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Recently, a new probability model dubbed the Laplacian transparent composite model (LPTCM) was developed for DCT coefficients, which could identify outlier coefficients in addition to providing superior modeling accuracy. In this paper, we aim at exploring its applications to image compression. To this end, we propose an efficient nonpredictive image compression system, where quantization (including...
In this paper, we present an efficient hardware implementation of a Context Adaptive Variable Length Coding (CAVLC) module for an H.264/AVC video encoder. To improve timing performance, a three-stage pipeline architecture is proposed including: input data statistical analysis, encoding and packing. The context information and coding tables are stored in memory elements. To minimize the hardware implementation...
In this paper, we improve on our previous work regarding component-based image coding, a hybrid transform-based/perceptual image coding scheme based on a decomposition of the image into structure and texture characterized by a Gaussian Markov random field. The 2D Itakura distance allows us to evaluate the performance of our texture model in terms of rate vs. distortion. A minimal quantization step...
This paper presents a high-throughput hardware architecture for H.264/AVC CAVLC encoding. Our scheme eliminates the pipeline stage of computing the coefficient statistics (as adopted by state-of-the-art hardware architectures) with a pre-processing stage during the quantization in order to avoid the extra looping logic in CAVLC. This provides significant performance improvement compared to state-of-the-art...
This article introduces one adaptive binary arithmetic coding system based on context. H.264/AVC is a new video coding standard developed by ITU-T VCEG and ISO/IEC MPEG. It includes many new technology features, such as Multi-mode prediction, Flexible Macro block Ordering (FMO), integer transform, Universal Variable Length Codes (UVLC), Context-based Adaptive Binary Arithmetic Coding (CABAC), laying...
This paper presents a lossless image compression method for one frame of High-definition television (HDTV). We apply classified adaptive prediction, and then the prediction error is encoded by entropy coding of arithmetic coding. Then an image is divided into small blocks, and they are classified into some classes each of which correspond to one minimum mean square error (MMSE) linear predictor. In...
In this paper a novel method to estimate the required bits for representing the coded (quantized) coefficients within a block of natural video sequences is proposed. The proposed method assumes a parameterized probabilistic model for coded data and utilizes a maximum likelihood parameter estimation technique to estimate the model's parameters. The proposed method achieves a robust estimation of the...
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