首页> 外文会议>Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on >A new algorithm of projection onto narrow quantization constraint set for postprocessing of quantized images
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A new algorithm of projection onto narrow quantization constraint set for postprocessing of quantized images

机译:投影到窄量化约束集上的新算法,用于量化图像的后处理

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In this paper, we propose a new method to reduce coding artifacts in transform image coding. It consists of a filtering scheme in spatial domain followed by a new projection algorithm onto the narrow quantization constraint set (NQCS). Generally, the projection onto NQCS can provide a better performance in terms of PSNR than the projection onto the conventional QCS. When the value of the narrowing factor is low, however, the projection onto NQCS does not guarantee a better performance, because it projects the transform coefficients that lie inside of the Original QCS onto NQCS. The proposed method projects transform coefficients that lie only outside of the original QCS onto the NQCS. Different projection methods are used for AC and DC coefficients, because the characteristics of distribution are different. The PSNR improvement ranges between 0.7 and 1.4 dB, compared with the decoded images without postprocessing. The PSNR gain of 0.2 to 0.5 dB is obtained, compared with the conventional projection method onto the NQCS.
机译:在本文中,我们提出了一种减少变换图像编码中的编码伪像的新方法。它由空间域中的过滤方案组成,然后是对窄量化约束集(NQCS)的新投影算法。通常,与在常规QCS上的投影相比,在NQCS上的投影可以提供更好的PSNR性能。但是,当缩小因子的值较低时,投影到NQCS上并不能保证更好的性能,因为它将原始QCS内的变换系数投影到NQCS上。所提出的方法将仅位于原始QCS之外的变换系数投影到NQCS上。由于分布特性不同,因此对AC和DC系数使用不同的投影方法。与没有后处理的解码图像相比,PSNR的改善范围在0.7至1.4 dB之间。与在NQCS上的常规投影方法相比,可以获得0.2至0.5 dB的PSNR增益。

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