Gray level enhancement to emphasize less dynamic region within image using genetic algorithm

Contrast enhancement plays an important role in image processing system. Enhancement is used to improve the appearance of an image and make it easier for visual interpretation, understanding and analysis of an image. Linear stretching and histogram equalization are the most common methods that are used for contrast enhancement, but the image that is enhanced by linear stretching or histogram equalization has bright and unnatural contrast. So we proposed a method that is based on genetic algorithm. This method enhances an image with natural contrast. In local contrast enhancement image can be enhanced using four parameters `a´, `b´, `c´ and `k´, where `a´, `b´, `c´ and `k´ are constants. We proposed a method in that the goal of contrast enhancement is achieved using these parameters with the new extension in their range. Local contrast enhancement increases the gray level of original image on the bases of light and dark edges. This proposed method has applied on m×n size of an original gray scale image. The local mean and local standard deviation of entire image, minimum value and maximum value of the image are used to statistically characterize digital image.