基于感兴趣区域和小波变换的图像融合算法（英文）

Image fusion algorithm based on region of interest and wavelet transform

为了提高图像融合效率,保持良好的边缘支持度,以便更好完成图像重构,提出了基于小波变换的图像融合算法。利用小波变换对信号多方向特征提取的优势,将多维图像信号分析化繁为简,在融合规则制定中,权衡图像融合的清晰度和融合算法复杂度,对图像信号低频信号和高频信号分开处理,低频进行加权平均,而高频进行局部方差处理,最后进行小波逆变换得到重构图像。实验证明,该方法重构图像效果清晰,且信噪比高。

In order to improve the efficiency of image fusion and maintain good edge support so as to better complete image reconstruction, an image fusion algorithm based on wavelet transform was proposed. The advantages of multi-directional feature extraction of signals using wavelet transform could simplify the analysis of multi-dimensional image signals. In the formulation of fusion rules, the clarity of the image fusion and the complexity of the fusion algorithm are weighed, and the low-frequency signal and the high-frequency signal of the image signal are processed separately. Low-frequency weighted average, high-frequency local variance processing, and finally wavelet inverse transform to get the reconstructed image. Experimental results show that this method has a clear effect on reconstructing images and it has a high signal-to-noise ratio.