In this letter, we propose a novel Uniformity-Approximated Histogram Equalization (UAHE) algorithm to enhance the image as well as to preserve the image features. First, the UAHE algorithm generates the image histogram and computes the average value of all bins as the histogram threshold. In order to approximate the uniform histogram, the bins of image histograms greater than the above threshold are clipped, and the subtracted counts are averaged and uniformly assigned to the remaining bins lower than the threshold. The approximated uniform histogram is then applied to generate the intensity transformation function for image contrast enhancement. Experimental results show that our algorithm achieves the maximum entropy as well as the feature similarity values for image contrast enhancement.