具有紧支撑正交非张量积小波的图像融合

提出了基于一种新的小波——具有紧支撑、正交性、伸缩矩阵为^2 0 ^0 2]的非张量积小波的图像融合方法。首先根据非张量积小波理论，利用Daubechies构造的单变量滤波器构造出基于四通道的不可分的小波滤波器组，用此滤波器组对参加融合的图像进行分解，然后对低频部分采用取均值、高频部分采用系数绝对值取大的融合算法对分解子图进行融合，最后重构。并采用熵、交叉熵、互信息、均方根误差和峰值信噪比等指标对该方法进行了客观评价。对可见光图像与红外图像、远红外图像与近红外图像、遥感图像、多聚焦图像和其它多类图像的融合实验结果证明本方法有较好的融合效果，其融合性能与采用同样融合算法的张量积db2小波的融合方法的融合性能相当。

Image Fusion Based on Non-Separable Orthogonal Compact Supported Wavelet

Image fusion method based on non-separable orthogonal compact supported wavelet is presented. First a non-separable wavelet 4-channels filter bank using the theory of non-separable wavelets is constructed. The images involing the fusion are decomposed by the filter bank. We use the fusion algorithm as follow: for low-frequency part, the average value is selected; for the three high-frequency parts of each level, the maximum of the absolute value of the pixel is selected, then the new image is reconstructed. The method's performance is evaluated by using the entropy, cross-entropy, mutual information, error of mean square root and peak signal to noise ratio. The experimental results show that it has good effect for the fusion of visible image and infrared image, far infrared image and near infrared image, remote sensing images, multi-focus images and many others class of images. The performance of the non-separable wavelet fusion method is close to the performance of the db2 separable wavelet fusion method.