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一種基于視覺熵的圖像分割壓縮方法

Image Compression with Visual Entropy-Based Segmentation

  • 摘要: 基于視覺熵概念提出了一種靜止圖像分割壓縮方法.通過對人類視覺系統特性的歸納,總結了基于視覺熵的圖像分割原理,提出了用于量化圖像特征的數學定義和基于視覺嫡的分割算法.實驗結果表明,這種基于視覺熵的圖像分割壓縮算法既提高了壓縮比,又能保證壓縮后的重建圖像整體上具有高的主觀視覺感知質量.

     

    Abstract: An image compression method with Visual Entropy-Based segmentation is presented. Firstly the induction of the characteristics of Human Vision System(HVS) and the principles for Visual Entropy-based segmentation is made. Then the mathematic definition for quantification of image character and the algorithm for Visual Entropy-Based segmentation are fully described. The experimental results have shown that image compression with Visual Entropy-Based segmentation can not only gets a rather low bit rate but also gives satisfactory subjective perceptual quality. This method has well emulated the properties of HVS.

     

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