Abstract: This paper introduces noise suppression using adaptive filtering especially for Gaussian and speckle noise. This filter is used for the sharpness enhancement of degraded image and performs well for Gaussian noise and speckle noise reduction. A simple and effective based on the combined difference image and k-means clustering is proposed for the synthetic aperture radar (SAR) image change detection task. First, we use one of the most popular denoising methods, the probabilistic-patch-based algorithm, for speckle noise reduction of the two multitemporal SAR images, and the subtraction operator and the log ratio operator are applied to generate two kinds of simple change maps. Then, the mean filter and the median filter are used to the two change maps, respectively, where the mean filter focuses on making the change map smooth and the local area consistent, and the median filter is used to preserve the edge information.
Keywords: Change detection, Difference image, K-means clustering, SAR images.
Title: Combined Difference Image and Fuzzy C-Means Clustering for SAR Image Change Detection
Author: O. Chitrapraba
International Journal of Electrical and Electronics Research
ISSN 2348-6988 (online)
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