Machine Vision and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multisensor image fusion using the wavelet transform
Graphical Models and Image Processing
Image fusion based on median filters and SOFM neural networks: a three-step scheme
Signal Processing - Special section on information theoretic aspects of digital watermarking
Digital Image Processing
Towards cognitive image fusion
Information Fusion
MRI and PET image fusion by combining IHS and retina-inspired models
Information Fusion
Medical image fusion via an effective wavelet-based approach
EURASIP Journal on Advances in Signal Processing
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
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A new quantitative metric is proposed to objectively evaluate the quality of fused imagery. The measured value of the proposed metric is used as feedback to a fusion algorithm such that the image quality of the fused image can potentially be improved. This new metric, called the ratio of spatial frequency error (rSFe), is derived from the definition of a previous measure termed ''spatial frequency'' (SF) that reflects local intensity variation. In this work, (1) the concept of SF is first extended by adding two diagonal SFs, then, (2) a reference SF (SF"R) is computed from the input images, and finally, (3) the error SF (SF"E) (subtracting the fusion SF from the reference SF), or the ratio of SF error (rSFe=SF"E/SF"R), is used as a fusion quality metric. The rSFe (which can be positive or negative) indicates the direction of fusion error-over-fused (if rSFe0) or under-fused (if rSFe