A novel approach to sparse histogram image lossless compression using JPEG2000

In this paper a novel approach to the compression of sparse histogram images is proposed. First, we define a sparsity index which gives hints on the relationship between the mathematical concept of matrix sparsity and the visual information of pixel distribution. We use this index to better understand the scope of our approach and its preferred field of applicability, and to evaluate the performance. We present two algorithms which modify one of the coding steps of the JPEG2000 standard for lossless image compression. A theoretical study of the gain referring to the standard is given. Experimental results on well standardized images of the literature confirm the expectations, especially for high sparse images

High throughput image compression and decompression on GPUs

Diese Arbeit befasst sich mit der Entwicklung eines GPU-freundlichen, intra-only, Wavelet-basierten Videokompressionsverfahrens mit hohem Durchsatz, das für visuell verlustfreie Anwendungen optimiert ist. Ausgehend von der Beobachtung, dass der JPEG 2000 Entropie-Kodierer ein Flaschenhals ist, werden verschiedene algorithmische Änderungen vorgeschlagen und bewertet. Zunächst wird der JPEG 2000 Selective Arithmetic Coding Mode auf der GPU realisiert, wobei sich die Erhöhung des Durchsatzes hierdurch als begrenzt zeigt. Stattdessen werden zwei nicht standard-kompatible Änderungen vorgeschlagen, die (1) jede Bitebebene in nur einem einzelnen Pass verarbeiten (Single-Pass-Modus) und (2) einen echten Rohcodierungsmodus einführen, der sample-weise parallelisierbar ist und keine aufwendige Kontextmodellierung erfordert. Als nächstes wird ein alternativer Entropiekodierer aus der Literatur, der Bitplane Coder with Parallel Coefficient Processing (BPC-PaCo), evaluiert. Er gibt Signaladaptivität zu Gunsten von höherer Parallelität auf und daher wird hier untersucht und gezeigt, dass ein aus verschiedensten Testsequenzen gemitteltes statisches Wahrscheinlichkeitsmodell eine kompetitive Kompressionseffizienz erreicht. Es wird zudem eine Kombination von BPC-PaCo mit dem Single-Pass-Modus vorgeschlagen, der den Speedup gegenüber dem JPEG 2000 Entropiekodierer von 2,15x (BPC-PaCo mit zwei Pässen) auf 2,6x (BPC-PaCo mit Single-Pass-Modus) erhöht auf Kosten eines um 0,3 dB auf 1,0 dB erhöhten Spitzen-Signal-Rausch-Verhältnis (PSNR). Weiter wird ein paralleler Algorithmus zur Post-Compression Ratenkontrolle vorgestellt sowie eine parallele Codestream-Erstellung auf der GPU. Es wird weiterhin ein theoretisches Laufzeitmodell formuliert, das es durch Benchmarking von einer GPU ermöglicht die Laufzeit einer Routine auf einer anderen GPU vorherzusagen. Schließlich wird der erste JPEG XS GPU Decoder vorgestellt und evaluiert. JPEG XS wurde als Low Complexity Codec konzipiert und forderte erstmals explizit GPU-Freundlichkeit bereits im Call for Proposals. Ab Bitraten über 1 bpp ist der Decoder etwa 2x schneller im Vergleich zu JPEG 2000 und 1,5x schneller als der schnellste hier vorgestellte Entropiekodierer (BPC-PaCo mit Single-Pass-Modus). Mit einer GeForce GTX 1080 wird ein Decoder Durchsatz von rund 200 fps für eine UHD-4:4:4-Sequenz erreicht.This work investigates possibilities to create a high throughput, GPU-friendly, intra-only, Wavelet-based video compression algorithm optimized for visually lossless applications. Addressing the key observation that JPEG 2000’s entropy coder is a bottleneck and might be overly complex for a high bit rate scenario, various algorithmic alterations are proposed. First, JPEG 2000’s Selective Arithmetic Coding mode is realized on the GPU, but the gains in terms of an increased throughput are shown to be limited. Instead, two independent alterations not compliant to the standard are proposed, that (1) give up the concept of intra-bit plane truncation points and (2) introduce a true raw-coding mode that is fully parallelizable and does not require any context modeling. Next, an alternative block coder from the literature, the Bitplane Coder with Parallel Coefficient Processing (BPC-PaCo), is evaluated. Since it trades signal adaptiveness for increased parallelism, it is shown here how a stationary probability model averaged from a set of test sequences yields competitive compression efficiency. A combination of BPC-PaCo with the single-pass mode is proposed and shown to increase the speedup with respect to the original JPEG 2000 entropy coder from 2.15x (BPC-PaCo with two passes) to 2.6x (proposed BPC-PaCo with single-pass mode) at the marginal cost of increasing the PSNR penalty by 0.3 dB to at most 1 dB. Furthermore, a parallel algorithm is presented that determines the optimal code block bit stream truncation points (given an available bit rate budget) and builds the entire code stream on the GPU, reducing the amount of data that has to be transferred back into host memory to a minimum. A theoretical runtime model is formulated that allows, based on benchmarking results on one GPU, to predict the runtime of a kernel on another GPU. Lastly, the first ever JPEG XS GPU-decoder realization is presented. JPEG XS was designed to be a low complexity codec and for the first time explicitly demanded GPU-friendliness already in the call for proposals. Starting at bit rates above 1 bpp, the decoder is around 2x faster compared to the original JPEG 2000 and 1.5x faster compared to JPEG 2000 with the fastest evaluated entropy coder (BPC-PaCo with single-pass mode). With a GeForce GTX 1080, a decoding throughput of around 200 fps is achieved for a UHD 4:4:4 sequence

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

Técnicas de compresión de imágenes hiperespectrales sobre hardware reconfigurable

Tesis de la Universidad Complutense de Madrid, Facultad de Informática, leída el 18-12-2020Sensors are nowadays in all aspects of human life. When possible, sensors are used remotely. This is less intrusive, avoids interferces in the measuring process, and more convenient for the scientist. One of the most recurrent concerns in the last decades has been sustainability of the planet, and how the changes it is facing can be monitored. Remote sensing of the earth has seen an explosion in activity, with satellites now being launched on a weekly basis to perform remote analysis of the earth, and planes surveying vast areas for closer analysis...Los sensores aparecen hoy en día en todos los aspectos de nuestra vida. Cuando es posible, de manera remota. Esto es menos intrusivo, evita interferencias en el proceso de medida, y además facilita el trabajo científico. Una de las preocupaciones recurrentes en las últimas décadas ha sido la sotenibilidad del planeta, y cómo menitoirzar los cambios a los que se enfrenta. Los estudios remotos de la tierra han visto un gran crecimiento, con satélites lanzados semanalmente para analizar la superficie, y aviones sobrevolando grades áreas para análisis más precisos...Fac. de InformáticaTRUEunpu

A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks

Schémas de tatouage d'images, schémas de tatouage conjoint à la compression, et schémas de dissimulation de données

In this manuscript we address data-hiding in images and videos. Specifically we address robust watermarking for images, robust watermarking jointly with compression, and finally non robust data-hiding.The first part of the manuscript deals with high-rate robust watermarking. After having briefly recalled the concept of informed watermarking, we study the two major watermarking families : trellis-based watermarking and quantized-based watermarking. We propose, firstly to reduce the computational complexity of the trellis-based watermarking, with a rotation based embedding, and secondly to introduce a trellis-based quantization in a watermarking system based on quantization.The second part of the manuscript addresses the problem of watermarking jointly with a JPEG2000 compression step or an H.264 compression step. The quantization step and the watermarking step are achieved simultaneously, so that these two steps do not fight against each other. Watermarking in JPEG2000 is achieved by using the trellis quantization from the part 2 of the standard. Watermarking in H.264 is performed on the fly, after the quantization stage, choosing the best prediction through the process of rate-distortion optimization. We also propose to integrate a Tardos code to build an application for traitors tracing.The last part of the manuscript describes the different mechanisms of color hiding in a grayscale image. We propose two approaches based on hiding a color palette in its index image. The first approach relies on the optimization of an energetic function to get a decomposition of the color image allowing an easy embedding. The second approach consists in quickly obtaining a color palette of larger size and then in embedding it in a reversible way.Dans ce manuscrit nous abordons l’insertion de données dans les images et les vidéos. Plus particulièrement nous traitons du tatouage robuste dans les images, du tatouage robuste conjointement à la compression et enfin de l’insertion de données (non robuste).La première partie du manuscrit traite du tatouage robuste à haute capacité. Après avoir brièvement rappelé le concept de tatouage informé, nous étudions les deux principales familles de tatouage : le tatouage basé treillis et le tatouage basé quantification. Nous proposons d’une part de réduire la complexité calculatoire du tatouage basé treillis par une approche d’insertion par rotation, ainsi que d’autre part d’introduire une approche par quantification basée treillis au seind’un système de tatouage basé quantification.La deuxième partie du manuscrit aborde la problématique de tatouage conjointement à la phase de compression par JPEG2000 ou par H.264. L’idée consiste à faire en même temps l’étape de quantification et l’étape de tatouage, de sorte que ces deux étapes ne « luttent pas » l’une contre l’autre. Le tatouage au sein de JPEG2000 est effectué en détournant l’utilisation de la quantification basée treillis de la partie 2 du standard. Le tatouage au sein de H.264 est effectué à la volée, après la phase de quantification, en choisissant la meilleure prédiction via le processus d’optimisation débit-distorsion. Nous proposons également d’intégrer un code de Tardos pour construire une application de traçage de traîtres.La dernière partie du manuscrit décrit les différents mécanismes de dissimulation d’une information couleur au sein d’une image en niveaux de gris. Nous proposons deux approches reposant sur la dissimulation d’une palette couleur dans son image d’index. La première approche consiste à modéliser le problème puis à l’optimiser afin d’avoir une bonne décomposition de l’image couleur ainsi qu’une insertion aisée. La seconde approche consiste à obtenir, de manière rapide et sûre, une palette de plus grande dimension puis à l’insérer de manière réversible

Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression

This thesis investigates new motion anchoring strategies that are targeted at wavelet-based highly scalable video compression (WSVC). We depart from two practices that are deeply ingrained in existing video compression systems. Instead of the commonly used block motion, which has poor scalability attributes, we employ piecewise-smooth motion together with a highly scalable motion boundary description. The combination of this more “physical” motion description together with motion discontinuity information allows us to change the conventional strategy of anchoring motion at target frames to anchoring motion at reference frames, which improves motion inference across time. In the proposed reference-based motion anchoring strategies, motion fields are mapped from reference to target frames, where they serve as prediction references; during this mapping process, disoccluded regions are readily discovered. Observing that motion discontinuities displace with foreground objects, we propose motion-discontinuity driven motion mapping operations that handle traditionally challenging regions around moving objects. The reference-based motion anchoring exposes an intricate connection between temporal frame interpolation (TFI) and video compression. When employed in a compression system, all anchoring strategies explored in this thesis perform TFI once all residual information is quantized to zero at a given temporal level. The interpolation performance is evaluated on both natural and synthetic sequences, where we show favourable comparisons with state-of-the-art TFI schemes. We explore three reference-based motion anchoring strategies. In the first one, the motion anchoring is “flipped” with respect to a hierarchical B-frame structure. We develop an analytical model to determine the weights of the different spatio-temporal subbands, and assess the suitability and benefits of this reference-based WSVC for (highly scalable) video compression. Reduced motion coding cost and improved frame prediction, especially around moving objects, result in improved rate-distortion performance compared to a target-based WSVC. As the thesis evolves, the motion anchoring is progressively simplified to one where all motion is anchored at one base frame; this central motion organization facilitates the incorporation of higher-order motion models, which improve the prediction performance in regions following motion with non-constant velocity

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity