Segmentation of SAR Satellite Images Using Cellular Learning Automata and Adaptive Chains
Gholamreza Akbarizadeh · Journal of Remote Sensing Technology · 2013
This paper presents a new method to segment SAR satellite images that depends on hard and easy segmentation processes. The proposed algorithm compounds the intensity information and input image texture using Cellular Learning Automata (CLA) in order to segment SAR images. In many of the segmentation techniques, some standards are first defined, and then the segmentation process acts according to this standards and neighbor image information. Information can be easily simulated and performed by CLA. Our proposed method performs in two steps: easy and hard segmentation. In easy segmentation step, input SAR satellite image is analyzed by CLA and we try to decrease intensity differences between pixels in same repeated region and produce an easy segmentation image, then this image is given to a hard segmentation system. Obtained results show that the proposed method is useful. KeywordsSynthetic Aperture Radar; SAR Image; Learning Automata; Cellular Learning Automata