Arici Tarik, Dikbas Salih, Altunbasak Yucel
Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
IEEE Trans Image Process. 2009 Sep;18(9):1921-35. doi: 10.1109/TIP.2009.2021548. Epub 2009 Apr 28.
A general framework based on histogram equalization for image contrast enhancement is presented. In this framework, contrast enhancement is posed as an optimization problem that minimizes a cost function. Histogram equalization is an effective technique for contrast enhancement. However, a conventional histogram equalization (HE) usually results in excessive contrast enhancement, which in turn gives the processed image an unnatural look and creates visual artifacts. By introducing specifically designed penalty terms, the level of contrast enhancement can be adjusted; noise robustness, white/black stretching and mean-brightness preservation may easily be incorporated into the optimization. Analytic solutions for some of the important criteria are presented. Finally, a low-complexity algorithm for contrast enhancement is presented, and its performance is demonstrated against a recently proposed method.
提出了一种基于直方图均衡化的图像对比度增强通用框架。在此框架中，对比度增强被视为一个最小化代价函数的优化问题。直方图均衡化是一种有效的对比度增强技术。然而，传统的直方图均衡化（HE）通常会导致过度的对比度增强，进而使处理后的图像看起来不自然并产生视觉伪像。通过引入专门设计的惩罚项，可以调整对比度增强的程度；噪声鲁棒性、白/黑拉伸和平均亮度保持可以很容易地纳入优化过程。给出了一些重要准则的解析解。最后，提出了一种低复杂度的对比度增强算法，并与最近提出的一种方法相比展示了其性能。
