Chronological Advancement in Image Processing from Lime Stone Mofits to Superpixel Classification

Image processing is widely used method for representation and extraction of information. The objective of this study is to get the information from the areas and objects which are not possible to be physically contact directly remote sensing image processing. While extracting the information from the remote sensed images, the major issues that affect the accuracy of the classification is the presence of mixed pixels (reflecting more than one spectral signature) in image. In this study, the authors have summarized the various eras of image processing from its origin and also give the various techniques and methods used to solve the problem of mixed pixels. In this study, a new algorithm is proposed to solve the mixed pixel problem by using PSO based Fuzzy C-mean and Biogeographical Based Optimization. This proposed algorithm will improve the classification of mixed pixels as compared to the literature.