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Shape-adaptive image compression using lossy shape coding, SA-prediction, and SA-deblocking

机译:使用有损形状编码,SA预测和SA解块的形状自适应图像压缩

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As the annoying blocking or ghost artifacts tend to appear in the conventional compression approaches either in the JPEG or JPEG2000 standards at low bitrate, the concept of the object-oriented image compression is proposed. This kind of methods is able to retain the image structural boundaries and therefore has relatively good visual qualities even in high compression ratios. In this paper, we propose a shape-adaptive image compression scheme employing an efficient lossy contour compression algorithm to encode the region information, which is usually the main overhead data in such systems. In addition, the prediction and deblocking techniques commonly used in novel compression approaches are also applied with the proposed shape-adaptive versions. Simulation results suggest that the proposed compression system is able to provide compressed images with much better visual qualities and more reasonable degradation forms compared to other prevailing methods.
机译:由于在低比特率下在JPEG或JPEG2000标准中的常规压缩方法中容易出现烦人的阻塞或重影伪影,因此提出了面向对象的图像压缩的概念。这种方法能够保留图像结构边界,因此即使在高压缩比下也具有相对较好的视觉质量。在本文中,我们提出了一种形状自适应的图像压缩方案,该方案采用有效的有损轮廓压缩算法对区域信息进行编码,该信息通常是此类系统中的主要开销数据。另外,在新颖的压缩方法中通常使用的预测和解块技术也与提出的形状自适应版本一起应用。仿真结果表明,与其他主流方法相比,所提出的压缩系统能够提供具有更好视觉效果的压缩图像和更合理的降级形式。

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