG 2000 and HD Photo can be used in a standardized and XML-based framework for format-independent content adaptation in the compressed domain. An analysis is provided of the cost of providing adaptivity in the compressed domain, in terms of loss of coding efficiency, as well as in terms of the complexity of the format-agnostic adaptation system used. This complexity is expressed in terms of execution times, memory consumption, and file size overhead of the XML descriptions. Using the outcome of our analysis, a number of improvements are proposed that allow reducing the complexity of XML-based adaptation for JPEG 2000 and HD Photo, in particular the use of compact XML descriptions and an adaptation chain based on the Simple API for XML (SAX). Compact XML descriptions contain a minimal amount of information for the purpose of adaptation-their use is enabled by introducing an additional lightweight pre- and post-processing step in the overall adaptation chain. Our results show that editing-style operations on JPEG 2000 and HD Photo bitstreams can be executed with a feasible complexity when relying on compact XML descriptions. These editing-style operations include exploiting spatial and quality scalability, as well as interactive extraction of regions-of-interest (ROIs). However, low-level operations in the compressed domain, such as rotating an image, cannot be supported, due to the need for entropy decoding and data reordering at macroblock or codeblock level.

This paper presents a unified approach for low-memory and on-the-fly implementation of generic hierarchical transforms (GHTs) suited for parent-children tree (PCT) production, called the stripe-based hierarchical transform (SBHT). Here, the term ''generic'' means that totally different FBs may appear in different decomposition levels. This approach generates the exactly same subband coefficients as the traditional global implementation of GHTs with a low memory budget that is unrelated to the input signal length and only dependent on the GHT. The SBHT lends itself to the PCT-based image coding algorithm in the sense that the basic data unit generated by the SBHT is row-based collections of PCT structures, the most widely used data entity in subband coding. To demonstrate the SBHT's application in image coding, a PCT coder based on the LLEC is proposed to encode the PCTs generated by the SBHT. No intermediate buffering is needed between the SBHT and the codec. The experiments show that when the GHT is configured appropriately, the proposed coder provides competitive coding efficiency relative to the SPIHT and JPEG2000 with a very low memory budget and low computation complexity.

High dynamic range (HDR) image requires a higher number of bits per color channel than traditional images. This brings about problems to storage and transmission. Color space quantization has been extensively studied to achieve bit encodings for each pixel and still yields prohibitively large files. This paper explores the possibility of further compressing HDR images quantized in color space. The compression schemes presented in this paper extends existing lossless image compression standards to encode HDR images. They separate HDR images in their bit encoding formats into images in grayscale or RGB domain, which can be directly compressed by existing lossless compression standards such as JPEG, JPEG 2000 and JPEG-LS. The efficacy of the compression schemes is illustrated by presenting extensive results of encoding a series of synthetic and natural HDR images. Significant bit savings of up to 53% are observed when comparing with original HDR formats and HD Photo compressed version. This is beneficial to the storage and transmission of HDR images.

Intra-video coding is a common way to process video material for applications like professional video editing systems, digital cinema, video surveillance applications, multi-spectral satellite imaging, HQ video delivery, etc. Most practical intra-coding systems employ JPEG encoders due to their simplicity, low coding delay and low memory requirements. JPEG2000 is the main candidate to replace JPEG in this kind of application due to its excellent rate/distortion (R/D) performance and high coding flexibility. However, its complexity and computational resource requirements for proper operation could be a limitation for certain applications. In this work, we propose an intra-video codec, M-LTW, which is able to obtain very good R/D performance results, as good as JPEG2000 or H.264 INTRA, with faster processing and lower memory usage.

Perceptual image quality evaluation has become an important issue, due to increasing transmission of multimedia contents over the Internet and 3G mobile networks. Most of the no reference perceptual image quality evaluations traditionally attempted to quantify the predefined artifacts of the coded images. Under the assumption that human visual perception is very sensitive to edge information of an image and any kinds of artifacts create pixel distortion, we propose a new approach for designing a no reference image quality evaluation model for JPEG2000 images in this paper, which uses pixel distortions and edge information. Subjective experiment results on the images are used to train and test the model, which has achieved good quality prediction performance.

Most coding techniques for color image compression employ a de-correlation approach-the RGB primaries are transformed into a de-correlated color space, such as YUV or YCbCr, then the de-correlated color components are encoded separately. Examples of this approach are the JPEG and JPEG2000 image compression standards. A different method, of a correlation-based approach (CBA), is presented in this paper. Instead of de-correlating the color primaries, we employ the existing inter-color correlation to approximate two of the components as a parametric function of the third one, called the base component. We then propose to encode the parameters of the approximation function and part of the approximation errors. We use the DCT (discrete cosine transform) block transform to enhance the algorithm's performance. Thus the approximation of two of the color components based on the third color is performed for each DCT subband separately. We use the rate-distortion theory of subband transform coders to optimize the algorithm's bits allocation for each subband and to find the optimal color components transform to be applied prior to coding. This pre-processing stage is similar to the use of the RGB to YUV transform in JPEG and may further enhance the algorithm's performance. We introduce and compare two versions of the new algorithm and show that by using a Laplacian probability model for the DCT coefficients as well as down-sampling the subordinate colors, the compression results are further improved. Simulation results are provided showing that the new CBA algorithms are superior to presently available algorithms based on the common de-correlation approach, such as JPEG.

This paper presents an unequal error protection scheme for still and motion image transmissions. The underlying channel codes are created using a Plotkin construction and offer the novel ability of using one long channel codeword to protect an entire image, yet still allowing progressive decoding. Progressive quality improvements occur in two ways: the first is the usual progressive refinement, where image quality is improved as more data are received; the second is that residual error rates of earlier received data are reduced as more data are received.

We consider an interactive browsing environment for 3D scenes, which allows for the dynamic optimization of selected client views by distributing available transmission resources between geometry and texture components. Texture information is available at a server in the form of scalably compressed images, corresponding to a multitude of original image views. Surface geometry is also available at the server in the form of scalably compressed depth maps, again corresponding to a multitude of original views. Texture and depth components are both open to augmentation as more content becomes available. At any point in the interactive browsing experience, the server must decide how to allocate transmission resources between the delivery of new elements from the various original view bit-streams and new elements from the original geometry bit-streams. The proposed framework implicitly supports dynamic view sub-sampling, based on rate-distortion criteria, since the best server policy is not always to send the nearest original view image to the one which the client is rendering. In this paper, we particularly elaborate upon a novel strategy for distortion-sensitive synthesis of both geometry and rendered imagery at the client, based upon whatever data is provided by the server. We also outline how the JPIP standard for interactive communication of JPEG2000 images, can be leveraged for the 3D scene browsing application.

Current image coding systems such as JPEG are far away from the capability of the human perceptual system in that the encoding may not maximise the reconstruction quality of image contents. Humans are often concerned with the interpretability of the image and thus enhanced reconstruction quality in image contents would facilitate improved recognition performance. This paper addresses this issue by incorporating characteristics of the human perceptual system into an image coding system. This is achieved by analysing the spatial and temporal characteristics of the human visual attention system as recorded from an eye-tracking device at the encoding end. Human visual attention mechanisms direct the viewer's eye movements around the image to provide a sequence of fixations, which are analysed, clustered and classified into regions of interest (ROI). These ROIs are used to selectively encode and prioritise regions such that an improved image content recognition performance can be achieved.

This paper addresses the use of independent component analysis (ICA) for image compression. Our goal is to study the adequacy (for lossy transform compression) of bases learned from data using ICA. Since these bases are, in general, non-orthogonal, two methods are considered to obtain image representations: matching pursuit type algorithms and orthogonalization of the ICA bases followed by standard orthogonal projection. Several coder architectures are evaluated and compared, using both the usual SNR and a perceptual quality measure called picture quality scale . We consider four classes of images (natural, faces, fingerprints, and synthetic) to study the generalization and adaptation abilities of the data-dependent ICA bases. In this study, we have observed that: bases learned from natural images generalize well to other classes of images; bases learned from the other specific classes show good specialization. For example, for fingerprint images, our coders perform close to the special-purpose WSQ coder developed by the FBI. For some classes, the visual quality of the images obtained with our coders is similar to that obtained with JPEG2000, which is currently the state-of-the-art coder and much more sophisticated than a simple transform coder. We conclude that ICA provides a excellent tool for learning a coder for a specific image class, which can even be done using a single image from that class. This is an alternative to hand tailoring a coder for a given class (as was done, for example, in the WSQ for fingerprint images). Another conclusion is that a coder learned from natural images acts like an universal coder, that is, generalizes very well for a wide range of image classes.

This paper proposes an interworking between MPEG-2 Intraframe coding and JPEG2000 international standards. The latter codec is integrated into the base layer of spatial scalability encoders whilst retaining full compatibility with MPEG-2 decoders. The proposed solution combines existing ISO/IEC MPEG standards and is elaborated upon with respect to three application areas; bitstream format portability and adaptability, bitstream switching and combined video scalability. The paper elaborates upon the proposed coding architectures and compatibility with published MPEG standards. The proposed coding architecture is compared against counterpart video transcoders, scalable and single layer codecs. It is shown that the proposed spatial encoder is superior to all the aforementioned codecs whilst enjoying an extensible architecture capable of serving restricted end systems and hosting additional scalable layers such as SNR and temporal scalabilities.

In the image-based relighting (IBL), tremendous reference images are needed to provide a high quality rendering. Therefore, a data compression is a must for its real applications. In this paper, two global analysis methods, the principal component analysis (PCA) and the independent component analysis (ICA), are used to compress the huge IBL data by exploiting its correlation properties. Both approaches approximate the raw data with a small number of global base images, and they follow a similar algorithm structure: base images extraction, raw data representation, and further compression on the base images and the representing coefficients. What differs is that PCA only removes the second-order data correlation, but ICA reduces nearly all order statistics data dependence, which should benefit the data compression. Simulations are given to evaluate their performance. Comparisons are also made between them and JPEG2000 and MPEG. The evaluation results show that both approaches are superior to JPEG2000 and MPEG. Although ICA tends to remove higher order dependence than PCA, it is a little inferior to PCA in terms of compression ratio/reconstruction error performance.

Importance prioritised coding is an image coding principle aimed at improving the interpretability versus bit-rate performance of image coding systems. It is important in surveillance where image formats are large and transmission over bandlimited channels can take considerable time even for compressed bit-streams. It is also useful in content-based retrieval and browsing applications, where the number of images viewed tend to be large and faster interpretability would imply faster rejection of unwanted partially decompressed images. An importance prioritised image coder incorporated within the JPEG 2000 framework, called IMP-J2K, is presented, to prioritise image contents according to a metric based on its ‘importance’. The performance of IMP-J2K is also quantitatively assessed using the objective peak signal-to-noise ratio quality and subjective national imagery interpretability rating scale.

We present a full- and no-reference blur metric as well as a full-reference ringing metric. These metrics are based on an analysis of the edges and adjacent regions in an image and have very low computational complexity. As blur and ringing are typical artifacts of wavelet compression, the metrics are then applied to JPEG2000 coded images. Their perceptual significance is corroborated through a number of subjective experiments. The results show that the proposed metrics perform well over a wide range of image content and distortion levels. Potential applications include source coding optimization and network resource management.

In this paper, we examine the behavior of the JPEG2000 coding scheme over noisy or congested communication channels and highlight a cost policy aspect. Two error schemes are considered, involving bit errors (noisy channel) and packet-dropping (congested channel) effects. Two bit error methods are used, consisting of flipping or eliminating the bits, and various packet sizes are put to the test of packet dropping. Extensive performance results are presented accompanied by an overall cost analysis. r 2003 Elsevier Science B.V. All rights reserved.

In 1996, the JPEG committee began to investigate possibilities for a new still image compression standard to serve current and future applications. This initiative, which was named JPEG 2000, has resulted in a comprehensive standard (ISO 15444∣ITU-T Recommendation T.800) that is being issued in six parts. Part 1, in the same vein as the JPEG baseline system, is aimed at minimal complexity and maximal interchange and was issued as an International Standard at the end of 2000. Parts 2–6 define extensions to both the compression technology and the file format and are currently in various stages of development. In this paper, a technical description of Part 1 of the JPEG 2000 standard is provided, and the rationale behind the selected technologies is explained. Although the JPEG 2000 standard only specifies the decoder and the codesteam syntax, the discussion will span both encoder and decoder issues to provide a better understanding of the standard in various applications.

This paper describes the functionality in the JPEG 2000 Part 1 standard, for encoding images with predefined regions of interest (ROI) of arbitrary shape. The method described is called the Maxshift method. This method is based on scaling of the wavelet coefficients after the wavelet transformation and quantization. By sufficiently scaling the wavelet coefficients used to reconstruct the ROI, all the information pertaining to the ROI is placed before the information pertaining to the rest of the image (background), in the codestream. By varying the quantization of the image and by truncation of the codestream, different quality for the ROI and for the background can be obtained. A description is also given of how the wavelet coefficients that are used to reconstruct the ROI (ROI mask) can be found. Since the decoder uses only the number of significant bitplanes for each wavelet coefficient to determine whether it should be scaled back, an arbitrary set of wavelet coefficients can be scaled on the encoder side. This means that there is no need to encode or send the shape of the ROI. This paper also describes how this can be used to further enhance the ROI functionality. The results in this paper show that the Maxshift method can be used to greatly increase the compression efficiency by lowering the quality of the background and that it also makes it possible to receive the ROI before the background, when transmitting the image.

The human visual system plays a key role in the final perceived quality of the compressed images. It is therefore desirable to allow system designers and users to take advantage of the current knowledge of visual perception and models in a compression system. In this paper, we review the various tools in JPEG 2000 that allow its users to exploit many properties of the human visual system such as spatial frequency sensitivity, color sensitivity, and the visual masking effects. We show that the visual tool sets in JPEG 2000 are much richer than what is achievable in JPEG, where only spatially invariant frequency weighting can be exploited. As a result, the visually optimized JPEG 2000 images can usually have much better visual quality than the visually optimized JPEG images at the same bit rates. Some visual comparisons between different visual optimization tools, as well as some visual comparisons between JPEG 2000 and JPEG, will be shown.

While there exist many different image file formats, the JPEG committee concluded that none of those formats addressed a majority of the needs of tomorrow's complicated imaging applications. Many formats do not provide sufficient flexibility for the intelligent storage and maintenance of metadata. Others are very restrictive in terms of colorspace specification. Others provide flexibility, but with a very high cost because of complexity. The JPEG 2000 file format addresses these concerns by combining a simple binary container with flexible metadata architecture and a useful yet simple mechanism for encoding the colorspace of an image. This paper describes the binary format, metadata architecture, and colorspace encoding architecture of the JPEG 2000 file format. It also shows how this format can be used as the basis for more advanced applications, such as the upcoming motion JPEG 2000 standard.

Quantization is instrumental in enabling the rich feature set of JPEG 2000. Several quantization options are provided within JPEG 2000. Part I of the standard includes only uniform scalar dead-zone quantization, while Part II allows both generalized uniform scalar dead-zone quantization and trellis coded quantization (TCQ). In this paper, an overview of these quantization methods is provided. Issues that arise when each of these methods are employed are discussed as well.