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An Iterative SAR Image Filtering Method Using Nonlocal Sparse Model
DOI:10.1109/LGRS.2015.2417551.png)
摘要
En 中文
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.
Keyword:
Despeckling
iterative regularization
nonlocal sparse model
synthetic aperture radar (SAR)
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期刊
IF:
16.4
论文数:
1.0W
被引数:
5.1K
机构
引用论文
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Image denoising via sparse and redundant representations over learned dictionaries通过学习字典上的稀疏和冗余表示进行图像去噪
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SIGNAL PROCESSING
IF3.6

