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- W2185895358 abstract "This paper presents an unsupervised distribution free change detection for Synthetic Aperture Radar (SAR) images based on an image fusion strategy and novel fuzzy clustering algorithm. Here we first perfom the mean ratio and log ratio on two original images and then apply DWT based fusion rules for performing image fusion and apply RFLICM and FLICM techniques for DWT based fused image. The image fusion technique is introduced to generate a difference image by using complementary information by performing log ratio and mean ratio on two original images and by applying DWT based fusion rules. Since the SAR images suffer from the speckle noise, so thatht's why we proposed an unsupervised distribution-free change detection approach for Synthetic Aperture Radar images based on an image fusion strategy and novel fuzzy clustering algorithm. A reformulated fuzzy local instruction C- means (RFLICM) clustering algorithm is proposed for classifying changed and unchanged regions in the fused difference image. Experiments on real SAR images show that the image fusion strategy integrates the advantages of the log ratio operator and the mean ratio operator and gains better performance. The change detection results obtained by the improved fuzzy clustering algorithm exhibited lower error than its preexistences." @default.
- W2185895358 created "2016-06-24" @default.
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- W2185895358 date "2013-01-01" @default.
- W2185895358 modified "2023-09-27" @default.
- W2185895358 title "Robust Technique for Change Detection in Multitemporal Synthetic Aperture Radar Images" @default.
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