摘要
目的是改进移动目标图像质量降质的问题。论文提出了一种基于粗集理论方法来提高移动目标图像的质量,该方法基于粗集定义了一个改进移动目标图像分割决策系统,提出了一种分割决策算法,并在空域采用3×3的滑动窗口,利用不可分辨关系分离出噪声图像中的噪声点,然后再利用基于粗集的近似精度检测边缘,对噪声点通过均值滤波去噪,对边缘进行增强。通过实验仿真表明,该方法在图像增强效果和时间的复杂性方面均优于传统图像增强方法,有效地改善了运动图像的退化现象,提高图像清晰度。
This article is intended to improve moving target image processing. A method of improvement quality of moving targets image is proposed based on rough set theory. Based on a 3 ×3 in the airspace of the sliding window defined, an algorithm for moving object segmentation is proposed by way of rough set decision method. Isolate noise points in a moving targets image are detected by idea of indiscernibility and noise is removed by mean filtering. Enhancement of image edges is realized on approximate accuracy in rough set. Experiment simulation showed that the method of moving object segmentation image enhancement proposed is superior to the traditional method in effectively improving moving image degradation and image clarity.
出处
《电子设计工程》
2016年第8期134-137,共4页
Electronic Design Engineering
基金
四川省技术厅应用基础研究专项课题(2011JY0051)
四川省白酒及生物技术重点实验室重点专项课题(NJ2010-01)
关键词
粗集理论
图像增强
直方图均衡
均值滤波
rough set theory
image enhancement
histogram equalization
median filtering
