Comparative analysis on landsat image enhancement using fractional and integral differential operators

In this paper, Landsat image enhancement based on the fractional and integral differential methods is compared. Enhancement techniques used in remote sensing are based on the traditional integral order differential mask operators, such as Sobel, Prewitt and Laplacian operators. Other techniques involve the fractional calculus and general masks using Grunwald-Letnikov with eight directions. Notably, it is crucial to perform fractional filtering of I weight (intensity or brightness) in color space of (hue, saturation, intensity or brightness) according to the filtering rule. We study the quantitative analysis of enhancement performance via the gray-scale histogram and information entropy. Finally, we demonstrated that fractional differential operator is capable of enhanced performance superior to that of the integral differential operators. The optimal fractional order for image enhancement of Landsat Thematic Mapper is 1.15, 1.4, and 0.6 based on the (3 x 3), (5 x 5), and (7 x 7) masks, respectively.