Abstract: Histogram Equalization（HE） is a simple and effective contrast enhancing technique, but it can’t preserve the mean brightness and the entropy of the image, and hence is seldom suitable for actual application. This paper proposes a new method about histogram specification to overcome those drawbacks of HE. This method（EPHEMP） makes the histogram as flat as possible by the fundamental idea of HE, and by the variation algorithm, finds a suitable target histogram maximize the mean brightness under the constraint that the entropy is constant, at last transforms the original histogram to that target one by histogram specification. Comparing to the existing methods including HE, BBHE, DSIHE, MMBEBHE, and BPHEME, experimental results show that EPHEMP can not only preserve the entropy, but also enhance the contrast of the image effectively. And hence it is possible to be used for many commercial purposes such as consumer electronic products.

Key words: contrast enhancement, histogram equalization, histogram specification, variation approach, entropy preserving

摘要： 直方图均衡化是一种简单有效的图像对比度增强技术，由于它无法保持图像的均值亮度和熵值，因此在实际工程中很少应用。提出了一种直方图规定化的新方法以避免直方图均衡化的缺点，该算法利用直方图均衡化的特点——使直方图分布尽可能均匀，通过变分法求出一个在熵值不变的约束下使得图像均值亮度最大化的直方图，最后将原始直方图转换成直方图规定化后的目标直方图。通过与已有方法HE/DSIHE/MMBEBHE/BPHEME比较，结果表明该方法不仅能够保持熵值，而且可以有效地增强图像对比度，可以用于消费型电子产品中。

关键词: 对比度增强, 直方图均衡化, 直方图规定化, 变分法, 保持熵值