结合子层分割和自适应函数引导的规定化图像增强

Image Enhancement Combined Sub-Layer Segmentation with Histogram Specification Induced by Adaptive Function

为了更好地辨别低照度图像中的目标，提高图像的对比度并增强纹理细节信息，采用子层分割规定化算法对图像进行增强处理，提出一种结合子层分割和自适应函数引导的规定化图像增强算法。首先根据原始图像直方图的特点对直方图进行子层分割，之后通过对分割后的子层进行灰度区间拉伸来提高图像的亮度，以增强图像的对比度；为了增强图像中的细节信息，在每个子层求取自适应函数来对每个子层做规定化处理；最后对子层直方图合并，得到增强后图像。实验结果证明，经过增强后图像的灰度平均梯度值为原始图像的3～4倍，信息熵也明显增大；该算法在增强图像细节、提高图像的对比度上具有优越性。

In order to distinguish the target of the illumination image better 、increase the contract and enhance the weak information ,by using sub‐layer segmentation and histogram specification to enhance image , we propose the image enhancement combined sub‐layer segmentation with histogram specification induced by adaptive function algorithm .Firstly ,according to the features of the original image ,its histogram will be divided into sub‐layer .Then ,stretching gradation interval of the sub‐layer to increase the image brightness ,the image contrast can be enhanced . To enhance the image details better ,we use the required adaptation functions to do the histogram specification in each sub‐layer .Finally ,the sub‐layer histogram will be merged to get the enhanced image .Experimental results show that the gray mean gradient value of the enhanced image was 3‐4 times of the original image ,and entropy was increased obviously .The algorithm can enhance image detail and improve image contrast with superiority .