Image Fusion Based on Principle Component Analysis and Modified Gray-level Variance | IEEE Conference Publication | IEEE Xplore

Image Fusion Based on Principle Component Analysis and Modified Gray-level Variance


Abstract:

We consider the problem of image fusion in a multispectral vision system in which the quality criteria is the peak signal-to-noise ratio. The aim of the work is to develo...Show More

Abstract:

We consider the problem of image fusion in a multispectral vision system in which the quality criteria is the peak signal-to-noise ratio. The aim of the work is to develop an algorithm that allows to create a fused image that is comfortable for the subjective observer, even if the image in one of the channels of the multispectral vision system contains a powerful high-frequency noise component. The developed algorithm provides a gain in the peak signal-to-noise ratio by 3.4 and 4.6 times compared with the known fusion methods of the principal component analysis and calculation of the average respectively.
Date of Conference: 08-11 June 2020
Date Added to IEEE Xplore: 07 July 2020
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Conference Location: Budva, Montenegro

References

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