Multisensor image fusion using the wavelet transform
Graphical Models and Image Processing
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Sensor and Data Fusion: A Tool for Information Assessment and Decision Making (SPIE Press Monograph Vol. PM138)
The contourlet transform: an efficient directional multiresolution image representation
IEEE Transactions on Image Processing
Fusing images with different focuses using support vector machines
IEEE Transactions on Neural Networks
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This paper presents a new image fusion algorithm by combining contourlet transform with Kernel Principle Component Analysis to enhance perception in case of night vision applications. Contourlet Transform improves visual perception preserving the edge and texture information as compared to wavelet transform, while Kernel Principle Component Analysis helps to develop effective fusion decision rule for selecting appropriate coefficients for fusion. Additionally, mutual information is used to adjust the contribution of each image in final fused image. Fusion Quality Index is used for image fusion quality evaluation. Experimental results show that the proposed algorithm performs considerably well as compared to previous wavelet and pyramid based fusion approaches.