Mixed Pixel Resolution by Evolutionary Algorithm: A Survey

Now a day2019;s Remote Sensing is a mature research area. Remote sensing is defined as a technique for acquiring the information about an object without making physical contact with that image via remote sensors. But the major problem of remotely sensed images is mixed pixel which always degrades the image quality. Mixed pixels are usually the biggest reason for degrading the success in image classification and object recognition. Another major problem is the decomposition of mixed pixels precisely and effectively. Remote sensing data is widely used for the classification of types of features such as vegetation, water body etc but the problem occurs in tagging appropriate class to mixed pixels. In this paper we attempted to present an approach for resolving the mixed pixels by using optimization algorithm i.e. Biogeography based optimization. The main idea is to tag the mixed pixel to a particular class by finding the best suitable class for it using the BBO parameters i.e. Migration and Mutation

Mixels Resolution by hybridization approach (BBO & GA)

Abstract: "Mixels" are usually the biggest reason for degrading the image quality especially for remote sensing or satellites images. In this paper we present an approach for resolving the mixed pixels by using optimization algorithm i.e. Biogeography based optimization and genetic algorithm. The hybrid approach is used for resolving super pixel problem. This paper deals with the comparison of hybridization of BBO & GA with previously published paper results which are discussed in section V