基于增强指数加权均值比的SAR图像边缘检测算法

Edge Detection Algorithm for SAR Image Based on Enhanced ROEWA

研究学者们认为指数加权均值比(ROEWA)算子存在无法计算SAR图像边缘方向的缺陷。为此,进行了一些通过方向滤波器为ROEWA算法施加方向的工作。该文对ROEWA算法进行了深入的探讨和分析,通过对ROEWA算法卷积过程的进一步推导,获得了ROEWA算法像素级的观测公式。根据推导结果,提出了一种增强的ROEWA(EROEWA)边缘检测算法。首先,利用新的卷积策略将ROEWA的公式项解耦,获得了4个方向的指数加权均值;然后把SAR图像旋转45°,再利用新的卷积策略获取额外的4个方向的指数加权均值;最后,将8个方向的指数加权均值表示成8个矢量,通过矢量合成求出边缘强度和边缘方向。实验结果表明,提出的EROEWA算法不仅具有优秀的边缘方向计算能力,与ROEWA算法相比,边缘强度的提取也有显著的增强效果。

Researchers generally consider that Ratio Of Exponentially Weighted Averages （ROEWA） can not calculate the edge directions of SAR images. Therefore, some directional filters are used to add directions to ROEWA. In this paper, an Enhanced ROEWA （EROEWA） algorithm is proposed. Through the further derivation of the ROEWA algorithm convolution process, the pixel-level observation formula of ROEWA algorithm is obtained. First, a new convolution strategy is used to decouple the ROEWA formula to obtain exponentially weighted averages over the four directions. Second, the SAR images are rotated by 45° and exponentially weighted averages of the four additional directions are calculated. Finally, exponentially weighted averages of eight directions are expressed as eight vectors, and edge intensity and direction are solved by vector synthesis. Experimental results show that the EROEWA has a significant enhancement effect on the edge intensity and the direction.