82 research outputs found

    Segmentation-based mesh design for motion estimation

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    Dans la plupart des codec vidĂ©o standard, l'estimation des mouvements entre deux images se fait gĂ©nĂ©ralement par l'algorithme de concordance des blocs ou encore BMA pour « Block Matching Algorithm ». BMA permet de reprĂ©senter l'Ă©volution du contenu des images en dĂ©composant normalement une image par blocs 2D en mouvement translationnel. Cette technique de prĂ©diction conduit habituellement Ă  de sĂ©vĂšres distorsions de 1'artefact de bloc lorsque Ie mouvement est important. De plus, la dĂ©composition systĂ©matique en blocs rĂ©guliers ne dent pas compte nullement du contenu de l'image. Certains paramĂštres associes aux blocs, mais inutiles, doivent ĂȘtre transmis; ce qui rĂ©sulte d'une augmentation de dĂ©bit de transmission. Pour paillier a ces dĂ©fauts de BMA, on considĂšre les deux objectifs importants dans Ie codage vidĂ©o, qui sont de recevoir une bonne qualitĂ© d'une part et de rĂ©duire la transmission a trĂšs bas dĂ©bit d'autre part. Dans Ie but de combiner les deux exigences quasi contradictoires, il est nĂ©cessaire d'utiliser une technique de compensation de mouvement qui donne, comme transformation, de bonnes caractĂ©ristiques subjectives et requiert uniquement, pour la transmission, l'information de mouvement. Ce mĂ©moire propose une technique de compensation de mouvement en concevant des mailles 2D triangulaires a partir d'une segmentation de l'image. La dĂ©composition des mailles est construite a partir des nƓuds repartis irrĂ©guliĂšrement Ie long des contours dans l'image. La dĂ©composition rĂ©sultant est ainsi basĂ©e sur Ie contenu de l'image. De plus, Ă©tant donnĂ© la mĂȘme mĂ©thode de sĂ©lection des nƓuds appliquĂ©e Ă  l'encodage et au dĂ©codage, la seule information requise est leurs vecteurs de mouvement et un trĂšs bas dĂ©bit de transmission peut ainsi ĂȘtre rĂ©alise. Notre approche, comparĂ©e avec BMA, amĂ©liore Ă  la fois la qualitĂ© subjective et objective avec beaucoup moins d'informations de mouvement. Dans la premier chapitre, une introduction au projet sera prĂ©sentĂ©e. Dans Ie deuxiĂšme chapitre, on analysera quelques techniques de compression dans les codec standard et, surtout, la populaire BMA et ses dĂ©fauts. Dans Ie troisiĂšme chapitre, notre algorithme propose et appelĂ© la conception active des mailles a base de segmentation, sera discute en dĂ©tail. Ensuite, les estimation et compensation de mouvement seront dĂ©crites dans Ie chapitre 4. Finalement, au chapitre 5, les rĂ©sultats de simulation et la conclusion seront prĂ©sentĂ©s.Abstract: In most video compression standards today, the generally accepted method for temporal prediction is motion compensation using block matching algorithm (BMA). BMA represents the scene content evolution with 2-D rigid translational moving blocks. This kind of predictive scheme usually leads to distortions such as block artefacts especially when the motion is important. The two most important aims in video coding are to receive a good quality on one hand and a low bit-rate on the other. This thesis proposes a motion compensation scheme using segmentation-based 2-D triangular mesh design method. The mesh is constructed by irregularly spread nodal points selected along image contour. Based on this, the generated mesh is, to a great extent, image content based. Moreover, the nodes are selected with the same method on the encoder and decoder sides, so that the only information that has to be transmitted are their motion vectors, and thus very low bit-rate can be achieved. Compared with BMA, our approach could improve subjective and objective quality with much less motion information."--RĂ©sumĂ© abrĂ©gĂ© par UM

    Pattern Recognition

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    A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition tasks. The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms. The 27 chapters coved in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition

    Motion compensation and very low bit rate video coding

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    Recently, many activities of the International Telecommunication Union (ITU) and the International Standard Organization (ISO) are leading to define new standards for very low bit-rate video coding, such as H.263 and MPEG-4 after successful applications of the international standards H.261 and MPEG-1/2 for video coding above 64kbps. However, at very low bit-rate the classic block matching based DCT video coding scheme suffers seriously from blocking artifacts which degrade the quality of reconstructed video frames considerably. To solve this problem, a new technique in which motion compensation is based on dense motion field is presented in this dissertation. Four efficient new video coding algorithms based on this new technique for very low bit-rate are proposed. (1) After studying model-based video coding algorithms, we propose an optical flow based video coding algorithm with thresh-olding techniques. A statistic model is established for distribution of intensity difference between two successive frames, and four thresholds are used to control the bit-rate and the quality of reconstructed frames. It outperforms the typical model-based techniques in terms of complexity and quality of reconstructed frames. (2) An efficient algorithm using DCT coded optical flow. It is found that dense motion fields can be modeled as the first order auto-regressive model, and efficiently compressed with DCT technique, hence achieving very low bit-rate and higher visual quality than the H.263/TMN5. (3) A region-based discrete wavelet transform video coding algorithm. This algorithm implements dense motion field and regions are segmented according to their content significance. The DWT is applied to residual images region by region, and bits are adaptively allocated to regions. It improves the visual quality and PSNR of significant regions while maintaining low bit-rate. (4) A segmentation-based video coding algorithm for stereo sequence. A correlation-feedback algorithm with Kalman filter is utilized to improve the accuracy of optical flow fields. Three criteria, which are associated with 3-D information, 2-D connectivity and motion vector fields, respectively, are defined for object segmentation. A chain code is utilized to code the shapes of the segmented objects. it can achieve very high compression ratio up to several thousands

    Object-based video representations: shape compression and object segmentation

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    Object-based video representations are considered to be useful for easing the process of multimedia content production and enhancing user interactivity in multimedia productions. Object-based video presents several new technical challenges, however. Firstly, as with conventional video representations, compression of the video data is a requirement. For object-based representations, it is necessary to compress the shape of each video object as it moves in time. This amounts to the compression of moving binary images. This is achieved by the use of a technique called context-based arithmetic encoding. The technique is utilised by applying it to rectangular pixel blocks and as such it is consistent with the standard tools of video compression. The blockbased application also facilitates well the exploitation of temporal redundancy in the sequence of binary shapes. For the first time, context-based arithmetic encoding is used in conjunction with motion compensation to provide inter-frame compression. The method, described in this thesis, has been thoroughly tested throughout the MPEG-4 core experiment process and due to favourable results, it has been adopted as part of the MPEG-4 video standard. The second challenge lies in the acquisition of the video objects. Under normal conditions, a video sequence is captured as a sequence of frames and there is no inherent information about what objects are in the sequence, not to mention information relating to the shape of each object. Some means for segmenting semantic objects from general video sequences is required. For this purpose, several image analysis tools may be of help and in particular, it is believed that video object tracking algorithms will be important. A new tracking algorithm is developed based on piecewise polynomial motion representations and statistical estimation tools, e.g. the expectationmaximisation method and the minimum description length principle

    Connected Attribute Filtering Based on Contour Smoothness

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    Image Segmentation using Human Visual System Properties with Applications in Image Compression

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    In order to represent a digital image, a very large number of bits is required. For example, a 512 X 512 pixel, 256 gray level image requires over two million bits. This large number of bits is a substantial drawback when it is necessary to store or transmit a digital image. Image compression, often referred to as image coding, attempts to reduce the number of bits used to represent an image, while keeping the degradation in the decoded image to a minimum. One approach to image compression is segmentation-based image compression. The image to be compressed is segmented, i.e. the pixels in the image are divided into mutually exclusive spatial regions based on some criteria. Once the image has been segmented, information is extracted describing the shapes and interiors of the image segments. Compression is achieved by efficiently representing the image segments. In this thesis we propose an image segmentation technique which is based on centroid-linkage region growing, and takes advantage of human visual system (HVS) properties. We systematically determine through subjective experiments the parameters for our segmentation algorithm which produce the most visually pleasing segmented images, and demonstrate the effectiveness of our method. We also propose a method for the quantization of segmented images based on HVS contrast sensitivity, arid investigate the effect of quantization on segmented images

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

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    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

    Improved quality block-based low bit rate video coding.

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    The aim of this research is to develop algorithms for enhancing the subjective quality and coding efficiency of standard block-based video coders. In the past few years, numerous video coding standards based on motion-compensated block-transform structure have been established where block-based motion estimation is used for reducing the correlation between consecutive images and block transform is used for coding the resulting motion-compensated residual images. Due to the use of predictive differential coding and variable length coding techniques, the output data rate exhibits extreme fluctuations. A rate control algorithm is devised for achieving a stable output data rate. This rate control algorithm, which is essentially a bit-rate estimation algorithm, is then employed in a bit-allocation algorithm for improving the visual quality of the coded images, based on some prior knowledge of the images. Block-based hybrid coders achieve high compression ratio mainly due to the employment of a motion estimation and compensation stage in the coding process. The conventional bit-allocation strategy for these coders simply assigns the bits required by the motion vectors and the rest to the residual image. However, at very low bit-rates, this bit-allocation strategy is inadequate as the motion vector bits takes up a considerable portion of the total bit-rate. A rate-constrained selection algorithm is presented where an analysis-by-synthesis approach is used for choosing the best motion vectors in term of resulting bit rate and image quality. This selection algorithm is then implemented for mode selection. A simple algorithm based on the above-mentioned bit-rate estimation algorithm is developed for the latter to reduce the computational complexity. For very low bit-rate applications, it is well-known that block-based coders suffer from blocking artifacts. A coding mode is presented for reducing these annoying artifacts by coding a down-sampled version of the residual image with a smaller quantisation step size. Its applications for adaptive source/channel coding and for coding fast changing sequences are examined
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