柔性矢量形态学梯度算子

Soft Vector Morphological Gradient Operators

经典的形态学梯度算子不能直接拓展到彩色图像处理中,现有的矢量形态学梯度算子对噪声较为敏感且性能较低。为解决该问题,提出了一种新的柔性矢量形态学梯度算子,并将其应用到彩色图像边缘检测中。新的形态学梯度算子利用柔性形态学原理有效地降低了噪声对彩色图像边缘的影响,从而提高了矢量形态学梯度算子的抗干扰能力。实验结果表明,新的柔性矢量形态学梯度算子在噪声条件下能获得较好的矢量梯度,对彩色图像的后续分割及目标识别具有重要的作用。

Since classical morphological gradient operator cannot be directly extended to color image processing, the existing vector morphological gradient operator is sensitive to noise and it has low performance. This paper proposes a new soft vector morphological gradient operator and applies it in the edge detection of color images in order to solve the problem. New morphological gradient operator takes the advantage of soft morphology theory, which effectively reduces the influence of noise on the edge, so as to improve the anti-interference ability of the vector morphological gradient operator. Experimental results show that compared with the existing vector morphological gradient operators, the new soft vector morphology gradient operators achieve better gradient vector in the case of noise, and plays an important role in the following steps of color image segmentation and recognition.