Color transfer based remote sensing image fusion using non-separable wavelet frame transform
Pattern Recognition Letters
Guest editorial: Image fusion: Advances in the state of the art
Information Fusion
A Novel Wavelet Medical Image Fusion Method
MUE '07 Proceedings of the 2007 International Conference on Multimedia and Ubiquitous Engineering
Visual information processing in primate cone pathways. I. A model
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Biological image fusion using a NSCT based variable-weight method
Information Fusion
EURASIP Journal on Advances in Signal Processing - Special issue on theory and application of general linear image processing
Pixel-level image fusion with simultaneous orthogonal matching pursuit
Information Fusion
Computer Methods and Programs in Biomedicine
A medical image fusion method based on visual models
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
Human visual system inspired multi-modal medical image fusion framework
Expert Systems with Applications: An International Journal
Image matting for fusion of multi-focus images in dynamic scenes
Information Fusion
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Image fusion has become a widely used tool for increasing the interpretation quality of images in medical applications. The acquired data might exhibit either good functional characteristic (such as PET) or high spatial resolution (such as MRI). The MRI image shows the brain tissue anatomy and contains no functional information. The PET image indicates the brain function and has a low spatial resolution. Hence, the image fusion task is carried out to enhance the spatial resolution of the functional images by combining them with a high-resolution anatomic image. A perfect fusion process preserves the original functional characteristics and adds spatial characteristics to the image with no spatial distortion. The intensity-hue-saturation (IHS) algorithm and the retina-inspired model (RIM) fusion technique can preserve more spatial feature and more functional information content, respectively. The presented algorithm integrates the advantages of both IHS and RIM fusion methods to improve the functional and spatial information content. Visual and statistical analyses show that the proposed algorithm significantly improves the fusion quality in terms of: entropy, mutual information, discrepancy, and average gradient; compared to fusion methods including, IHS, Brovey, discrete wavelet transform (DWT), a-trous wavelet and RIM.