Image Fusion Algorithm for Industrial Endoscope Based on Wavelet Transform
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摘要: 针对工业内窥镜使用场所特殊而存在采集的图像效果不佳的问题，提出了一种基于多尺度小波变换和不同融合算子的图像融合算法。首先对源图像进行小波变换，然后对代表近似信息的低频系数采用简单的平均算法融合，对代表细节信息的高频系数采用基于区域方差的动态加权平均算法融合，最后对处理的低频和高频系数进行小波逆变换得到融合图像。实验结果表明，与其它几种算法比较，该算法得到的图像参数较好，提高了图像处理效果。Abstract: In view of problem of bad effect of image collected by industrial endoscope because of special application place, the paper proposed an image fusion algorithm based on multi-scale wavelet transform and different fusion operators. Firstly, it made wavelet transform for source image, then used simple average algorithm to fuse low frequency coefficients which represents approximate information and used dynamic weighting average algorithm based on local deviation to fuse high frequency coefficients which represent detail information. Finally, it made inverse wavelet transform of processed low and high frequency coefficients to get fused image. The experiment result showed that the algorithm improves image processing effect with better image parameters comparing with other algorithms.
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