基于直方图均衡化图像增强的两种改进方法

直方图均衡化（Histogram Equalization，HE）是图像增强领域中基础性很强的方法，对其研究和改进工作至关重要.首先，本文分析了经典HE算法的缺点，也概括了五类基于直方图均衡化的图像增强技术，然后针对HE经典算法的缺点提出了两种改进方法，分别引入了直方图动态削峰技术和边缘信息融合技术，最后选取曝光不足和过曝光的两类图像验证算法的性能，采取了有效的图像客观质量评价指标对实验结果做出评价.结合主客观图像质量评价可以看出，本文提出的算法具有增强效果好、输入参数少等特点.

Two Improved Methods Based on Histogram Equalization for Image Enhancement

HE (Histogram Equalization) is a fundamental method in the field of image enhancement,the research and improvement about which is very significant.First,this paper analyzes the disadvantages of the classical HE algorithm and summarizes five kinds of image enhancement techniques based on HE.Then,two kinds of improved methods are proposed aiming at the disadvantages of the classical HE algorithm,the techniques of the peak clipping and the edge information fusion are introduced.Finally,underexposure and overexposure images are selected to verify the algorithms' properties,the standard of efficient image objective quality assessment is selected to evaluate the experimental results.The assessment of image subjective and objective quality shows the algorithms this paper proposes have the characteristics of better results,less input parameters and so on.