Non-linear Image Enhancement Using Opportunity Costs

Abstract

Image enhancement is a commonly used method for the improvement of the quality of blurred image. Among many image enhancement approaches, the nonlinear image enhancement method has a simple structure and can obtain a good processing effect. For various target images, it is difficult to decide the best combination of clipping and scaling parameters within the nonlinear image enhancement method. In this paper, we propose a new method involving the concept of opportunity cost to simulate the image enhancement, and identify the most suitable enhancement parameters of clipping and scaling. Furthermore, a smoothing cubic B-spline filter is proposed for the conventional nonlinear image enhancement. Experimental results show that the proposed method improves the quality of blurred image and obtains a better subjective quality and objective PSNR performance than other nonlinear image enhancement methods.