A novel image fusion algorithm based on wavelet-based contourlet transform (WBCT) and principal component analysis (PCA) is proposed. The PCA method is adopted for the low-frequency components. Using the proposed algorithm to choose the greater of the active measures, the region consistency test is performed for the high-frequency components. Experiments show that the proposed method works better in preserving the edge and texture information than wavelet transform method and Laplacian pyramid (LP) method do in image fusion. Four indicators for the fusion image are given to compare the proposed method with other methods.
© 2008 Chinese Optics Letters
Qiguang Miao and Baoshu Wang, "A novel image fusion method using WBCT and PCA," Chin. Opt. Lett. 6, 104-107 (2008)