Structural Similarity Metrics for Quality Image Fusion Assessment: Algorithms

被引:6
|
作者
Pistonesi, Silvina [1 ,2 ]
Martinez, Jorge [1 ]
Mara Ojeda, Silvia [3 ]
Vallejos, Ronny [4 ]
机构
[1] Univ Nacl Sur, Dept Matemat, Bahia Blanca, Buenos Aires, Argentina
[2] Univ Tecnol Nacl, Fac Reg Bahia Blanca, Buenos Aires, DF, Argentina
[3] Univ Nacl Cordoba, Fac Matemat Astron & Fis, Cordoba, Argentina
[4] Univ Tecn Federico Santa Maria, Dept Matemat, Valparaiso, Chile
来源
IMAGE PROCESSING ON LINE | 2018年 / 8卷
关键词
image fusion; image quality metrics; structural similarity; non-reference quality measures;
D O I
10.5201/ipol.2018.196
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
The wide use of image fusion techniques in different fields such as medical diagnostics, digital camera vision, military and surveillance applications, among others, has motivated the development of various image quality fusion metrics, in order to evaluate them. In this paper, we study and implement the algorithms of non-reference image structural similarity based metrics for fusion assessment: Piella's metric, Cvejic's metric, Yang's metric, and Codispersion Fusion Quality metric. We conduct the comparative experiment of the selected image fusion metrics over four multiresolution image fusion algorithms, performed on different pairs of images used in different applications.
引用
收藏
页码:345 / 368
页数:24
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