State of the art in 2D content representation and compression

Livrable D1.3 du projet ANR PERSEECe rapport a été réalisé dans le cadre du projet ANR PERSEE (n° ANR-09-BLAN-0170). Exactement il correspond au livrable D3.1 du projet

Image coding employing vector quantisation

The work described in this thesis is concerned with the coding of digitised images employing vector quantisation (VQ). A new VQ-based coding system, named Directional Classified Gain-Shape Vector Quantisation (DCGSVQ), has been developed. It combines vector quantisation with transform coding tech-niques and exploits various properties of the human visual system (HVS) like frequency sensitivity, the masking effect, and orientation sensitivity, to produce reconstructed images with good subjective quality at low bit rates (0.48 bit per pixel). A content classifier, operating in the spatial domain, is employed to classify each image block of 8x8 pixels into one of several classes which represent various image patterns (edges in various directions, monotone areas, complex texture, etc.). Then a classified gain-shape vector quantiser is employed in the cosine domain to encode vectors of AC transform coefficients, while using either a scalar quantiser or a gain-shape vector quantiser to encode the DC coefficients. A new vector configuration strategy for defining AC vectors in the cosine domain has been proposed to better adapt the system to the local statistics of the image blocks. Accordingly, the AC coefficients are first weighted by an equivalent modulation transfer function (MTF) that represents the filtering characteristics of the HVS, and then they are grouped into directional vectors according to their direction in the cosine domain. An optional simple method for feature enhancement, based on inherent properties of the proposed strategy, has also been proposed enabling further image processing at the receiver. A new algorithm for designing the various DCGSVQ codebooks has been developed in two steps. First, a general-purpose new algorithm for classified VQ (CVQ) codebook design has been developed as an alternative to empirical methods proposed in the literature. The new algorithm provides a simple and systematic method for codebook design and reduces considerably the total num-ber of mathematical operations during codebook design. We have named this new algorithm Classified Nearest Neighbour Clustering (CNNC). A fast search algorithm has also been developed to reduce further computational efforts during codebook design. Secondly, a new optimisation criterion which is more suitable for shape code-book design has been developed and employed within the CNNC algorithm to design classified shape codebooks for the DCGSVQ. We have named this algo-rithm modified CNNC. The new algorithm designs the various shape codebooks simultaneously giving the designer full freedom to assign more importance to certain classes of vectors or to certain training vectors. The DCGSVQ system has been shown to outperform the full search VQ, the CVQ, and the transform coding CVQ (TC-CVQ) producing nicer coded images with better signal to noise ratio (SNR) figures at various bit rates. To improve further the perceived quality of coded images, a new postpro-cessing algorithm that can be applied at the decoder without increasing the bit rate has been developed. The proposed algorithm is based on various charac-teristics of the signal spectrum and the noise spectrum, and exploits various properties of the HVS. The proposed algorithm is a general-purpose algorithm that can be applied to block-coded images produced by various systems like VQ, transform coding (TC), and Block Truncation Coding (BTC). The algorithm is modular and can be applied in an adaptive way depending on the quality of the block-coded image. The last theme of this work has been the identification of useful fidelity criteria for image quality assessment. Quality predictors in the form of some subjectively weighted error measures were sought such that a smooth functional relationship exists between them and quality ratings made by human viewers. Quality predictors that incorporate simplified models of the HVS have been proposed and tested on a large set of VQ-coded images. Two such predictors have been shown to be better suited for image quality assessment than the commonly used mean square error (MSE) measure

Data compression techniques applied to high resolution high frame rate video technology

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended

Speech coding

Speech is the predominant means of communication between human beings and since the invention of the telephone by Alexander Graham Bell in 1876, speech services have remained to be the core service in almost all telecommunication systems. Original analog methods of telephony had the disadvantage of speech signal getting corrupted by noise, cross-talk and distortion Long haul transmissions which use repeaters to compensate for the loss in signal strength on transmission links also increase the associated noise and distortion. On the other hand digital transmission is relatively immune to noise, cross-talk and distortion primarily because of the capability to faithfully regenerate digital signal at each repeater purely based on a binary decision. Hence end-to-end performance of the digital link essentially becomes independent of the length and operating frequency bands of the link Hence from a transmission point of view digital transmission has been the preferred approach due to its higher immunity to noise. The need to carry digital speech became extremely important from a service provision point of view as well. Modem requirements have introduced the need for robust, flexible and secure services that can carry a multitude of signal types (such as voice, data and video) without a fundamental change in infrastructure. Such a requirement could not have been easily met without the advent of digital transmission systems, thereby requiring speech to be coded digitally. The term Speech Coding is often referred to techniques that represent or code speech signals either directly as a waveform or as a set of parameters by analyzing the speech signal. In either case, the codes are transmitted to the distant end where speech is reconstructed or synthesized using the received set of codes. A more generic term that is applicable to these techniques that is often interchangeably used with speech coding is the term voice coding. This term is more generic in the sense that the coding techniques are equally applicable to any voice signal whether or not it carries any intelligible information, as the term speech implies. Other terms that are commonly used are speech compression and voice compression since the fundamental idea behind speech coding is to reduce (compress) the transmission rate (or equivalently the bandwidth) And/or reduce storage requirements In this document the terms speech and voice shall be used interchangeably