一种用于减少块伪影的卷积模型和倒谱滤波算法

N. Cho
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引用次数: 2

摘要

提出了一种用于减少压缩图像和视频中的块伪影的卷积模型和倒谱滤波算法。由于压缩图像的每条水平线或垂直线几乎每隔8个样本就会发生突变,因此可以将图像建模为原始序列与周期为8的激励信号的卷积。倒频谱的比较也表明,压缩信号倒频谱的8个样本的倍数通常比原始的倒频谱的倍数具有更大的幅度。本文提出的滤波算法是对倒频谱每8个样本进行降阶,并将降阶后的值分散到邻近样本中。该算法在倒频谱域中进行,只减少引起阻塞伪影的激励信号。因此,高频内容没有减少后处理,而传统的低通滤波模糊图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A convolution model and a cepstral filtering algorithm for the reduction of blocking artifacts
Proposes a convolution model and a cepstral filtering algorithm for reducing the blocking artifacts in compressed images and videos. Since each of the horizontal or vertical lines of the compressed image has abrupt changes at almost every 8th sample, images can be modeled as a convolution of the original sequence with an excitation signal of periodicity 8. Comparison of the cepstrums also shows that the multiples of 8th samples of the compressed signal's cepstrum usually have larger magnitudes than those of the original. The proposed filtering algorithm is to reduce the magnitudes of every 8th sample of the cepstrum, and disperse the reduced values to the neighboring samples. The algorithm is conducted in the cepstrum domain for reducing only the excitation signal which is the cause of blocking artifacts. Hence, the high frequency contents are not reduced by the postprocessing, whereas the conventional lowpass filtering blurs the image.
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