基于最优离散滤波器的边缘检测算法

Edge detection algorithm based on the Optimal Discrete Filter

边缘检测已经成为图像理解和计算机视觉中的一个主要领域,其检测的质量直接影响后期理解的效果。寻找一种对噪声不敏感、定位精确、能有效区分真假边缘的方法,一直是研究的重点。从理论上来说,Canny算子是连续域最优的边缘检测算子,但在离散域中却并非最优,对于数字图像可能存在误差。为此,提出一套完整的离散域边缘检测算法。在最优滤波器理论基础上,推导出离散域的最优平滑算子,抑制了图像的分割错误、噪声和伪边缘的影响。实验表明,该算法能有效实现灰度图像的多尺度边缘检测,具有高的信噪比,更清楚和更符合计算机识别要求,是一个理想的边缘检测方法。

Edge detection has been an important domain in comprehension of image and computer vision, Its quality determines the result of subsequent analysis. Thus it＇s an important goal for people to find a kind of method that is insensitive to noise, precisely locates true edges and excludes false edges. In theory Canny operator is optimal in continuous domain for edge detection, but not optimal in discrete case, which may lead to inaccurate result. In order to solve the problem above, a good edge detection algorithm in discrete field is proposed. The smooth operator is inferred based on the Optimal Discrete Filter＇s theory, which can reduce the influence of noise, false edges and image error. The experimental result shows that the proposed method can achieve multi-scale edge detection and high SNR, satisfy the requirement for computer recognition. So it is a good edge detection method.