一种基于清晰区域筛选的图像增强方法
Image Enhancement Method Based on Clear Region Screening
张谦谦 1马卫红1
作者信息
- 1. 西安工业大学光电工程学院,陕西 西安 710021
- 折叠
摘要
针对目前图像处理方法在待测物尺寸超出成像系统景深条件下图像部分区域模糊的问题,提出基于清晰区域筛选的图像增强方法.首先对成像系统使用步进截获的方法,完成同目标多清晰区域的图像组抓取.之后结合双边滤波和边缘提取算法弱化图像低清晰度区域,保留其强边缘特征,再进一步进行强边缘及区域衔接组合,解决模糊区域对边缘的误导问题.最后引用基于图像方差特征的高清晰度区域筛选算法筛出非边缘区域清晰图像,与强区域边缘图匹配,获得目标图像.实验结果表明,综合三个实验用例,与常用图像增强算法相比,所提算法处理后的图像的清晰区域变化幅度小,模糊区域得到有效加强.与直方图均衡化、自适应滤波、Retinex三种算法的结果相比,所提方法的信息熵、信噪比、结构相似度和清晰度平均提高了4.1%、21.3%、36%、9.53%,标准差平均降低了23.3%.
Abstract
To address the issue of image blurring when the object size exceeds the depth of the field for the imaging system,we propose an image enhancement method based on clear region screening.First,the imaging system employs step capture to obtain multiple images,each focusing on different clear areas of the same target.Second,a combination of bilateral filtering and edge extraction algorithms is employed to weaken low-definition regions of images while retaining strong edge features.The combination of strong edges and regions mitigates the misleading effects of blurred regions near edges.A high-resolution region screening algorithm based on image-variance features is then introduced to select clear images of non-edge regions and match them with strong region-edge maps to obtain the final target images.The experimental results show that,compared to conventional image-enhancement algorithms,the clear regions of the image obtained by the proposed method exhibit minimal change and the blurred regions are effectivly enhanced.Compared with the histogram equalization,adaptive filtering,and Retinex algorithms,the proposed algorithm increases the information entropy,signal-to-noise ratio,structural similarity,and sharpness by an average of 4.1%,21.3%,36.0%,and 9.53%,respectively,while decreases the standard error by 23.3%on average.
关键词
图像处理/图像增强/清晰区域筛选/模糊区域Key words
image processing/image enhancement/clear region screening/fuzzy region引用本文复制引用
出版年
2024
NETL
NSTL
万方数据