Application Of Mathematical Convolution Approach Of Image Sharpening To Digital And Satellite Imaging

This research paper explores the roles of convolution and Laplacian operators in image sharpening, with the primary objective of enhancing image clarity. The study delves into the mathematical foundations of these operators and their application in digital image processing. Methods are compared to evaluate their effectiveness in terms of computational efficiency and visual outcomes. The paper identifies the gaps in existing literature, particularly the lack of comprehensive literature on the derivation of the Laplacian kernel and reasons for post-processing methods after its convolution with an image. The literature in this paper helps understand the foundation of Laplacian kernel, offering valuable insights on its derivation, and setting the basis for other techniques that have been built on it, with applications in satellite imagery and digital photography. Also, comparison of Laplacian kernel with unsharp masking method is presented.