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- W3037058434 abstract "Synthetic Aperture Radar (SAR) image segmentation based on intensity information alone poses severe inaccuracy due to the presence of speckle noise. The multiplicative speckle noise produces salt and pepper noise effect in the end product of the image and thereby making it difficult to segment the images efficiently. Moreover, due to the same reason, by applying the classical methods which are based on thresholding and clustering, satisfactory results are often not achieved. Since the SAR images as they are in their original state cause a severe obstacle in segmentation, here it is proposed to first extract the roughness information feature in terms of local entropy and median filtered image; and then feed to the fuzzy inference system. The fuzzy inference system then takes inputs from two different features and decide the segmentation criteria. The end result from the Fuzzy classifier is then thresholded using Otsu’s method to get the final segmented image. The proposed method simplifies the segmentation by generalizing the possible spatial features to be extracted and incorporated in the segmentation process while resulting to efficient and effective results." @default.
- W3037058434 created "2020-07-02" @default.
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- W3037058434 date "2020-01-01" @default.
- W3037058434 modified "2023-09-26" @default.
- W3037058434 title "Single Look SAR Image Segmentation Using Local Entropy, Median Low-Pass Filter and Fuzzy Inference System" @default.
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- W3037058434 doi "https://doi.org/10.1007/978-981-15-6315-7_12" @default.
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