A modified Unsharp Masking method using Particle Swarm Optimization

Unsharp Masking is an effective and simple method of contrast enhancement. This paper explores the Unsharp Mask using the Laplacian Operator. The proposed method optimizes the Laplacian coefficient, α, and the Unsharp Mask´s gain by maximizing the information content. The optimization process used was Multi-objective Particle Swarm Optimization. The proposed method was applied on both a global and local scale. The results show that the proposed method outperforms the classic Unsharp Masking method. The method is intended for gray-level images but can be applied to color images in general.