基于灰度值补偿的视频监测图像模糊细节增强方法
Fuzzy detail enhancement method of video monitoring image based on gray value compensation
刘世章 1赵丹 2林伟1
作者信息
- 1. 电子科技大学成都学院,成都 610000
- 2. 西南民族大学,成都 610041
- 折叠
摘要
针对在光照复杂变化环境中图像容易出现失真现象,导致视频监测细节模糊,直接影响到图像数据的准确性和有效性.为了提升模糊图像的质量,提出一种基于灰度值补偿的视频监测图像模糊细节增强方法.采用引导滤波法分别提取曝光和欠光图像的亮度分量值,求解亮度分量与图像分辨率间二维线性关系,按照图像线性关系失衡的最大、最小值,给出动态拉伸或压缩调整.在此基础上,划分图像区域,按照各个区域亮度分量大小与模糊集间的隶属度关系,建立模糊集域,计算属于模糊集域内像素点的灰度值,通过调节灰度值大小完成模糊细节增强.实验结果证明,所提方法能够降低光照复杂变化条件对图像的干扰,可高效、高质量地完成模糊细节增强,且图像增强后峰值信噪比高达36 dB,且结构相似度最接近1,说明研究方法的图像增强效果好,适用性更理想.
Abstract
In complex and changing lighting environments,images are prone to distortion,leading to blurring of video monitoring details and directly affecting the accuracy and effectiveness of image data.In order to improve the quality of blurred images,a method for enhancing blurry details in video monitoring images based on grayscale com-pensation is proposed.The guided filtering method is used to extract the brightness component values of exposed and under lit images,and the two-dimensional linear relationship between the brightness component and image resolution is solved.Dynamic stretching or compression adjustments are given based on the maximum and minimum values of the imbalance in the linear relationship of the image.On this basis,image regions are divided,and a fuzzy set domain is established based on the membership relationship between the brightness components of each region and the fuzzy set.The grayscale values of pixels belonging to the fuzzy set domain are calculated,and the enhancement of fuzzy details is achieved by adjusting the grayscale values.Experimental results show that the proposed method can reduce the inter-ference of complex lighting conditions on the image,and complete the fuzzy detail enhancement with high efficiency and high quality.The peak signal-to-noise ratio of image enhancement is as high as 36 dB,and the structural similar-ity is closest to 1,indicating that the image enhancement effect and applicability of the proposed method are better.
关键词
光照复杂变化/视频监测图像/模糊细节/图像分辨率/亮度分量Key words
complex changes in lighting/video monitoring images/blur details/image resolution/luminance component引用本文复制引用
基金项目
四川省科技计划(2019YJ0114)
国家社会科学基金(18FZW012)
出版年
2024
NETL
NSTL
万方数据