A fusion edge detection method based on wavelet transform and differential

Zuoxian Fu, Caixia Deng, Yuanyan Tang
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引用次数: 5

Abstract

Comparing the two improved methods, which are improved Sobel operator and improved wavelet transform using the multi-scale morphological filtering, subjective visual have achieved better results. However there are advantages and disadvantages in objective evaluations. So this paper makes the gained edges image fusion with the two improved methods using the wavelet transform fusion technology. The experimental results show that the fused image has increased significantly in information entropy and the average gradient compared to the improved Sobel operator, and it also has improved the peak signal to noise ratio and the distortion degree compared to the improved wavelet edge detection method. The fused image can concentrate the advantages of the two improved methods together and make complementary advantages. Eventually, the good de-noising effect and complete edge are achieved.
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一种基于小波变换和差分的融合边缘检测方法
对比改进的Sobel算子和改进的多尺度形态滤波小波变换两种改进方法,主观视觉效果更好。然而,客观评价有优点和缺点。因此,本文利用小波变换融合技术,将两种改进方法得到的边缘图像进行融合。实验结果表明,与改进的Sobel算子相比,融合后的图像在信息熵和平均梯度上有了明显的提高,在峰值信噪比和失真程度上也比改进的小波边缘检测方法有了明显的提高。融合后的图像可以将两种改进方法的优点集中在一起,形成优势互补。最终得到了良好的去噪效果和完整的边缘。
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