A histogram is a graphical representation of the brightness values that comprise an image. The brightness values (i.e. 0-255) are displayed along the x-axis of the graph. The frequency of occurrence of each of these values in the image is shown on the y-axis. Histogram of a digital image with intensity level in the range of [0, L-1 ] is a discrete function h(rk) = nk where rk is the kth intensity level and nk is no of a pixel in the image with intensity rk. Histogram equalization is a method in image processing of contrast adjustment using the image's histogram. Histogram equalization automatically determines a transformation function that seeks to produce output images that have a uniform histogram. When the automatic enhancement is desired that is the good approach because result from this technique are predictable and method is simple to implement. The method used to generate a processed image that has a specified histogram is called histogram matching or histogram specification. In this thesis we will use the advanced algorithm to enhance the quality of an image and we succeeded and also got the entropy value of image by changing the scaling factor K we got different value and also got different shifted histogram image. In our research work, we will work on the different level to analyze the effect of an algorithm. By changing scaling factor we analyze different EME and image enhanced significantly from which a lot of important information can be recovered.