A new image fusion performance metric based on visual information fidelity

被引：590
|
作者：
Han, Yu [1 ,2 ]
Cai, Yunze [1 ]
Cao, Yin [1 ]
Xu, Xiaoming [1 ,3 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
[2] Jiangsu Automat Res Inst, Lianyungang 222006, Peoples R China
[3] Shanghai Acad Syst Sci, Univ Shanghai Sci & Technol, Shanghai 200093, Peoples R China
来源：
INFORMATION FUSION | 2013年 / 14卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Image fusion assessment; Fused image quality; Visual information fidelity; Visual information fidelity for fusion; QUALITY ASSESSMENT;
D O I：
10.1016/j.inffus.2011.08.002
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码：127 / 135
页数：9
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