Resolving mixed pixels by hybridization of biogeography based optimization and ant colony optimization

Recent advances in remote sensing techniques made research possible in those areas where human hands are inaccessible. Digital Imagery brings the virtual image of a desired location, which requires some pre-processing to bring the view to an optimal level. Accuracy level in image classification is assumed on the categorization of the pixel into one of the several land cover classes. When the recognition of pixel accounts for two different classes at the same time, the resulting pixel is categorized as a mixed pixel. This paper proposes a novel approach by clustering the dataset of mixed pixel and thereafter implementing fusion of Ant Colony Optimization (ACO) and Biogeography Based Optimization (BBO) thereby resolving the problem of mixed pixels.