Feature-Based Image Fusion Quality Metrics

被引:0
|
作者
Hossny, Moharnrned [1 ]
Nahavandi, Saeid [1 ]
Crieghton, Doug [1 ]
机构
[1] Deakin Univ, Intelligent Syst Res Lab, Geelong, Vic 3217, Australia
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Image fusion quality metrics have evolved from image processing quality metrics. They measure the quality of fused images by estimating how much localized information has been transferred from the source images into the fused image. However, this technique assumes that it is actually possible to fuse two images into one without any loss. In practice; some features must be sacrificed and relaxed in both source images. Relaxed features might be very important, like edges, gradients and texture elements. The importance of a certain feature: is application dependant. This paper presents a new method for image fusion quality assessment. It depends on estimating how much valuable information has not been transferred.
引用
收藏
页码:469 / 478
页数:10
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