JOURNAL ARTICLE

Fast topology preserving PolSAR image superpixel segmentation

Abstract

In this paper, we propose a fast PolSAR image superpixel segmentation method. This method takes a simple coarse-to-fine optimization technique to minimize a Markov-Random-Field (MRF) like energy function which integrates the Pol- SAR image statistic, spatial position and boundary smoothing. It updates boundary of superpixels staring with a large block level and iterates down to the final pixel level. We demonstrate the performance of our approach both on the synthetic and real full polarimetric images , showing that our proposed approach can achieve significantly faster convergence than SLIC method, and make a good compromise between accuracy and computation speed.

Keywords:
Computer science Artificial intelligence Image segmentation Markov random field Smoothing Pixel Pattern recognition (psychology) Computer vision Boundary (topology) Segmentation Block (permutation group theory) Algorithm Mathematics

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Citation History

Topics

Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Synthetic Aperture Radar (SAR) Applications and Techniques
Physical Sciences →  Engineering →  Aerospace Engineering
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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