Cell neural network hot region fusion method based on wavelet transform

The invention discloses a cell neural network hot region fusion method based on wavelet transform. The method comprises a step of calculating uncorrelated hot region images by using different contrastfunctions by using an ICA algorithm to obtain various forms of hot region images, a step of extracting low-frequency hot region images from the various forms of hot region images by using the wavelettransform, and a step of fusing the low-frequency hot region images based on a cellular neural network. In this way, defect features in the images are enhanced, the edges and contours of thermal images are enhanced, and thus the visualization effect of defect detection is better and more accurate. 本发明公开了种基于小波变换的细胞神经网络热区域融合方法，先利用ICA算法，采取不同的对比函数计算不相关的热区域图像，得到多种形式的热区域图像，然后利用小波变换分别多种形式的热区域图像中提取出低频热区域图像，最后基于细胞神经网络对低频热区域图像进行融合，这样增强了图像中的缺陷特征，而且还增强了热图像的边缘与轮廓，使得缺陷检测的可视化效果更好和准确。