Non-local mean despeckling algorithm based on edge strength map and region division for SAR image
In order to reduce the multiplicative speckle noise of synthetic aperture radar(SAR) image, an improved non-local mean (NLM) algorithm is proposed in this paper. Firstly, the coefficient of variation (CV) was used to estimate the SAR image region division threshold, and estimate area division factor...
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| Published in | Xi'An Gongcheng Daxue Xuebao Vol. 35; no. 1; pp. 75 - 80 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
Editorial Office of Journal of XPU
01.02.2021
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1674-649X |
| DOI | 10.13338/j.issn.1674-649x.2021.01.012 |
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| Abstract | In order to reduce the multiplicative speckle noise of synthetic aperture radar(SAR) image, an improved non-local mean (NLM) algorithm is proposed in this paper. Firstly, the coefficient of variation (CV) was used to estimate the SAR image region division threshold, and estimate area division factor based on threshold. Thus, the SAR image wasdivided into texture area and homogeneous area by area division factor. Then, similarity windows of different scales were used to estimate the ESM corresponding to pixels in different regions, and the ESM matrix of each pixel in the search window under the similarity window and the ESM matrix of the center pixel were selected further. Moreover, the two-norm of the ratio of the two corresponding elements were used to construct the similarity measurement parameter that adapts to the multiplicative noise, filter value was obtained by combining the similarity parameter with the adaptive decay factor dominated by CV. Finally, the non-local average weighted filtering of the SAR |
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| AbstractList | In order to reduce the multiplicative speckle noise of synthetic aperture radar(SAR) image, an improved non-local mean (NLM) algorithm is proposed in this paper. Firstly, the coefficient of variation (CV) was used to estimate the SAR image region division threshold, and estimate area division factor based on threshold. Thus, the SAR image wasdivided into texture area and homogeneous area by area division factor. Then, similarity windows of different scales were used to estimate the ESM corresponding to pixels in different regions, and the ESM matrix of each pixel in the search window under the similarity window and the ESM matrix of the center pixel were selected further. Moreover, the two-norm of the ratio of the two corresponding elements were used to construct the similarity measurement parameter that adapts to the multiplicative noise, filter value was obtained by combining the similarity parameter with the adaptive decay factor dominated by CV. Finally, the non-local average weighted filtering of the SAR |
| Author | Fei GAO Lei ZHU Zijin FENG |
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| SubjectTerms | edge strength map non-local mean filtering region division speckle noise synthetic aperture radar image |
| Title | Non-local mean despeckling algorithm based on edge strength map and region division for SAR image |
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