An image may suffer from some degradation such as blurriness. This degradation affects the image contrast. There are various approaches to improve the contrast of the images. Among these approaches, un-sharp masking is a popular method due to its simplicity in implementation and computation. In the un-sharp masking method, the details of the input image are boosted to improve the image quality. In this method, the quality of the enhanced image directly depends on the parameter named gain factor. Since the quality of an image may not be the same throughout the image, in this paper we propose an adaptive un-sharp masking method to locally improve the quality of the images. In this method, at first, the input image is divided into a number of overlapping blocks. Then the appropriate gain factor is estimated for the pixels of each block using the gradient information of the block. Subjective and objective image quality assessments are used to compare the performance of the proposed method with both the classic and the recently developed un-sharp masking methods. The experimental results show that the proposed method has a better performance in comparison to the other existing methods.
