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An Iterative SAR Image Filtering Method Using Nonlocal Sparse Model
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DOI：10.1109/LGRS.2015.2417551.png)
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Abstract
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In this letter, we propose an iterative synthetic aperture radar (SAR) image filtering method using the nonlocal sparse model. The original SAR image is first transformed to the logarithmic SAR image domain. Then, we use the nonlocal sparse model and the iterative regularization technique to denoise the log-intensity image. In each iteration, we update the noisy image and then estimate the noise variance. For each patch in the noisy image, we find several similar patches and stack them together in a group. This noisy group is filtered by simultaneous sparse coding. Then, all of the filtered groups are aggregated to form the denoised image. Experimental results demonstrate that the proposed method can achieve state-of-the-art SAR image despeckling performance.
Keywords:
Despeckling
iterative regularization
nonlocal sparse model
synthetic aperture radar (SAR)
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Multiplicative noise removal via sparse and redundant representations over learned dictionaries and total variation.png)
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