SAR image segmentation based on different gradients with nonlocal mean filter

Changkai Li Sr.

doi:10.1117/12.2601761

30 June 2021 SAR image segmentation based on different gradients with nonlocal mean filter

Changkai Li Sr.

Proceedings Volume 11878, Thirteenth International Conference on Digital Image Processing (ICDIP 2021); 118780P (2021) https://doi.org/10.1117/12.2601761
Event: Thirteenth International Conference on Digital Image Processing, 2021, Singapore, Singapore

Abstract

Aiming at the problem that SAR image segmentation is seriously interfered by the speckle, this paper studies the methods of SAR image segmentation based on different gradients under nonlocal mean (NLM) filter. We focus on four gradient operators, contained ratio of average(ROA), ratio of an exponentially weighted averages (ROEWA), Unsampled Wavelet Transform (UWT) and instantaneous coefficient of variation (ICOV). Firstly, the NLM filter is used to suppress the speckle and protect the structure in the SAR image. After that, the gradient of SAR image is calculated based on the above different gradient operators. Finally, the watershed technique is used to segment the image based on the gradient of SAR image. Experimental results show that the segmentation based on ICOV and UWT obtain more accurate boundary location and fewer segmentation regions than the methods based on ROA and ROEWA.

Citation Download Citation

Changkai Li Sr. "SAR image segmentation based on different gradients with nonlocal mean filter", Proc. SPIE 11878, Thirteenth International Conference on Digital Image Processing (ICDIP 2021), 118780P (30 June 2021); https://doi.org/10.1117/12.2601761

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