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Remote Sens. 2017, 9(12), 1311;

SAR Image De-Noising Based on Shift Invariant K-SVD and Guided Filter

Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China
Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing 100044, China
Electronic Information Engineering College, Hebei University, Baoding 071002, China
Author to whom correspondence should be addressed.
Received: 7 November 2017 / Revised: 10 December 2017 / Accepted: 12 December 2017 / Published: 13 December 2017
(This article belongs to the Section Remote Sensing Image Processing)
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Finding a way to effectively suppress speckle in SAR images has great significance. K-means singular value decomposition (K-SVD) has shown great potential in SAR image de-noising. However, the traditional K-SVD is sensitive to the position and phase of the characteristics in the image, and the de-noised image by K-SVD has lost some detailed information of the original image. In this paper, we present one new SAR image de-noising method based on shift invariant K-SVD and guided filter. The whole method consists of two steps. The first deals mainly with the noisy image with shift invariant K-SVD and obtaining the initial de-noised image. In the second step, we do the guided filtering for the initial de-noised image. Finally, we can recover the final de-noised image. Experimental results show that our method not only has better visual effects and objective evaluation, but can also save more detailed information such as image edge and texture when de-noising SAR images. The presented shift invariant K-SVD can be widely used in image processing, such as image fusion, edge detection and super-resolution reconstruction. View Full-Text
Keywords: shift invariance; K-SVD; guided filter; image de-noising; SAR image shift invariance; K-SVD; guided filter; image de-noising; SAR image

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Ma, X.; Hu, S.; Liu, S. SAR Image De-Noising Based on Shift Invariant K-SVD and Guided Filter. Remote Sens. 2017, 9, 1311.

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