Locally Adaptive Resolution (LAR) codec

The JPEG committee has initiated a study of potential technologies dedicated to future generation image compression systems. The idea is to design a new norm of image compression, named JPEG AIC (Advanced Image Coding), together with advanced evaluation methodologies, closely matching to human vision system characteristics. JPEG AIC thus aimed at defining a complete coding system able to address advanced functionalities such as lossy to lossless compression, scalability (spatial, temporal, depth, quality, complexity, component, granularity...), robustness, embed-ability, content description for image handling at object level... The chosen compression method would have to fit perceptual metrics defined by the JPEG community within the JPEG AIC project. In this context, we propose the Locally Adaptive Resolution (LAR) codec as a contribution to the relative call for technologies, tending to fit all of previous functionalities. This method is a coding solution that simultaneously proposes a relevant representation of the image. This property is exploited through various complementary coding schemes in order to design a highly scalable encoder. The LAR method has been initially introduced for lossy image coding. This efficient image compression solution relies on a content-based system driven by a specific quadtree representation, based on the assumption that an image can be represented as layers of basic information and local texture. Multiresolution versions of this codec have shown their efficiency, from low bit rates up to lossless compressed images. An original hierarchical self-extracting region representation has also been elaborated: a segmentation process is realized at both coder and decoder, leading to a free segmentation map. This later can be further exploited for color region encoding, image handling at region level. Moreover, the inherent structure of the LAR codec can be used for advanced functionalities such as content securization purposes. In particular, dedicated Unequal Error Protection systems have been produced and tested for transmission over the Internet or wireless channels. Hierarchical selective encryption techniques have been adapted to our coding scheme. Data hiding system based on the LAR multiresolution description allows efficient content protection. Thanks to the modularity of our coding scheme, complexity can be adjusted to address various embedded systems. For example, basic version of the LAR coder has been implemented onto FPGA platform while respecting real-time constraints. Pyramidal LAR solution and hierarchical segmentation process have also been prototyped on DSPs heterogeneous architectures. This chapter first introduces JPEG AIC scope and details associated requirements. Then we develop the technical features, of the LAR system, and show the originality of the proposed scheme, both in terms of functionalities and services. In particular, we show that the LAR coder remains efficient for natural images, medical images, and art images

Flexible Macroblock Ordering for Context-Aware Ultrasound Video Transmission over Mobile WiMAX

The most recent network technologies are enabling a variety of new applications, thanks to the provision of increased bandwidth and better management of Quality of Service. Nevertheless, telemedical services involving multimedia data are still lagging behind, due to the concern of the end users, that is, clinicians and also patients, about the low quality provided. Indeed, emerging network technologies should be appropriately exploited by designing the transmission strategy focusing on quality provision for end users. Stemming from this principle, we propose here a context-aware transmission strategy for medical video transmission over WiMAX systems. Context, in terms of regions of interest (ROI) in a specific session, is taken into account for the identification of multiple regions of interest, and compression/transmission strategies are tailored to such context information. We present a methodology based on H.264 medical video compression and Flexible Macroblock Ordering (FMO) for ROI identification. Two different unequal error protection methodologies, providing higher protection to the most diagnostically relevant data, are presented

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

Error resilience and concealment techniques for high-efficiency video coding

This thesis investigates the problem of robust coding and error concealment in High Efficiency Video Coding (HEVC). After a review of the current state of the art, a simulation study about error robustness, revealed that the HEVC has weak protection against network losses with significant impact on video quality degradation. Based on this evidence, the first contribution of this work is a new method to reduce the temporal dependencies between motion vectors, by improving the decoded video quality without compromising the compression efficiency. The second contribution of this thesis is a two-stage approach for reducing the mismatch of temporal predictions in case of video streams received with errors or lost data. At the encoding stage, the reference pictures are dynamically distributed based on a constrained Lagrangian rate-distortion optimization to reduce the number of predictions from a single reference. At the streaming stage, a prioritization algorithm, based on spatial dependencies, selects a reduced set of motion vectors to be transmitted, as side information, to reduce mismatched motion predictions at the decoder. The problem of error concealment-aware video coding is also investigated to enhance the overall error robustness. A new approach based on scalable coding and optimally error concealment selection is proposed, where the optimal error concealment modes are found by simulating transmission losses, followed by a saliency-weighted optimisation. Moreover, recovery residual information is encoded using a rate-controlled enhancement layer. Both are transmitted to the decoder to be used in case of data loss. Finally, an adaptive error resilience scheme is proposed to dynamically predict the video stream that achieves the highest decoded quality for a particular loss case. A neural network selects among the various video streams, encoded with different levels of compression efficiency and error protection, based on information from the video signal, the coded stream and the transmission network. Overall, the new robust video coding methods investigated in this thesis yield consistent quality gains in comparison with other existing methods and also the ones implemented in the HEVC reference software. Furthermore, the trade-off between coding efficiency and error robustness is also better in the proposed methods

ARQ protocol for joint source and channel coding and its applications

Shannon\u27s separation theorem states that for transmission over noisy channels, approaching channel capacity is possible with the separation of source and channel coding. Practically, the situation is different. Infinite size blocks are needed to achieve this theoretical limit. Also, time-varying channels require a different approach. This leads to many approaches for source and channel coding. This dissertation will address a joint source and channel coding that suits Automatic Repeat Request (ARQ) application and applies it to packet switching networks. Following aspects of the proposed joint source and channel coding approach will be presented: The design of the proposed joint source and channel coding scheme. The approach is based on a variable length coding scheme which adapts the arithmetic coding process for joint source and channel coding. The protocol using this joint source and channel coding scheme in communication systems. The error recovery technique of the proposed scheme is presented. The application of the scheme and protocol. The design is applied to wireless TCP network and real-time video transmissions. The coding scheme embeds the redundancy needed for error detection in source coding stage. The self-synchronization property of lossless compression is utilized by decoder to detect channel errors. With this approach, error detection may be delayed. The delay in detection is referred to as error propagation distance. This work analyzes the distribution of error propagation distance. The error recovery technique of this joint source and channel coding for ARQ (JARQ) protocol is analyzed. Throughput is studied using signal flow graph for both independent channel and nonindependent channels. A packet combining technique is presented which utilizes the non-uniform distribution of error propagation distance to increase the throughput. The proposed scheme may be applied to many areas. In particular, two applications are discussed. A TCP/JARQ protocol stack is introduced and the coordination between TCP and JARQ layers is discussed to maximize system performance. By limiting the number of retransmission, the proposed scheme is applied to real-time transmission to meet timing requirement