The design of the optimal inverse discrete cosine transform (IDCT) to compensate the quantization error is proposed for effective lossy image compression in this work. The forward and inverse DCTs are designed in pair in current image/video coding standards without taking the quantization effect into account. Yet, the distribution of quantized DCT coefficients deviate from that of original DCT coefficients. This is particularly obvious when the quality factor of JPEG compressed images is small. To address this problem, we first use a set of training images to learn the compound effect of forward DCT, quantization and dequantization in cascade. Then, a new IDCT kernel is learned to reverse the effect of such a pipeline. Experiments are conducted to demonstrate that the advantage of the new method, which has a gain of 0.11-0.30dB over the standard JPEG over a wide range of quality factors.

翻译：在这项工作中,为了有效压缩图像,建议设计最佳反离子共生变异(IDCT),以弥补量化错误。在不考虑量化效应的情况下,根据当前图像/视频编码标准,设计了前方和反方DCT。然而,量化的DCT系数的分布偏离了原始DCT系数的分布。当JPEG压缩图像的质量系数小时,这一点尤其明显。为了解决这一问题,我们首先使用一套培训图像来学习前方DCT、定量和级变分的复合效应。然后,学会了一个新的IDCT内核来扭转这种管道的效果。进行了实验,以证明新方法的优势,在一系列质量因素上比标准JPEG具有0.11-0.30DB的收益。