Perceptual lossless medical image coding

A novel perceptually lossless coder is presented for the compression of medical images. Built on the JPEG 2000 coding framework, the heart of the proposed coder is a visual pruning function, embedded with an advanced human vision model to identify and to remove visually insignificant/irrelevant information. The proposed coder offers the advantages of simplicity and modularity with bit-stream compliance. Current results have shown superior compression ratio gains over that of its information lossless counterparts without any visible distortion. In addition, a case study consisting of 31 medical experts has shown that no perceivable difference of statistical significance exists between the original images and the images compressed by the proposed coder

Human Vision Models of Perceptual Image Distortions

Digital media's prevalence in today's society is placing an increasing strain on the technology to provide, transmit and store these contents. The demand for higher quality content in digital media has led to drastic increase in storage requirements over the past three decades. To meet the challenge of storing and securing digital media, this thesis proposes an insight into how the human vision system (HVS) can be characterized to determine thresholds of visibility of visual distortions. The use of these results can increase the amount of watermarking information applied to an image as well as applications in quantization error detection. In this thesis, we first propose a framework for predicting the regions of natural images that visually disguise distortions created as a result of modification of wavelet domain coefficients. The visual error perception algorithm adaptively predicts the visual perceptibility threshold of spread spectrum watermarking added in the wavelet subband. Spatial statistical feature maps combined with ground truth data from psychophysical experiments enabled the generation of an activity scaling parameter that evaluates the masking thresholds of image regions. We also demonstrate the correlation with an image quality assessment algorithm to the detectability of distortions in an image. Subsequently the algorithm is combined with a compression scheme to yield compressed images of higher visual quality. Secondly, we presents the results of another psychophysical experiment designed to investigate the effect of a scene's context on the detection of distortions presented in natural-image patches. Via a two-alternative forced-choice experiment, we measured thresholds for detecting 6.2 c/deg gabor target in image patches which were placed in various image surrounds (contexts), including various textures, a solid-gray background, and the patch's original context. The contexts were adjusted using histogram specification to control for differences in brightness, contrast, and other first-order statistical properties of the luminance distribution. Our results revealed that the context in which a patch is placed does indeed affect the ability to detect distortions in that patch. The findings suggest that characterization and implementation of a human visual system's ability to detect errors has potential in providing perceivable greater quality in image applications.School of Electrical & Computer Engineerin

Accelerating BPC-PaCo through visually lossless techniques

Fast image codecs are a current need in applications that deal with large amounts of images. Graphics Processing Units (GPUs) are suitable processors to speed up most kinds of algorithms, especially when they allow fine-grain parallelism. Bitplane Coding with Parallel Coefficient processing (BPC-PaCo) is a recently proposed algorithm for the core stage of wavelet-based image codecs tailored for the highly parallel architectures of GPUs. This algorithm provides complexity scalability to allow faster execution at the expense of coding efficiency. Its main drawback is that the speedup and loss in image quality is controlled only roughly, resulting in visible distortion at low and medium rates. This paper addresses this issue by integrating techniques of visually lossless coding into BPC-PaCo. The resulting method minimizes the visual distortion introduced in the compressed file, obtaining higher-quality images to a human observer. Experimental results also indicate 12% speedups with respect to BPC-PaCo

Visually lossless strategies to decode and transmit JPEG2000 imagery

Visually lossless coding allows image codecs to achieve high compression ratios while producing images without visually noticeable distortion. In general, visually lossless coding is approached from the point of view of the encoder, so most methods are not applicable to already compressed codestreams. This paper presents two algorithms focused on the visually lossless decoding and transmission of JPEG2000 codestreams. The proposed strategies can be employed by a decoder, or a JPIP server, to reduce the decoding or transmission rate without penalizing the visual quality of the resulting images

MIJ2K: Enhanced video transmission based on conditional replenishment of JPEG2000 tiles with motion compensation

A video compressed as a sequence of JPEG2000 images can achieve the scalability, flexibility, and accessibility that is lacking in current predictive motion-compensated video coding standards. However, streaming JPEG2000-based sequences would consume considerably more bandwidth. With the aim of solving this problem, this paper describes a new patent pending method, called MIJ2K. MIJ2K reduces the inter-frame redundancy present in common JPEG2000 sequences (also called MJP2). We apply a real-time motion detection system to perform conditional tile replenishment. This will significantly reduce the bit rate necessary to transmit JPEG2000 video sequences, also improving their quality. The MIJ2K technique can be used both to improve JPEG2000-based real-time video streaming services or as a new codec for video storage. MIJ2K relies on a fast motion compensation technique, especially designed for real-time video streaming purposes. In particular, we propose transmitting only the tiles that change in each JPEG2000 frame. This paper describes and evaluates the method proposed for real-time tile change detection, as well as the overall MIJ2K architecture. We compare MIJ2K against other intra-frame codecs, like standard Motion JPEG2000, Motion JPEG, and the latest H.264-Intra, comparing performance in terms of compression ratio and video quality, measured by standard peak signal-to-noise ratio, structural similarity and visual quality metric metrics.This work was supported in part by Projects CICYT TIN2008– 06742-C02–02/TSI, CICYT TEC2008–06732-C02–02/TEC, SINPROB, CAM MADRINET S-0505/TIC/0255 and DPS2008–07029-C02–02.Publicad

A visible wavelet watermarking technique based on exploiting the contrast sensitivity function and noise reduction of human vision system

Dengan meluasnya penggunaan Internet dan pesatnya perkembangan teknologi digital, perlindungan hak cipta atas konten multimedia telah menjadi isu penting. Di antara teknologi yang tersedia, teknik watermarking digital dianggap sebagai solusi perlindungan hak milik atas sumber daya multimedia. Untuk mengevaluasi kinerja teknik watermarking yang terlihat, ketangguhan dan tembus persepsi adalah dua kriteria penting untuk aplikasi watermark. Untuk mendapatkan pertukaran terbaik antara energi penyisipan tanda air dan penembusan perseptual, penelitian ini menghadirkan teknik bernama ICOCOA (konten inovatif dan sadar kontras) dengan mengeksploitasi fungsi sensitivitas kontras (CSF) dan pengurangan kebisingan dari sistem penglihatan manusia. dalam domain wavelet. Ide baru lainnya dari karya ini adalah untuk mengusulkan kurva inovasi CSF masking (I-CSF) yang memberikan persepsi bobot yang lebih baik di mana arsitektur teori permainan dapat dimanfaatkan untuk menentukan masking I-CSF terbaik untuk gambar yang diberi watermark. Hasil percobaan menunjukkan bahwa pendekatan yang diusulkan tidak hanya memberikan kualitas watermark yang tembus cahaya tetapi juga mencapai ketahanan terhadap operasi pemrosesan gambar umum

Codage d'images avec et sans pertes à basse complexité et basé contenu

This doctoral research project aims at designing an improved solution of the still image codec called LAR (Locally Adaptive Resolution) for both compression performance and complexity. Several image compression standards have been well proposed and used in the multimedia applications, but the research does not stop the progress for the higher coding quality and/or lower coding consumption. JPEG was standardized twenty years ago, while it is still a widely used compression format today. With a better coding efficiency, the application of the JPEG 2000 is limited by its larger computation cost than the JPEG one. In 2008, the JPEG Committee announced a Call for Advanced Image Coding (AIC). This call aims to standardize potential technologies going beyond existing JPEG standards. The LAR codec was proposed as one response to this call. The LAR framework tends to associate the compression efficiency and the content-based representation. It supports both lossy and lossless coding under the same structure. However, at the beginning of this study, the LAR codec did not implement the rate-distortion-optimization (RDO). This shortage was detrimental for LAR during the AIC evaluation step. Thus, in this work, it is first to characterize the impact of the main parameters of the codec on the compression efficiency, next to construct the RDO models to configure parameters of LAR for achieving optimal or sub-optimal coding efficiencies. Further, based on the RDO models, a “quality constraint” method is introduced to encode the image at a given target MSE/PSNR. The accuracy of the proposed technique, estimated by the ratio between the error variance and the setpoint, is about 10%. Besides, the subjective quality measurement is taken into consideration and the RDO models are locally applied in the image rather than globally. The perceptual quality is improved with a significant gain measured by the objective quality metric SSIM (structural similarity). Aiming at a low complexity and efficient image codec, a new coding scheme is also proposed in lossless mode under the LAR framework. In this context, all the coding steps are changed for a better final compression ratio. A new classification module is also introduced to decrease the entropy of the prediction errors. Experiments show that this lossless codec achieves the equivalent compression ratio to JPEG 2000, while saving 76% of the time consumption in average in encoding and decoding.Ce projet de recherche doctoral vise à proposer solution améliorée du codec de codage d’images LAR (Locally Adaptive Resolution), à la fois d’un point de vue performances de compression et complexité. Plusieurs standards de compression d’images ont été proposés par le passé et mis à profit dans de nombreuses applications multimédia, mais la recherche continue dans ce domaine afin d’offrir de plus grande qualité de codage et/ou de plus faibles complexité de traitements. JPEG fut standardisé il y a vingt ans, et il continue pourtant à être le format de compression le plus utilisé actuellement. Bien qu’avec de meilleures performances de compression, l’utilisation de JPEG 2000 reste limitée due à sa complexité plus importe comparée à JPEG. En 2008, le comité de standardisation JPEG a lancé un appel à proposition appelé AIC (Advanced Image Coding). L’objectif était de pouvoir standardiser de nouvelles technologies allant au-delà des standards existants. Le codec LAR fut alors proposé comme réponse à cet appel. Le système LAR tend à associer une efficacité de compression et une représentation basée contenu. Il supporte le codage avec et sans pertes avec la même structure. Cependant, au début de cette étude, le codec LAR ne mettait pas en oeuvre de techniques d’optimisation débit/distorsions (RDO), ce qui lui fut préjudiciable lors de la phase d’évaluation d’AIC. Ainsi dans ce travail, il s’agit dans un premier temps de caractériser l’impact des principaux paramètres du codec sur l’efficacité de compression, sur la caractérisation des relations existantes entre efficacité de codage, puis de construire des modèles RDO pour la configuration des paramètres afin d’obtenir une efficacité de codage proche de l’optimal. De plus, basée sur ces modèles RDO, une méthode de « contrôle de qualité » est introduite qui permet de coder une image à une cible MSE/PSNR donnée. La précision de la technique proposée, estimée par le rapport entre la variance de l’erreur et la consigne, est d’environ 10%. En supplément, la mesure de qualité subjective est prise en considération et les modèles RDO sont appliqués localement dans l’image et non plus globalement. La qualité perceptuelle est visiblement améliorée, avec un gain significatif mesuré par la métrique de qualité objective SSIM. Avec un double objectif d’efficacité de codage et de basse complexité, un nouveau schéma de codage LAR est également proposé dans le mode sans perte. Dans ce contexte, toutes les étapes de codage sont modifiées pour un meilleur taux de compression final. Un nouveau module de classification est également introduit pour diminuer l’entropie des erreurs de prédiction. Les expérimentations montrent que ce codec sans perte atteint des taux de compression équivalents à ceux de JPEG 2000, tout en économisant 76% du temps de codage et de décodage

Scalable video compression with optimized visual performance and random accessibility

This thesis is concerned with maximizing the coding efficiency, random accessibility and visual performance of scalable compressed video. The unifying theme behind this work is the use of finely embedded localized coding structures, which govern the extent to which these goals may be jointly achieved. The first part focuses on scalable volumetric image compression. We investigate 3D transform and coding techniques which exploit inter-slice statistical redundancies without compromising slice accessibility. Our study shows that the motion-compensated temporal discrete wavelet transform (MC-TDWT) practically achieves an upper bound to the compression efficiency of slice transforms. From a video coding perspective, we find that most of the coding gain is attributed to offsetting the learning penalty in adaptive arithmetic coding through 3D code-block extension, rather than inter-frame context modelling. The second aspect of this thesis examines random accessibility. Accessibility refers to the ease with which a region of interest is accessed (subband samples needed for reconstruction are retrieved) from a compressed video bitstream, subject to spatiotemporal code-block constraints. We investigate the fundamental implications of motion compensation for random access efficiency and the compression performance of scalable interactive video. We demonstrate that inclusion of motion compensation operators within the lifting steps of a temporal subband transform incurs a random access penalty which depends on the characteristics of the motion field. The final aspect of this thesis aims to minimize the perceptual impact of visible distortion in scalable reconstructed video. We present a visual optimization strategy based on distortion scaling which raises the distortion-length slope of perceptually significant samples. This alters the codestream embedding order during post-compression rate-distortion optimization, thus allowing visually sensitive sites to be encoded with higher fidelity at a given bit-rate. For visual sensitivity analysis, we propose a contrast perception model that incorporates an adaptive masking slope. This versatile feature provides a context which models perceptual significance. It enables scene structures that otherwise suffer significant degradation to be preserved at lower bit-rates. The novelty in our approach derives from a set of "perceptual mappings" which account for quantization noise shaping effects induced by motion-compensated temporal synthesis. The proposed technique reduces wavelet compression artefacts and improves the perceptual quality of video