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A distortion analysis of image VQ-based coding using a finite mixture distribution model

机译:基于图像VQ的编码的失真分析使用有限混合混合模型

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Traditional coding schemes break an image into blocks prior to coding. It is possible to classify current algorithms according to the block construction. Either the block size is kept constant, or the block size is image dependent. Since most natural images can be divided into regions of high and low detail, variable block-size coding techniques exploit more efficiently the structure of the data. The superior performance of this scheme over fixed block ones has been observed experimentally. Rate-distortion analysis is carried out for compression systems using vector quantization. Using an appropriate model of the signal we derive analytical results that assess the superiority of variable block vector quantization algorithms.
机译:传统的编码方案在编码之前将图像分解为块。可以根据块结构对当前算法进行分类。块大小保持常量,或者块大小取决于图像。由于大多数自然图像可以分为高低细节的区域,因此可变块尺寸的编码技术更有效地利用数据的结构。通过实验观察到该方案对固定块的优越性。使用矢量量化对压缩系统进行速率失真分析。使用适当的信号模型,我们推导了评估可变块矢量量化算法的优越性的分析结果。

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