Acta Optica Sinica, Volume. 34, Issue 9, 901004(2014)
Satellite Remote Sensing Cloud Image Segmentation Using Edge Corrected CV Model
Segmenting satellite remote sensing cloud images is an essential step of analyzing satellite cloud image data. In order to segment satellite remote sensing cloud images more accurately, a satellite remote sensing cloud image segmentation method based on Chan Vese (CV) model incorporating edge information is proposed. Satellite cloud image is diffused and a smooth image is obtained. The edge information is calculated based on the smooth image. The edge information is incorporated into the CV model, and a distance regularized term is added to avoid the reinitialization of the level set function during its evolution. Experimental results show that, compared with conventional CV model, region-scalable fitting energy level set model and bias field correction level set model, the proposed method can segment region of cloud more accurately and the speed is faster.
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Song Yu, Wu Yiquan, Bi Shuoben. Satellite Remote Sensing Cloud Image Segmentation Using Edge Corrected CV Model[J]. Acta Optica Sinica, 2014, 34(9): 901004
Category: Atmospheric Optics and Oceanic Optics
Received: Mar. 27, 2014
Accepted: --
Published Online: Aug. 15, 2014
The Author Email: Yu Song (519559374@qq.com)