Multilevel Thresholding based on Cuckoo Search Algorithm using Tsallis's Objective Function for Coastal Video Image Segmentation

Image segmentation could be a difficult surroundings is a due to the presence of weakly correlated and ambiguous multiple regions of interest. Many algorithms are developed to get optimum threshold values for segmenting satellite images with efficiency in their quality and blurred regions of image. In this paper a novel multilevel thresholding algorithm using a Cuckoo Search (CS) algorithm has been proposed for solving the coastal video image segmentation problem. The optimum threshold values are determined by the maximization of Tsaliis’s objective function using CS algorithm. In this paper, the analysis of CS algorithm performance is combined with Tsallis's objective function. Based on evaluations of PSNR, FSIM and Convergence characteristi CS, the Algorithm CS based on Tsallis objective function evolved to be most promising and computationally efficient for segmenting coastal video images achieve stable global optimum thresholds. The experiments results encourages related researches in computer vision, remote sensing and image processing applications.