Interleaved S+P Pyramidal Decomposition with Refined Prediction Model

International audienceScalability and others functionalities such as the Region of Interest encoding become essential properties of an efficient image coding scheme. Within the framework of lossless compression techniques, S+P and CALIC represent the state-of-the-art. The proposed Interleaved S+P algorithm outperforms these method while providing the desired properties. Based on the LAR (Locally Adaptive Resolution) method, an original pyramidal decomposition combined with a DPCM scheme is elaborated. This solution uses the S-transform in such a manner that a refined prediction context is available for each estimation steps. The image coding is done in two main steps, so that the first one supplies a LAR low-resolution image of good visual quality, and the second one allows a lossless reconstruction. The method exploits an implicit context modelling, intrinsic property of our content-based quad-tree like representation

Embedding Multilevel Image Encryption in the LAR Codec

International audienceA still image codec should not only to be good from compression point of view, it might also provide services. The LAR interleaved S+P codec allows lossless to lossy coding, presenting both resolution and distortion scalability. The proposed method brings image encryption at no cost in the LAR framework. It exploits the embedded quadtree decomposition of the LAR to provide multilevel protection to the whole bit-stream. Theoretical aspects are considered and experimental results show the effectiveness of the process

LAR Video : Lossless Video Coding with Semantic Scalability

Baptized “LAR Video”, the method proposed in this paper describes a new lossless video coding algorithm with advanced semantic scalability. Motion estimation and compensation steps are undertaken first to produce the well known displaced frame difference (DFD). The basic idea is to apply a pyramidal decomposition to this residual error, based on an efficient scalable image compression technique named LAR-APP. As a result of progressive data broadcasting, the image-sequence can be scalably rebuilt in the decoder at different spatial resolution levels. The given experimental results show that the proposed solution achieves not only scalability but also good compression performances

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

WG1N5315 - Response to Call for AIC evaluation methodologies and compression technologies for medical images: LAR Codec

This document presents the LAR image codec as a response to Call for AIC evaluation methodologies and compression technologies for medical images.This document describes the IETR response to the specific call for contributions of medical imaging technologies to be considered for AIC. The philosophy behind our coder is not to outperform JPEG2000 in compression; our goal is to propose an open source, royalty free, alternative image coder with integrated services. While keeping the compression performances in the same range as JPEG2000 but with lower complexity, our coder also provides services such as scalability, cryptography, data hiding, lossy to lossless compression, region of interest, free region representation and coding

LAR Image transmission over fading channels: a hierarchical protection solution

International audienceThe aim of this paper is to present an efficient scheme to transmit a compressed digital image over a non frequency selective Rayleigh fading channel. The proposed scheme is based on the Locally Adaptive Resolution (LAR) algorithm, and the Reed-Solomon error correcting code is used to protect the data against the channel errors. In order to optimize the protection rate and ensure better protection we introduce an Unequal Error Protection (UEP) strategy, where we take the hierarchy of the information into account. The digital communication system also includes appropriate interleaving and differential modulation. Simulation results clearly show that our scheme presents an efficient solution for image transmission over wireless channels, and provides a high quality of service, outperforming the JPWL scheme in high bit error rate conditions

Context-Based Scalable Coding and Representation of High Resolution Art Pictures for Remote Data Access

International audienceEROS is the largest database in the world of high resolution art pictures. The TSAR project is designed to open it in a secure, efficient and user-friendly way that involves cryptography and watermarking as well as compression and region-level representation abilities. This paper more particularly addresses the two last points. The LAR codec is first presented as a suitable solution for picture encoding with compression ranging from highly lossy to lossless. Then, we detail the concept of self-extracting region representation, which consists of performing a segmentation process at both the coder and decoder from a highly compressed image, and later locally enhancing the image in a region of interest. The overall scheme provides an efficient, consistent solution for advanced data browsing

A content based method for perceptually driven joint color/depth compression

International audienceMulti-view Video plus Depth (MVD) data refer to a set of conventional color video sequences and an associated set of depth video sequences, all acquired at slightly different viewpoints. This huge amount of data necessitates a reliable compression method. However, there is no standardized compression method for MVD sequences. H.264/MVC compression method, which was standardized for Multi-View-Video representation (MVV), has been the subject of many adaptations to MVD. However, it has been shown that MVC is not well adapted to encode multi-view depth data. We propose a novel option as for compression of MVD data. Its main purpose is to preserve joint color/depth consistency. The originality of the proposed method relies on the use of the decoded color data as a prior for the associated depth compression. This is meant to ensure consistency in both types of data after decoding. Our strategy is motivated by previous studies of artifacts occurring in synthesized views: most annoying distortions are located around strong depth discontinuities and these distortions are due to misalignment of depth and color edges in decoded images. Thus the method is meant to preserve edges and to ensure consistent localization of color edges and depth edges. To ensure compatibility, colored sequences are encoded with H.264. Depth maps compression is based on a 2D still image codec, namely LAR (Locally adapted Resolution). It consists in a quad-tree representation of the images. The quad-tree representation contributes in the preservation of edges in both color and depth data. The adopted strategy is meant to be more perceptually driven than state-of-the-art methods. The proposed approach is compared to H.264 encoding of depth images. Objective metrics scores are similar with H.264 and with the proposed method, and visual quality of synthesized views is improved with the proposed approach

One Pass Quality Control and Low Complexity RDO in A Quadtree Based Scalable Image Coder

International audienceThis paper presents a joint quality control (QC) and rate distortion optimization (RDO) algorithm applied to a still image codec called Locally Adaptive Resolution (LAR). LAR supports scalability in resolution for both lossy and lossless coding and has low complexity. This algorithm is based on the study of the relationship between compression efficiency and relative parameters. The RDO model is proposed firstly to find suitable parameters. Relying on this optimization, relationships between the distortion of reconstructed image and quantization parameter can be described with a new linear model. This model is used for parametric configuration to control compression distortion. Experimental results show that this algorithm provides an effective solution for an efficient one pass codec with automatic parameters selection and accurate QC. This algorithm could be extended to codecs with similar functions, such as High Efficiency Video Coding (HEVC)

Protection de données à coût nul dans un codeur d'images multirésolution

Les performances des codeurs d'images fixes ne sont plus uniquement évaluées à l'aide des courbes débit-distorsion. Les services fournis sont également un critère de choix. Dans cet article, nous proposons d'intégrer dans un codeur d'images multirésolution offrant des performances supérieures à l'état de l'art avec et sans perte, un schéma de protection de contenu. L'utilisation judicieuse du flux binaire générée par le codeur permet d'obtenir ce service à coût nul. Des éléments tant théoriques que pratiques sont avancés pour justifier l'emploi de ce schéma de protection