A new image fusion performance metric based on visual information fidelity

Authors:
Yu Han;Yunze Cai;Yin Cao;Xiaoming Xu
Affiliations:
Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, PR China and Jiangsu Automation Research Institute, Lianyungang 222006, PR China;Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, PR China;Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, PR China;Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, PR China and University of Shanghai for Science and Technology, Shanghai Academy of Systems Science, Shanghai 200093, PR C ...
Venue:
Information Fusion
Year:
2013

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Abstract

Because subjective evaluation is not adequate for assessing work in an automatic system, using an objective image fusion performance metric is a common approach to evaluate the quality of different fusion schemes. In this paper, a multi-resolution image fusion metric using visual information fidelity (VIF) is presented to assess fusion performance objectively. This method has four stages: (1) Source and fused images are filtered and divided into blocks. (2) Visual information is evaluated with and without distortion information in each block. (3) The visual information fidelity for fusion (VIFF) of each sub-band is calculated. (4) The overall quality measure is determined by weighting the VIFF of each sub-band. In our experiment, the proposed fusion assessment method is compared with several existing fusion metrics using the subjective test dataset provided by Petrovic. We found that VIFF performs better in terms of both human perception matching and computational complexity.