提高小波域噪声图像的重构质量

E. Medvedeva, I. Trubin
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引用次数: 0

摘要

提出了一种提高噪声压缩图像重建质量的方法。为了减少传输的数据量,他们提出只使用经过低频小波滤波后的子带图像,信号能量浓度最高。为了在随机马尔可夫场小波区域中恢复噪声图像,提出了一种基于二维马尔可夫链数学模型的二维非线性滤波算法。在减少信道发射端的计算资源的情况下,所考虑的恢复噪声压缩图像的方法在信噪比高达-6 dB和压缩比高达64倍的情况下有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving the Quality of Reconstruction of Noisy Images in the Wavelet Region
The authors suggest an approach to improving the quality of reconstruction of noisy compressed images. To reduce the amount of transmitted data, they offer to use only a subband image after a low-frequency wavelet filter with the highest concentration of signal energy. To restore a noisy image in the wavelet region, which is a random Markov field, it is proposed to use a two-dimensional nonlinear filtering algorithm based on a mathematical model of a two-dimensional Markov chain. The considered method of recovering noisy compressed images is effective at signal-to-noise ratios up to -6 dB and compression ratio up to 64 times when computing resources on the transmitting side of the channel are reduced.
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