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      Performance Analysis of Segmentation of Hyperspectral Images Based on Color Image Segmentation

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          Abstract

          Image segmentation is a fundamental approach in the field of image processing and based on user’s application .This paper propose an original and simple segmentation strategy based on the EM approach that resolves many informatics problems about hyperspectral images which are observed by airborne sensors. In a first step, to simplify the input color textured image into a color image without texture. The final segmentation is simply achieved by a spatially color segmentation using feature vector with the set of color values contained around the pixel to be classified with some mathematical equations. The spatial constraint allows taking into account the inherent spatial relationships of any image and its color. This approach provides effective PSNR for the segmented image. These results have the better performance as the segmented images are compared with Watershed & Region Growing Algorithm and provide effective segmentation for the Spectral Images & Medical Images.

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          Author and article information

          Journal
          Journal of Applied and Computational Mechanics
          Shahid Chamran University of Ahvaz
          01 June 2017
          : 3
          : 2
          : 144-149
          Affiliations
          [1 ] Poorima College of Engineering, Department of Electronics & communication Engineering, Jaipur, Rajasthan, India
          [2 ] Poorima College of Engineering, Department of Mathematics, Jaipur, Rajasthan, India
          [3 ] MIT, Department of Electronics & communication Engineering, Jaipur, Rajasthan, India
          Article
          2962ace8248c485ba032f04ed65b1156
          10.22055/jacm.2017.12639
          0a796567-61de-4b9b-9759-a668ab0433af

          This work is licensed under a Creative Commons Attribution Non Commercial 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/4.0/legalcode

          History
          Categories
          Mechanics of engineering. Applied mechanics
          TA349-359

          Chaos, fractals & dynamical systems,Engineering,Nanotechnology,Sensor materials,Mechanical engineering,Renewable energy
          Hyperspectral,EM,Segmentation

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