An efficient modified fuzzy possibilistic c-means algorithm for segmenting color based hyperspectral images

In computer vision, segmentation refers to the process of partitioning a digital image into multiple segments. Image segmentation is typically used to locate objects and boundaries in images. Image segmentation is the process of assigning a label to every pixel in an image such that pixel with the same label share contain visual characteristics. In this paper present a new approach for color based image segmentation by applying modified fuzzy possiblitic c-means algorithm. Normally, due to the progress in spatial resolution of satellite imagery. The methods of segment-based image analysis for generating and updating geographical information are being more and more important. So in this paper the main objective of this paper is to get a non-overlapping of image and a reliable output.