摘要
通过边缘图像增强处理,提高模糊图像的辨识能力和成像质量。针对边缘图像像素差异性较大,导致成像质量差的问题,提出一种基于模糊聚类算法的边缘图像增强技术。对图像进行小波降噪处理,提取降噪输出图像的灰度直方图特征信息参量,在仿射不变区域对特征量进行模糊聚类,采用C均值聚类算法实现灰度像素点的边缘聚敛和信息增强,进行图像的边缘轮廓特征提取。仿真结果表明,采用该方法进行图像增强处理,提高了输出图像的峰值信噪比,图像的辨识性能得到改善。
The enhancement for edge image can improve the identification ability and imaging quality of fuzzy image. Since edge image has large pixel difference, which may cause the poor imaging quality, an edge image enhancement technology based on fuzzy clustering algorithm is put forward. The wavelet denoising is carried out for the image to extract the gray histogram fea- ture information parameters of the denoised output image. The fuzzy clustering is conducted for the characteristic quantity in affine-invariant region. The C-means clustering algorithm is adopted to realize the edge convergence and information enhance- ment of the gray pixel points, and extract the edge contour feature of the image. The simulation results show that the method used for image enhancement can improve the peak signal-to-noise ratio of the output image and identification performance of the fuzzy image.
出处
《现代电子技术》
北大核心
2017年第24期103-105,共3页
Modern Electronics Technique
基金
国家自然科学基金项目(61462019)
韶关学院校级科研项目(SY2016KJ12)
关键词
模糊聚类
图像增强
边缘轮廓
特征提取
fuzzy clustering
image enhancement
edge contour
feature extraction
