An interactive genetic algorithm-based image sharpening system considering user's liking

Abstract

Nowadays, digital images can be easily obtained, recorded and processed in accordance with the widespread use of digital cameras and personal computers. There is an image enhancement as one of most general image processing techniques. In the image enhancement, unsharp masking (UM) has been used widely because its algorithm is very simple and can produce good results. However, over-enhancement occurs in edge parts of the image. Additionally UM also is easy to generate artifacts such as jaggy and halo. To cope with these problems, the authors proposed the selective UM method based on the edge-preserved smoothing filter. However, the image quality obtained by our method depends on values of the enhancement parameters, and their optimal values vary according to user's liking. In this paper, we propose an image enhancement system considering the user's liking by using an interactive genetic algorithm (IGA). In the proposed system, the IGA optimizes the parameters of the image enhancement. Further, a new genetic operation is introduced in order to achieve the effective search in the IGA of the proposed system. Through the experiments using some images, the effectiveness of the proposed system is verified.