在彩色图像的边缘检测中,如何去掉噪声的干扰及怎样更精确的检测出边缘是图像处理中一个非常重要的问题。本文提出了一种去除脉冲噪声干扰的彩色图像的边缘检测算法。首先,提出一种基于Alpha稳定分布模型的图像去噪算法。其次,利用改进的各向同性边缘检测器和快速熵阈值技术自动确定图像边界,并考虑了像素与其邻域像素的颜色距离进一步精确定位图像的边缘。实验证明,该算法能够克服脉冲噪声的影响,较精确的检测出彩色图像的边缘。

Because the color is a powerful indicator of a color image, so the color edge detection is essensial for color image segmentation. The speckle noise in a color image would severely degrade the image interpretation and increase the difficulty for image processing, such as for edge detection and feature extraction. Thus, it is important to reserve the edge characters effectively based on speckle noise removing. This paper proposes a novel algorithm for removing the speckle noise and detecting the color image edge. Firstly, a denoising algorithm is proposed based on the alpha stable distribution. Secondly, the color image edges are obtained automatically by combining an improved isotropic edge detector and a fast entropy threshold technique. According to the color distance between the pixel and its eight neighbor-pixels, the color image edges can be further accurately determined. The experiments demonstrate that the proposed method can successfully be used to obtain the color image edges.