Low-contrast small target image enhancement based on rough set theory

摘要

Contrast enhancement is important for small target detection and tracking. Conventional contrast enhancement techniques often fail to produce satisfactory results for images expressing unimodal intensity histograms. This paper presents a new contrast enhancement method based on rough set theory which is especially suitable for such images. The method uses the max of between-class mean to partition the image into two sub-images, the denoised target region and the denoised background region. Then the target region is enhanced by extend histogram. Experimental results indicate the new enhancement method is more suitable than traditional methods for handling the enhancement problems of low contrast small target images.