Deng Guang
IEEE Trans Image Process. 2009 May;18(5):1135-40. doi: 10.1109/TIP.2009.2016796. Epub 2009 Mar 16.
The logarithmic image processing (LIP) model is a mathematical theory that provides new operations for image processing. The contrast definition has been shown to be consistent with some important physical laws and characteristics of human visual system. In this paper, we establish an information-theoretic interpretation of the contrast definition. We show that it can be expressed as a combination of the relative entropy and Shannon's information content. Based on this new interpretation, we propose an adaptive algorithm for enhancing the contrast and sharpness of noisy images.
对数图像处理（LIP）模型是一种为图像处理提供新操作的数学理论。已证明对比度定义与人类视觉系统的一些重要物理定律和特性相一致。在本文中，我们建立了对比度定义的信息论解释。我们表明它可以表示为相对熵和香农信息量的组合。基于这种新解释，我们提出了一种用于增强噪声图像对比度和清晰度的自适应算法。
