Wavelet-based distributed source coding of video

Publication in the conference proceedings of EUSIPCO, Antalya, Turkey, 200

Graph-Cut Rate Distortion Algorithm for Contourlet-Based Image Compression

The geometric features of images, such as edges, are difficult to represent. When a redundant transform is used for their extraction, the compression challenge is even more difficult. In this paper we present a new rate-distortion optimization al-gorithm based on graph theory that can encode efficiently the coefficients of a critically sampled, non-orthogonal or even redundant transform, like the contourlet decomposition. The basic idea is to construct a specialized graph such that its min-imum cut minimizes the energy functional. We propose to ap-ply this technique for rate-distortion Lagrangian optimization in subband image coding. The method yields good compres-sion results compared to the state-of-art JPEG2000 codec, as well as a general improvement in visual quality. Index Terms — subband image coding, rate- distortion allocation 1

Report of AhG on Exploration in Wavelet Video Coding

The AHG on Exploration in Wavelet Video Coding [1] was established at the 73rd MPEG meeting in Poznan, Poland, with the following mandates: 1. To identify and describe new applications of wavelet video coding; 2. For such applications, define coding conditions and plan a performance comparison with other codecs; 3. Conduct the exploration experiments; 4. Maintain and validate the exploration reference software; 5. Maintain and edit the wavelet codec reference document. All discussions took place over the reflector, [email protected], i.e., ~ 100 emails have been exchanged. AhG meeting: Saturday October 24th, 14:30-18:30, Nice Acropolis AhG meeting agenda: 1.- review of conducted exploration experiments on wavelet video coding; 2.- review 74th ISO/MPEG meeting input documents of interest to this AhG; 3.- review this AhG mandates and prepare AhG report, includine recommendation

Building nonredundant adaptive wavelets by update lifting

Adaptive wavelet decompositions appear useful in various applications in image and video processing, such as image analysis, compression, feature extraction, denoising and deconvolution, or optic flow estimation. For such tasks it may be important that the multiresolution representations take into account the characteristics of the underlying signal and do leave intact important signal characteristics such as sharp transitions, edges, singularities or other regions of interest. In this paper, we propose a technique for building adaptive wavelets by means of an extension of the lifting scheme. The classical lifting scheme provides a simple yet flexible method for building new, possibly nonlinear, wavelets from existing ones. It comprises a given wavelet transform, followed by a prediction and an update step. The update step in such a scheme computes a modification of the approximation signal, using information in the detail band. It is obvious that such an operation can be inverted, and therefore the perfect reconstruction property is guaranteed. In this paper we propose a lifting scheme including an adaptive update lifting and a fixed prediction lifting step

Analyse de textures à l'aide de modèles anisotropes à longue dépendance

Dans ce travail, nous introduisons des modèles discrets de textures de type "1/f", permettant de caractériser l'anisotropie souvent présente dans les images réelles. Ces modèles peuvent être conçus comme des équivalents 2D des processus 1D discrets ARIMA fractionnaires. Ils constituent aussi une alternative anisotrope aux bruits gaussiens fractionnaires 2D. Deux méthodes sont proposées pour identifier ces nouveaux modèles, en l'absence de bruit. Une application de l'algorithme EM est ensuite proposée pour traiter le cas où les données sont bruitées

Linear and nonlinear temporal prediction employing lifting structures for scalable video coding

Scalable 3D video codecs based on wavelet lifting structures have attracted recently a lot of attention, due to their compression performance comparable with that of state-of-art hybrid codecs. In this work, we propose a set of linear and nonlinear predictors for the temporal prediction step in lifting implementation. The predictor uses pixels on the motion trajectories of the frames in a window around the pixel to be predicted to improve the quality of prediction. Experimental results show that the video quality as well as PSNR values are improved with the proposed prediction method

LMS based adaptive prediction for scalable video coding

3D video codecs have attracted recently a lot of attention, due to their compression performance comparable with that of state-of-art hybrid codecs and due to their scalability features. In this work, we propose a least mean square (LMS) based adaptive prediction for the temporal prediction step in lifting implementation. This approach improves the overall quality of the coded video, by reducing both the blocking and ghosting artefacts. Experimental results show that the video quality as well as PSNR values are greatly improved with the proposed adaptive method, especially for video sequences with large contrast between the moving objects and the background and for sequences with illumination variations. © 2006 IEEE

Adaptive wavelets for image compression using update lifting: quantisation and error analysis

Classical linear wavelet representations of images have the drawback that they are not optimally suited to represent edge information. To overcome this problem, nonlinear multiresolution decompositions have been designed that can take into account the characteristics of the input signal/image. In our previous work [20,22] we have introduced an adaptive lifting framework, that does not require bookkeeping but has the property that it processes edges and homogeneous image regions in a different fashion. The current paper discusses the effects of quantisation in such an adaptive wavelet decomposition, as such an analysis is essential for the application of these adaptive decompositions in image compression. We provide conditions for recovering the original decisions at the synthesis and show how to estimate the reconstructions error in terms of the quantisation error

MASCOT : metadata for advanced scalable video coding tools : final report

The goal of the MASCOT project was to develop new video coding schemes and tools that provide both an increased coding efficiency as well as extended scalability features compared to technology that was available at the beginning of the project. Towards that goal the following tools would be used: - metadata-based coding tools; - new spatiotemporal decompositions; - new prediction schemes. Although the initial goal was to develop one single codec architecture that was able to combine all new coding tools that were foreseen when the project was formulated, it became clear that this would limit the selection of the new tools. Therefore the consortium decided to develop two codec frameworks within the project, a standard hybrid DCT-based codec and a 3D wavelet-based codec, which together are able to accommodate all tools developed during the course of the project