Laser & Optoelectronics Progress, Volume. 57, Issue 20, 201010(2020)
SAR Flow Ice Separation Algorithm Combined with Saliency Detection
In the synthetic aperture radar (SAR) images, there are many complex background problems, such as speckle noise, close contact of floating ice in drift-ice area, and more small pieces of ice. Here, we describe a SAR flow ice separation algorithm based on background-suppression saliency detection. This algorithm obtains a preliminary saliency map by learning the random forest regression based on the saliency detection of images. Then the image region is constructed by using super pixels. Additionally, discrete Fourier transformation is performed, after which the frequency domain features of the region are extracted, and the chi-squared distance is calculated. The proposed algorithm then suppresses the boundary background to generate a background-suppression module diagram, followed by fusion of the two-stage graph to obtain the enhanced saliency graph. We evaluate the proposed algorithm and compare its performance against seven saliency algorithms and three sea-ice-segmentation methods using a SAR sea-ice dataset. The results show that the proposed algorithm can effectively detect isolated ice floes and suppress background areas.
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Hongxia Yang, Hao Guo, Yan Gao, Jubai An. SAR Flow Ice Separation Algorithm Combined with Saliency Detection[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201010
Category: Image Processing
Received: Dec. 24, 2019
Accepted: Feb. 25, 2020
Published Online: Oct. 13, 2020
The Author Email: Guo Hao (guohao0512@dlmu.edu.cn)