29 August 2016 Improved de-noising method based on spare representation for remote sensing image
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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.
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Delin Mo, Delin Mo, Shuai Xing, Shuai Xing, Qin Xia, Qin Xia, Tengda Jiang, Tengda Jiang, Junjun Zhang, Junjun Zhang, Zhongxiao Ge, 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); doi: 10.1117/12.2244882; https://doi.org/10.1117/12.2244882
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