An Algorithm for Image Sharpening and Edge Detection using DWT-UM

Abstract

The field of Digital Image Processing (DIP) continues on a path of energetic growth in terms of popular and scientific interest and the number of commercial applications since 1970. The discipline of DIP covers a wide area of technical and engineering knowledge. It is built on a base of 1D and 2D signal processing theory. Broadly, image processing may be subdivided into the following categories: restoration, enhancement, coding, and understanding. The purpose of the first three categories is to improve the pictorial information either in quality (for purposes of improving visual appearance) or in transmission efficiency. In the last category, the objective is to obtain a symbolic description of the scene, leading to autonomous machine reasoning and perception. In this thesis our aim is to enhance the image for purpose of human interpretation and improving visual appearance. To improve the visual appearance of an image, image enhancement is done through the proper increment of contrast and brightness. Brightness refers to the overall lightness or darkness of the image. Contrast is the difference in brightness between objects or regions. But to make the image more clear and informatics, sharpening of edges are done. The sharp edges which makes it more pleasant to human eye and can be used for further image processing such as edge detection, segmentation etc. The amount of edge sharpening is much better than others existing sharpening methods. Sharpening is one of the most impressive transformations one can apply to an image since it seems to bring out image details that were not there before. A large number of algorithms have been designed for this purpose such as Unsharp Masking (UM), Gaussian and Laplacian filtering etc. In our proposed algorithm we have chose UM due to its simple calculation and less time of processing. In this thesis we have also measured the amount of sharpness by using the percentage of rise in values parameter. Finally the results for the image enhancement by using UM and DWT-UM techniques have been compared and have shown that there is enormous enhancement in image reproduction by using the proposed algorithm.