基于场景分类的细节保留直方图均衡算法

针对传统直方图均衡算法细节丢失和亮度饱和的问题，提出一种将场景分类和细节保留相结合的直方图均衡改进算法。利用图像的直方图特征进行场景分类，结合场景分类及图像像素点的特征对分段式直方图均衡处理方法的参数进行优化。改进后的算法复杂度仅为O(L)(L是图像的像素灰度级)，既保留了直方图均衡算法计算量小的特点，又能避免传统直方图均衡的细节丢失和亮度饱和问题，还具有适用于不同场景的稳健处理效果。通过德州仪器公司DM648平台实测验证，该算法可以用于实时视频图像的增强。

Scene classification based details preserving histogram equalization

Due to the swallow and over-enhancement problems of traditional histogram equalization, an improved histogram equalization algorithm combining scene classification and details preservation was proposed. In this algorithm, images were classified according to their histogram features. The parameter of piecewise histogram equalization was optimized according to the scene classification and the characteristics of image histogram. The complexity of the improved algorithm is only O(L).L is the level of image grayscale, and equals to 256 here. The improved algorithm has the small amount of computation and solves the swallow and over-enhancement problems of traditional histogram equalization. The results from TI (Texas Instruments) DM648 platform show the algorithm can be used for real-time video image enhancement.