基于各向异性高通滤波的图像边缘检测算法

Edge detection algorithm based on anisotropic high-pass filtering

图像在处理的过程中,总会受到噪声的污染。由于噪声和边缘都是图像的高频分量,在滤除噪声的同时,也破坏了图像的边缘。为了使所提取的图像边缘更加逼近被噪声污染的图像真实边缘且定位精确,提出结合各向异性高通滤波和多尺度积对图像进行边缘检测。首先采用具有各向异性的非下采样Contourlet变换(NSCT)对原始图像进行多尺度、多方向分解,并用多尺度积对变换结果的高频分量去噪,最后利用各向异性高通滤波器长轴与边缘方向之间的夹角确定图像边缘。实验结果表明,所提出的方法抗噪声能力强,计算复杂度低,所提取边缘清晰、光滑且定位精确。

Image is always polluted by noise in processing. Since noise and edge are high frequency, noise is suppressed while edge is corrupted. In order to capture more accurate and true edges in noisy im- age, an edge detection algorithm is proposed by means of combining Anisotropic High-pass Filtering with multi-scale product. Firstly, an original image is decomposed by Non-subsampled Contourlet Transform, which is multi-scale, multi-direction and anisotropy. Secondly, the multi-scale product is a- dopted in high frequency of transform in order to decrease noise. Finally, the relationship between anisotropic filter long axis and edge direction is introduced to locate image edges. The results of experiments show that the proposed method has strong de-noising ability, low computational cost and be able to ex- tract smooth and accurate edges.