A Water Change Detection Method of SAR Images Based on #br# New Difference Operator and Texture

doi:10.3969/j.issn.1006-2475.2020.04.015

Abstract

Abstract: Aiming at the problems of isolated noise points, artificial selection of partial parameters and incomplete information utilization in multi-temporal Synthetic Aperture Radar (SAR) change detection, an improved water change detection method of SAR images based on new difference operator and texture is proposed. First, according to characteristics of SAR images, combining with Log Ratio (LR) operator and Logarithmic Likelihood Ratio (LLR) operator, a new difference operator is proposed to amplify the characteristics of unchanged and changed regions. Then, according to the ratio graph of the histogram at two adjacent gray level in the new difference image, the threshold of initial segmentation is determined. Second, a new Fuzzy Local Information C-Means (FLICM) clustering method is proposed. This method utilizes the threshold from the previous step to obtain the initial clustering center. Then the texture-based FLICM method (FLICM_texture) is proposed to divide the difference image into three categories. Third, this paper divides the transition region again according to the threshold obtained by the difference image. This paper utilizes the SAR images over Canadas Ottawa, the Switzerland’s Bern and Chennai to demonstrate the superiority of this method. The Percentage of Correct Classifications (PCC) of Ottawa is 98.00%, the kappa coefficient is 92.03%. In Bern, the PCC can reach 99.66% and the kappa coefficient is 85.77%. In Chennai, the PCC can reach 98.83% and the kappa coefficient is 84.96%.

Key words: SAR, water change detection, difference operator, texture, FLICM, Chennai

CLC Number:

TN958

LI Ling-yu, ZHANG Yi. A Water Change Detection Method of SAR Images Based on #br# New Difference Operator and Texture[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2020.04.015.

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