融合小波变换和新形态学的含噪图像边缘检测  

Edge Detection for Noisy Image Based on Wavelet Transform and New Mathematical Morphology

作　　者：余小庆[1] 陈仁文[1] 唐杰[1] 许锦婷 YU Xiao-qing;CHEN Ren-wen;TANG Jie;XU Jin-ting(State Key Laboratory of Mechanics and Control of Mechanical Structures,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)

机构地区：[1]南京航空航天大学机械结构力学及控制国家重点实验室,南京210016

出　　处：《计算机科学》2018年第B11期194-197,共4页Computer Science

基　　金：国家自然科学基金项目(51675265);江苏高校优势学科建设工程基金资助

摘　　要：针对图像边缘检测中,滤除图像噪声并有效保留图像边缘信息这一研究,提出了一种融合小波变换模极大值法和新型改进的数学形态学的含噪图像边缘检测方法。首先介绍了基于小波变换模极大值的图像边缘检测算法;然后提出了一种新型改进的数学形态学检测算法;最后为了综合两种算法的优点,应用新的融合方式将两种方法的检测结果融合到一起,提出一种融合小波变换和新形态学的含噪图像边缘检测方法。实验结果表明,提出的融合检测算法相比于单独使用小波变换模极大值或数学形态学算法,能更有效地抑制噪声,提高边缘检测效果。In order to remove image noise and preserve image edge information in image edge detection,a edge detection method for noisy image based on wavelet transform modulus maxima and improved mathematical morphology edge detection was proposed.Firstly,the image edge detection algorithm based on wavelet transform modulus maxima was introduced.Then a new improved mathematical morphology was proposed.Finally,in order to synthesize the merits of the two algorithms,a new fusion method was used to fuse the results of the two methods together,and a novel edge detection method for noisy image based on wavelet transform and new morphology was proposed.The experimental results show that the proposed fusion detection algorithm can suppress the noise more effectively and improve the edge detection effect than using wavelet transform modulus maxima or new mathematical morphology alone.

关 键 词：模极大值 数学形态学 图像融合 边缘检测 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]