Feature detection from local energy
Pattern Recognition Letters
Multisensor image fusion using the wavelet transform
Graphical Models and Image Processing
Image Sequence Fusion Using a Shift-Invariant Wavelet Transform
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 3 - Volume 3
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
A quantitative evaluation of fixed-pattern noise reduction methods in imaging systems
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Multisensor video fusion based on spatial-temporal salience detection
Signal Processing
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Pixel-level image fusion has been investigated in various applications and a number of algorithms have been developed and proposed. However, few authors have addressed the problem of how to assess the performance of those algorithms and evaluate the resulting fused images objectively and quantitatively. In this study, two new fusion quality indexes are proposed and implemented through using the phase congruency measurement of the input images. Therefore, the feature-based measurements can provide a blind evaluation of the image fusion result, i.e. no reference image is needed. These metrics take the advantage of the phase congruency measurement which provides a dimensionless contrast- and brightness-invariant representation of image features. The fusion quality indexes are compared with recently developed blind evaluation metrics. The validity of the new metrics are identified by the test on the fusion results achieved by a number of multiresolution pixel-level fusion algorithms.