Images are captured at low contrast in a number of different scenarios. Image enhancement algorithms are used in a variety of image processing applications, primarily to improve or enhance the visual quality of an image by accentuating certain features. Image processing modifies pictures to improve them (enhancement, restoration) to prepare suitable images for various applications from raw unprocessed images.Image enhancement improves the quality (clarity) of images for human viewing. Increasing contrast, and revealing details are examples of enhancement operations whereas removing blurring and noise comes under the category Image restoration.

In this paper comparison ofdifferent algorithms are used for image enhancement (histogram equalization, adaptive histogram equalization, continuous histogram equalization, decorrelation stretching, median filtering, negative image and intensity adjustment). In this decorrelation stretching, median filtering and intensity adjustment together gives the best method for enhancing because it not only increases the intensity values but also removes salt-and-pepper noise.