192 research outputs found

    LAR Video : Lossless Video Coding with Semantic Scalability

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    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

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    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

    LAR Video: Hierarchical Representation for Low Bit-Rate Color Image Sequence Coding

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    LAR video is a low complexity system for low bit-rate color image sequence encoding. It aims to propose a joint solution for coding and representation of the frame content. In particular, it allows to provide a compressed description of both chromatic components and motion information at a region level without region partition encoding. Initialy proposed in the LAR coder, used principle has proved to be efficient for still color image encoding. Resulting from a hierarchical spatio-temporal segmentation, a Partition Tree (PT) is transmitted to the decoder with a controlled coding cost. Presented results show interesting performances considering both content representation and compression ratios

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

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    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)

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

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    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

    Real-time scalable video coding for surveillance applications on embedded architectures

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    Application of Bandelet Transform in Image and Video Compression

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    The need for large-scale storage and transmission of data is growing exponentially With the widespread use of computers so that efficient ways of storing data have become important. With the advancement of technology, the world has found itself amid a vast amount of information. An efficient method has to be generated to deal with such amount of information. Data compression is a technique which minimizes the size of a file keeping the quality same as previous. So more amount of data can be stored in memory space with the help of data compression. There are various image compression standards such as JPEG, which uses discrete cosine transform technique and JPEG 2000 which uses discrete wavelet transform technique. The discrete cosine transform gives excellent compaction for highly correlated information. The computational complexity is very less as it has better information packing ability. However, it produces blocking artifacts, graininess, and blurring in the output which is overcome by the discrete wavelet transform. The image size is reduced by discarding values less than a prespecified quantity without losing much information. But it also has some limitations when the complexity of the image increases. Wavelets are optimal for point singularity however for line singularities and curve singularities these are not optimal. They do not consider the image geometry which is a vital source of redundancy. Here we analyze a new type of bases known as bandelets which can be constructed from the wavelet basis which takes an important source of regularity that is the geometrical redundancy.The image is decomposed along the direction of geometry. It is better as compared to other methods because the geometry is described by a flow vector rather than edges. it indicates the direction in which the intensity of image shows a smooth variation. It gives better compression measure compared to wavelet bases. A fast subband coding is used for the image decomposition in a bandelet basis. It has been extended for video compression. The bandelet transform based image and video compression method compared with the corresponding wavelet scheme. Different performance measure parameters such as peak signal to noise ratio, compression ratio (PSNR), bits per pixel (bpp) and entropy are evaluated for both Image and video compression

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

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    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

    Enhanced Fractal Image Coding (FIC) with Collage and Reconstruction Residuals

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    In this paper, two new paradigms are proposed with fractal collage and reconstruction residuals to enhance FIC. In the first new paradigm, FIC is optimized using the reconstruction residuals. In the second paradigm, the selected collage residuals are used to correct the iterated function system (IFS) of FIC, and an effective technique for coding the selected collage residuals is applied based on DCT and embedded bit-plane coding. In the first paradigm, the reconstruction quality is improved without increasing the bit rate. Using the second paradigm, we can improve the reconstruction quality with a little bit (about 0.01 bpp) increase in bit rate. Experimental results show that the proposed paradigms achieve better performance than JPEG at lower bit rate and similar performance at higher bit rate

    Self-similarity and wavelet forms for the compression of still image and video data

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    This thesis is concerned with the methods used to reduce the data volume required to represent still images and video sequences. The number of disparate still image and video coding methods increases almost daily. Recently, two new strategies have emerged and have stimulated widespread research. These are the fractal method and the wavelet transform. In this thesis, it will be argued that the two methods share a common principle: that of self-similarity. The two will be related concretely via an image coding algorithm which combines the two, normally disparate, strategies. The wavelet transform is an orientation selective transform. It will be shown that the selectivity of the conventional transform is not sufficient to allow exploitation of self-similarity while keeping computational cost low. To address this, a new wavelet transform is presented which allows for greater orientation selectivity, while maintaining the orthogonality and data volume of the conventional wavelet transform. Many designs for vector quantizers have been published recently and another is added to the gamut by this work. The tree structured vector quantizer presented here is on-line and self structuring, requiring no distinct training phase. Combining these into a still image data compression system produces results which are among the best that have been published to date. An extension of the two dimensional wavelet transform to encompass the time dimension is straightforward and this work attempts to extrapolate some of its properties into three dimensions. The vector quantizer is then applied to three dimensional image data to produce a video coding system which, while not optimal, produces very encouraging results
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