A modified fuzzy C means approach for segmenting the input flood images captured by synthetic aperture radar. (10th February 2023)

• Record Type: Journal Article
• Authors: Natteshan, N.V.S.; Nagarajan, Sureshkumar
• Is Part Of: International journal of intelligent enterprise. Volume 10:Number 2(2023)
• Page Start: 180
• Page End: 191
• Publication Date: 2023-02-10
• Subjects: fuzzy C means -- de-speckling -- clustering -- quantisation -- aggregation -- segmentation; Organizational learning -- Periodicals; Knowledge management -- Periodicals; Business intelligence -- Periodicals; Business enterprises -- Design -- Periodicals; Organizational effectiveness -- Periodicals; 658.005
• Languages: English
• ISSNs: 1745-3232

Abstract

Image segmentation is a process of separating a homogenous area into a heterogeneous area. In this work the fuzzy C means algorithm is utilised for segmenting the flooded areas in the given input image based on intensity of images. But there is a problem of speckle noise occurring in the images due to backscattered echo from earth surface. Hence a fuzzy discontinuity adaptive weight based non-local means filtering is being used to eliminate the speckle noise. In the fuzzy C means segmentation algorithm a modification is proposed which is done as two steps namely the quantisation and aggregation. A modified fuzzy C means algorithm is required in order to reduce the convergence rate of the algorithm. This research work particularly focuses on the application of the fuzzy C means clustering algorithm for segmenting the flood occurred regions and further processing of the flood occurred regions will be carried out.