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http://dx.doi.org/10.5351/KJAS.2010.23.3.595

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

Lee, Dea-Gun (Korea Science Academy)
Park, Min-Jea (Korea Science Academy)
Kim, Jeong-Uk (Korea Science Academy)
Kim, Do-Yun (Korea Science Academy)
Kim, Dong-Wook (Department of Statistics, Busan National University)
Lim, Dong-Hoon (Department of Information Statistics and RINS, Gyeongsang National University)
Publication Information
The Korean Journal of Applied Statistics / v.23, no.3, 2010 , pp. 595-607 More about this Journal
Abstract
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 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.
Keywords
SAR image; speckle noise; wavelet transform; non-local means filter; two sample t-test;
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