为了改善直方图均衡对低灰度层密集分布图像的处理效果，通过分析图像直方图均衡理论对同一灰度像素在处理后映射到同一灰度的过程中存在的理论缺陷，提出了一种高效 的、自适应的算法。该算法首先对图像进行常规的直方图均衡处理， 然后对处理后所形成的图像灰度在一个较大的灰度范围内进行映射， 保证变换后的图像有较大的灰度动态范围， 最后对结果进行适当的亮度修正，保证变换图像整体有较高的对比度，便于观察图像的细节．通过实验证明，改进后的算法可以明显地改善直方图均衡处理低灰度层密集分布图像的效果，同时具有较高的算法效率，适合在实时图像处理系统 中采用。-In order to improve the histogram balanced to the low gradation level dense distribution image processing effect, through analysis image histogram isostatic theory to identical gradation picture element after processing maps theory flaw which the identical gradation in the process exists, proposed one kind highly effective, the auto-adapted algorithm. This algorithm first carries on conventional to the image the histogram equalization treatment, the gamma controller which then after processing forms in a great density latitude to carry on the mapping, guaranteed after the transformation the image has the great gradation dynamirange, finally carries on the suitable brightness revision to the result, guaranteed that the transformation image whole has the high contrast gradient, is advantageous for the observation image the detail. Proved through the experiment, after the improvement algorithm may improve the histogram equalization treatment low gradation level dense distribution image ob