G. Lakhani
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引用次数: 8

摘要

只提供摘要形式。在JPEG基线压缩算法中,如果我们利用DCT系数分布在零处达到峰值并呈指数下降的观察结果,可以减少对DCT系数的量化损失。这意味着JPEG解码器用来恢复落在区间内的所有系数的量化区间的中点(例如m)可以被另一个点(例如y)取代,该点更接近于零,但在区间内。如果我们模型的分布/ splλ/ e /呷- x / splλ/ | | /,/ splλ/ > 0是一个常数,可引出的一些统计参数如均值、方差、和我们假设调整q = |我|应该选择这样损失之和量化区间内的所有系数下降为每个时间间隔为零,我们可以推出q = q (e /吃晚饭/ splλ/ (q1) + (q2) / 2) / 2 e /吃晚饭/ splλ/ (q1) / 1) 1 / / splλ/ q是量化器的步长。为了测试上述想法的有效性,我们实现了两种方法:(1)JPEG编码器为每个DCT分布计算/spl lambda/,并将其作为编码数据的一部分传递给解码器,(2)JPEG解码器在解码其输入时,从量化的DCT系数中逐渐计算/spl lambda/。通过实验,我们发现这些方法都没有很大的改进,但发现了一个更好的方法(OUR),它不需要任何DCT建模。它使用/spl Sigma/(|m-y|*C)//spl Sigma/C来计算调整,其中C是落在一个区间内的系数的数量,/spl Sigma/被用于不包含零DCT的所有区间。我们还实施了Ahumada等人开发的公式(参见SID Digest, 1994),将其与OUR方法的结果进行比较。比较显示在图像的RMSE的%减少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adjustments for JPEG de-quantization coefficients
Summary form only given. In JPEG baseline compression algorithm, the quantization loss to DCT coefficients can be reduced, if we make use of the observation that the distributions of the DCT coefficients peak at zero and decrease exponentially. It means that the mid-point of a quantization interval, say m, used by the JPEG decoder to restore all coefficients falling within the interval, may be replaced by another point, say y, closer to zero but within the interval. If we model the distributions by /spl lambda/e/sup -/spl lambda/|x|/, where /spl lambda/>0 is a constant, derivable from some statistical parameters such as mean or variance, and we assume that the adjustment q=|m-y| should be chosen so that the sum of the loss to all coefficients falling within a quantization interval is zero for each interval, we can derive q=Q(e/sup /spl lambda/(Q-1)/+(Q-2)/2)/2e/sup /spl lambda/(Q-1)/-1)-1//spl lambda/ where Q is the quantizer step size. To test usefulness of the above idea, we implemented both approaches: (1) JPEG encoder computes /spl lambda/ for each DCT distribution and passes it as part of coded data to the decoder, and (2) JPEG decoder computes /spl lambda/ from the quantized DCT coefficient incrementally as it decodes its input. Through experiments, we found that none of these approaches resulted in much improvements, but found a better approach (OUR) which does not require any modeling of DCT. It uses /spl Sigma/(|m-y|*C)//spl Sigma/C to compute adjustments, where C is the number of coefficients falling within an interval, and the /spl Sigma/ is taken over all intervals not-containing the zero DCT. We also implemented the formulation developed by Ahumada et. al (see SID Digest, 1994) to compare it with the results of OUR approach. The comparison is shown in terms of the % reduction in the RMSE of the images.
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