基于限峰分离模糊直方图均衡化的图像增强算法

On Image Enhancement Algorithm Based on Limited Peak Separation and Fuzzy Histogram Equalization

为了解决当前图像增强算法在增强图像对比度的同时不能很好保留图像亮度的不足,提出了基于限峰分离模糊直方图均衡化的图像增强算法.首先,定义模糊统计方法,完成模糊直方图计算,获得图像的模糊直方图;其次,设计模糊直方图的导数模型,计算直方图的分割阈值;然后,利用阈值将直方图分割为多个子直方图;再通过强度因子控制子直方图均衡化的上、下约束值;最后,在限定范围内对每个子直方图进行均衡化,使其在增强对比度的同时也能够保持图像的亮度.仿真实验表明:与当前图像增强算法相比,所提算法能兼顾平均亮度保持和对比度增强度,更好地保留图像的丰富结构信息和特征.

In order to solve the shortage of image enhancement algorithm on the brightness preserving and enhanced visual effects can not be considered simultaneously as well as over enhancing the contrast,proposed a Image Enhancement Algorithm Based on Limited Peak Separation and Fuzzy Histogram Equalization.Firstly,Fuzzy statistical method was defined to complete the calculation of fuzzy histogram,obtained the fuzzy histogram of image;secondly,designing the derivative equation of fuzzy histogram,calculating histogram segmentation threshold;Then,The histogram was divided into several sub histograms by using the threshold value;And then the upper and lower bounds of the sub histogram equalization were controlled by the intensity factor;At last,the equalization of each sub histogram is carried out in a limited range,at the same time to enhance the contrast of the image can be maintained at the same time.Simulation experiments show that:The proposed method can achieve the ideal effect in the average brightness and contrast enhancement,enhanced images retain a wealth of structural information and features.