基于Facet模型的闪光图像边缘检测

针对闪光图像的特点,对经典边缘检测算子进行了分析,发现存在检测出的边缘粗和对噪声的干扰比较敏感的缺点,提出了一种基于Facet模型的爆轰实验图像边缘检测算法。该方法吸取了其它同类方法的优点,引进了正交基简化了运算,用离散正交多项式对图像每个像素的邻域作最佳曲面拟合,在此基础上使用整体梯度算子寻求二阶方向导数的零交叉点,最终提取边缘点。结果表明:该方法检测出的边缘细,并且光滑连续,对图像噪声干扰有较强的抑制能力,对于孤立的边缘能够给出较精确的定位。

Edge detection method based on Facet model for flash X-ray radiographs

In terms of the features of flash X-ray radiographs, the typical edge detection algorithm in digital image processing can only provide thick edges and is noise susceptibile. Thus an edge detection method based on Facet model for detonation experiment images is proposed. This method absorbs the merits of its congeneric method and introduces orthogonal basis to simplify operation. It uses surface fitting methods to approximate locally the image intensity function, and then makes decisions regarding the edge locations using the partial derivatives of the fitted surface. The result shows that the obtained edges of the image are thin, smooth and continuous. The algorithm has a better immunity to the noise jamming of images, and can give accurate localization for isolated edges.