基于直方图修正的局部对比度增强算法

针对传统直方图均衡化算法经常导致过增强,噪声放大和局部对比度低等缺点,提出了基于直方图修正的局部对比度增强算法。首先,利用自适应部分子块重叠方法把图像划分成一系列的子块,子块的大小能根据图像局部特征自适应调整;然后,对每个子块采用基于直方图修正的对比度增强方法进行处理;最后,融合各重叠子块的处理结果得到最终的增强图像。实验结果表明,该算法具有噪声鲁棒性、可控制增强等级、可调节动态范围和局部对比度较强的优势,增强后的图像具有更自然的视觉效果。

Local Contrast Enhancement Algorithm Based on Histogram Modification Framework

According to the shortages of conventional histogram equalization algorithm,such as excessive contrast enhancement,noise amplification,lowly local contrast and so on,a local contrast enhancement algorithm based on histogram modification framework is presented.Firstly,using adaptively partially overlapped sub-block method the image is divided into a series of sub-blocks,sizes of which are adaptively adjusted according to the local characteristics of the image,then each sub-block is processed by using contrast enhancement algorithm base on histogram modification framework,finally the processed results of overlapped sub-blocks are fused to achieve the finally enhanced image.Experimental results show that the algorithm has the advantage of noise robustness,controllable the level of contrast enhancement,adjustable dynamic range and strong local contrast,and enhanced image has natural visual effect.