Image Edge Detection Based on the Grey Prediction Model and Discrete Wavelet Transform
A novel image edge detection algorithm is presented by combining grey prediction model and discrete wavelet transform.Firstly, data are preprocessed according to GM(1,1) modeling condition.In order to remove the noise in edge information image, which is gained by preprocessed image subtracting from prediction image.Template of 3x3 pixel blocks is selected as the first choice in ascending order to predict maximum pixel value with GM(1,1).According to the information of template pixels with no difference, information of neighborhood pixels is used for improving differences of 3×3 template pixels.Secondly, median filter is employed to eliminate the isolated point noise in edge information images.Finally, image edge information with two-dimensional discrete wavelet weighted coefficient is obtained.Simulation results show that the proposed algorithm has advantages such as precisely locating, abundant weak edge, and better anti-noise performance, comparing the classical edge detection operator methods.
image processing edge detection GM(1,1) model median filter discrete wavelet transform (DWT)
WANG Qiu-Ping WANG Tie-Peng ZHANG Ke
School of Sciences,Xian University of Technology Xian,China School of Business HoHai University Nanjing,China
国际会议
南京
英文
624-628
2011-09-15（万方平台首次上网日期，不代表论文的发表时间）