The basic theory of the histogram equalization algorithm is analyzed, the image gray level, especially the gray level that denotes the image details is amalgamated overly, which can cause the imager after processing to lose the details and become fuzzy. In order to solve this problem, an algorithm for the increasing image gray level after the histogram equalization is proposed. Firstly, extract the high frequency details of the original image from the space or the frequency domain, and then add them with the image processed by the histogram equalization, lastly, the different image after enhancement is gained by adjusting the weight coefficient of the high frequency. The experimental results show that comparing with the traditional histogram equalization, the overall contrast can be enhanced and retained the more details of the original image.