Improved image fusion method based on NSCT and accelerated NMF

• Published in: Sensors (Basel, Switzerland) Vol. 12; no. 5; pp. 5872 - 5887
• Main Authors: Wang, Juan, Lai, Siyu, Li, Mingdong
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.05.2012; Molecular Diversity Preservation International (MDPI)
• Subjects: Algorithms; Computer simulation; Decomposition; Factorization; image fusion; Inverse; Low frequencies; neighborhood homogeneous measurement; Neighborhoods; non-subsampled contourlet transform; nonnegative matrix factorization; Sensors; Shape; Transforms; Wavelet transforms; China; non-subsampled contourlet transform; image fusion; nonnegative matrix factorization; neighborhood homogeneous measurement
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s120505872

In order to improve algorithm efficiency and performance, a technique for image fusion based on the Non-subsampled Contourlet Transform (NSCT) domain and an Accelerated Non-negative Matrix Factorization (ANMF)-based algorithm is proposed in this paper. Firstly, the registered source images are decomposed in multi-scale and multi-direction using the NSCT method. Then, the ANMF algorithm is executed on low-frequency sub-images to get the low-pass coefficients. The low frequency fused image can be generated faster in that the update rules for W and H are optimized and less iterations are needed. In addition, the Neighborhood Homogeneous Measurement (NHM) rule is performed on the high-frequency part to achieve the band-pass coefficients. Finally, the ultimate fused image is obtained by integrating all sub-images with the inverse NSCT. The simulated experiments prove that our method indeed promotes performance when compared to PCA, NSCT-based, NMF-based and weighted NMF-based algorithms.