Contrast Enhancement for Medical Images Based on Histogram Equalization Followed by Median Filter

The goal of image enhancement technique is to improve a characteristics or quality of an image, such that the resulting image is better than the original image. Histogram equalization (HE) is widely used for contrast enhancement. However, it tends to change the brightness of an images, where preserving the original brightness is essential to avoid annoying artifacts. So Bi-histogram equalization (BBHE) has been proposed and analyzed mathematically that it can preserve the original brightness to a certain extends. However, there are still cases that are not handled well by BBHE, as they require higher degree of preservation. The extension of BBHE is Minimum Mean Brightness Error Bi-Histogram Equalization (MMBEBHE). The result of MMBEBHE is bad for the image with a lot details. To overcome these drawbacks, a new method is proposed. In this method, image enhancement is performed by MMBEBHE based on a modified contrast stretching manipulation. While the image is enhanced, the impulse noises present in the images are also enhanced. To avoid this effect, the enhanced image is passed through a median filter. The median filter is an effective method for the removal of impulse based noise on images. This is due to the partial averaging effect of the median filter and its biasing of the input stream, rather than straight mathematical averaging. Keywords—Image Enhancement, Contrast stretching, histogram equalization (HE), MMBEBHE, padding, median filter.