Improved de-noising method based on spare representation for remote sensing image

Delin Mo; Shuai Xing; Qin Xia; Tengda Jiang; Junjun Zhang; Zhongxiao Ge

doi:10.1117/12.2244882

29 August 2016 Improved de-noising method based on spare representation for remote sensing image

Delin Mo, Shuai Xing, Qin Xia, Tengda Jiang, Junjun Zhang, Zhongxiao Ge

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100331T (2016) https://doi.org/10.1117/12.2244882
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

Abstract

Remote sensing satellite image de-noising is an important step in image preprocessing. Four de-noising algorithms for remote sensing images are investigated in this paper: BM3D, DCT, K-SVD, and wavelet threshold method. A modified method based on K-SVD is also proposed. The basic principles of the four kinds of de-noising methods are introduced, and the modified method is analyzed thoroughly. In the improved method, high-frequency information is extracted through High-pass filtering, and then sparse representation and reconstruction are carried out to maintain the detail information. Comparative experiments are conducted to reveal the advantages and disadvantages of each method in satellite images de-noising, and the results demonstrate that the proposed method can get better de-noising result as well as keeping the details at the same time.

Citation Download Citation

Delin Mo, Shuai Xing, Qin Xia, Tengda Jiang, Junjun Zhang, and Zhongxiao Ge "Improved de-noising method based on spare representation for remote sensing image", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100331T (29 August 2016); https://doi.org/10.1117/12.2244882

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