Wavelet Based Non-Local Means Filtering for Speckle Noise Reduction of SAR Images

被引:0
|
作者
Lee, Dea Gun [1 ]
Park, Min Jea [1 ]
Kim, Jeong Uk [1 ]
Kim, Do Yun [1 ]
Kim, Dong Wook [2 ]
Lim, Dong Hoon [3 ,4 ]
机构
[1] Korea Sci Acad, Busan, South Korea
[2] Busan Natl Univ, Dept Stat, Busan, South Korea
[3] Gyeongsang Natl Univ, Dept Informat Stat, Jinju 660701, South Korea
[4] Gyeongsang Natl Univ, RINS, Jinju 660701, South Korea
基金
新加坡国家研究基金会;
关键词
SAR image; speckle noise; wavelet transform; non-local means filter; two sample t-test;
D O I
暂无
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This paper addresses the problem of reducing the speckle noise in SAR images by wavelet transformation, using a non-local means(NLM) filter originated for Gaussian noise removal. Log-transformed SAR image makes multiplicative speckle noise additive. Thus, non-local means filtering and wavelet thresholding are used to reduce the additive noise, followed by an exponential transformation. NLM filter is an image denoising method that replaces each pixel by a weighted average of all the similarly pixels in the image. But the NLM filter takes an acceptable amount of time to perform the process for all possible pairs of pixels. This paper, also proposes an alternative strategy that uses the t-test more efficiently to eliminate pixel pairs that are dissimilar. Extensive simulations showed that the proposed filter outperforms many existing filters in terms of quantitative measures such as PSNR and DSSIM as well as qualitative judgments of image quality and the computational time required to restore images.
引用
收藏
页码:595 / 607
页数:13
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