抄録
Histogram Equalization is a traditional image improvement method for enhancing image contrast. However, this image contrast improvement is unsuitable for some consumer electronic applications since mean brightness of output image is different from that of the original image. Nevertheless, when the average brightness of the output image is close to the mean brightness of the original image, its contrast is also decreased thereby reducing efficiency of contrast improvement algorithm. In this paper, we propose a method that not only preserves the mean brightness but also improves the contrast of the output image. By separating the Histogram into Sub-histograms or Multi-peak histogram based on local minima, each sub-histogram will be spread out in a maximum dynamic range based on their gray level interval proportions. Subsequently, the conventional histogram equalization is independently applied to sub-histogram of each peak. To preserve the mean brightness, positions of local minima will be finely adjusted by shifting them within a certain gray scale interval. During each adjustment, sub-histograms of the two local minima which connected to the new local minimum point are re-equalized again. Finally, standard deviation will be normalized in order to improve contrast of the output image.
