基于多级直方图形状分割的图像对比度增强技术

针对现有图像增强算法中存在过度增强和欠增强、边缘光晕效应、由于细节增强导致信噪比降低等问题,提出一种基于多级直方图形状分割的图像对比度增强技术。利用引导图像过滤器将图像背景和细节分离,避免边缘过度增强带来的光晕效应;利用多级直方图形状分割方法,将直方图中出现频率相近的强度值区域分割出来,实现图像背景的个体均衡化;采用自适应细节增强方法在增强细节的同时抑制均匀区域中噪声,保持图像的信噪比。实验结果表明,与其他算法相比,该增强方法的效果更优,能够有效避免图像增强中常见的不利问题,同时产生足够的整体增强效果。

IMAGE CONTRAST ENHANCEMENT TECHNOLOGY BASED ON MULTI-LEVEL HISTOGRAM SHAPE SEGMENTATION

Aimed at the problems of over-enhancement and under-enhancement,edge halo effects and reduction in signal-to-noise ratio due to detail enhancement in the existing image enhancement algorithms,an image contrast enhancement technique based on multi-level histogram shape segmentation is proposed.This method used a guided image filter to separate the background and details of the image to avoid the halo effect caused by excessive edge enhancement.It used a multi-level histogram shape segmentation method to segment the intensity value regions with similar frequencies in the histogram and realized the individual equalization of the background of the image.The method adopted the adaptive detail enhancement method to suppress the noise in the uniform area while enhancing the details and maintain the signal-to-noise ratio of the image.The experimental results show that compared with other algorithms,the proposed enhancement method is more effective,which can effectively avoid the common disadvantages in image enhancement and generate enough overall enhancement effect.