Improved Color Satellite Image Segmentation Using Tsallis Entropy and Granular Computing

Jagan kumar. N (School of Information Technology and Engineering, VIT University, Vellore)
Agilandeeswari. L (School of Information Technology and Engineering, VIT University, Vellore)
Prabukumar. M (School of Information Technology and Engineering, VIT University, Vellore)

International Journal of Advances in Applied Sciences
Vol 6, No 4: December 2017

The research work is to improve the segmentation of the color satellite images. In this proposed method the color satellite image can be segmented by using Tsallis entropy and granular computing methods with the help of cuckoo search algorithm. The Tsallis and granular computing methods will used to find the maximum possibility of threshold limits and the cuckoo search will find the optimized threshold values based on threshold limit that is calculated by the Tsallis entropy and granular computing methods and the multilevel thresholding  will used for the segmentation of color satellite images based on the optimized threshold value that will find by this work and these methods will help to select the optimized threshold values for multiple thresholding effectively.