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A THz Image Edge Detection Method Based on Wavelet and Neural Network

机译:基于小波和神经网络的THz图像边缘检测方法

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A THz Image edge detection approach based on wavelet and Neural Network is proposed in this paper. First, the source image is decomposed by wavelet, the edges in the low-frequency sub-image are detected using Neural Network method and the edges in the high-frequency sub-images are detected using wavelet transform method on the coarsest level of the wavelet decomposition, the two edge images are fused according to some fusion rules to obtain the edge image of this level, it then is projected to the next level. Afterwards the final edge image of L-1 level is got according to some fusion rule. This process is repeated until reaching the 0 level thus to get the final integrated and clear edge image. The experimental results show that our approach based on fusion technique is superior to Canny operator method and wavelet transform method alone.
机译:本文提出了一种基于小波和神经网络的THz图像边缘检测方法。首先,通过小波分解源图像,使用神经网络方法检测低频子图像中的边缘,并且使用小波变换方法在小波的粗级别上检测高频子图像中的边缘分解,根据一些融合规则融合两个边缘图像以获得该级别的边缘图像,然后将其投影到下一个级别。之后,根据一些融合规则,L-1级别的最终边缘图像。因此,重复该过程直到达到0级以获得最终集成和清晰的边缘图像。实验结果表明,我们基于融合技术的方法优于罐头操作方法和小波变换方法。

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