National Institute of Statistical Sciences (NISS), Research Triangle Park, NC, USA.
IEEE Trans Image Process. 2000;9(5):889-96. doi: 10.1109/83.841534.
This paper proposes a scheme for adaptive image-contrast enhancement based on a generalization of histogram equalization (HE). HE is a useful technique for improving image contrast, but its effect is too severe for many purposes. However, dramatically different results can be obtained with relatively minor modifications. A concise description of adaptive HE is set out, and this framework is used in a discussion of past suggestions for variations on HE. A key feature of this formalism is a "cumulation function," which is used to generate a grey level mapping from the local histogram. By choosing alternative forms of cumulation function one can achieve a wide variety of effects. A specific form is proposed. Through the variation of one or two parameters, the resulting process can produce a range of degrees of contrast enhancement, at one extreme leaving the image unchanged, at another yielding full adaptive equalization.
本文提出了一种基于直方图均衡化（HE）推广的自适应图像对比度增强方案。HE 是一种用于改善图像对比度的有用技术，但对于许多目的来说，其效果过于剧烈。然而，只需进行相对较小的修改，就可以得到截然不同的结果。本文提出了自适应 HE 的简明描述，并在此框架中讨论了过去对 HE 变体的建议。这种形式主义的一个关键特征是“累积函数”，它用于从局部直方图生成灰度级映射。通过选择替代形式的累积函数，可以实现多种效果。本文提出了一种特定形式。通过一个或两个参数的变化，所得到的过程可以产生一系列对比度增强程度，在一个极端情况下保持图像不变，在另一个极端情况下则可以实现完全自适应均衡。
