摘要
根据图像和检测算子的特性,以相关性为准则,使用遗传算法对图像小波变换的尺度进行选择,从而构成一种自适应的高斯小波尺度空间.融合该空间下不同尺度检测的图像边缘,使得整幅图像的边缘细节丰富清晰,具有更好的抗噪性能.对测试图像使用Canny算法、单尺度、二进尺度和自适应尺度小波进行边缘检测,验证了该算法在去除噪声和准确定位方面的有效性.
Edge detection is one of most important fields in computer vision,and lots of algorithms have been proposed by former scholars.Based on properties of image and detector,and taking relevances as criterion,this paper proposes an algorithm which use genetic algorithm to select optimal wavelet transform scales to form an adaptive Gaussian wavelet scale space.By fusing image＇s edges detected at different scales in this scale space,image will be improved in edge details and noise immunity.Experiments show that this adaptive scale wavelet algorithm has advantage in terms of noise removing and corner points positioning over Canny algorithm,single-scale wavelet algorithm,binary scale wavelet algorithm or multi-scale wavelet a algorithm.
出处
《南京信息工程大学学报（自然科学版）》
CAS
2011年第3期259-264,共6页
Journal of Nanjing University of Information Science & Technology（Natural Science Edition）
基金
南京信息工程大学科研基金(2007-0063)
国家自然科学基金(20080144)
关键词
边缘检测
多尺度
自适应
遗传算法
edge detection
multi-scale
adaptation
genetic algorithm
