A clustering algorithm with optimized multiscale spatial texture information: application to SAR image segmentation

作者：Tian, Xiaolin^*; Jiao, Licheng; Zhang, Xiaohua

来源：International Journal of Remote Sensing, 2013, 34(4): 1111-1126.

DOI：10.1080/01431161.2012.718455

An image segmentation method based on optimized spatial texture information is proposed in this article. Spatial information, including the relative position of neighbouring pixels and texture features of the multiscale neighbourhood, is incorporated into the similarity measure of the fuzzy c-means (FCM) clustering algorithm, in which the Gaussian kernel is adopted to diminish the local incorrect segmentation. The FCM clustering is spatially adjusted and optimized by the particle swarm optimization (PSO) algorithm. The purpose of optimization is to obtain the appropriate control parameters influencing spatial information, which can improve segmentation results. Experimental results demonstrate that the proposed method achieves better segmentation performance and is capable of effectively segmenting synthetic images and synthetic aperture radar (SAR) images.

• 出版日期2013
• 单位西安电子科技大学