Research of the fusion methods of the multispectral optoelectronic systems images

Aleksandr S. Vasilev; Valery V. Korotaev

doi:10.1117/12.2184554

22 June 2015 Research of the fusion methods of the multispectral optoelectronic systems images

Aleksandr S. Vasilev, Valery V. Korotaev

Proceedings Volume 9530, Automated Visual Inspection and Machine Vision; 953007 (2015) https://doi.org/10.1117/12.2184554
Event: SPIE Optical Metrology, 2015, Munich, Germany

Abstract

This article is devoted to consideration of the issues relating to digital images fusion of the multispectral optoelectronic systems. The images fusion formation methods and methods are studied. Theoretical analysis of the methods was completed in the course of the work, mathematical simulation model of the multispectral optoelectronic systems was developed. Effect of various factors on the result of fusion was demonstrated on the basis of the said model investigation. The paper also considers and suggests the objective assessment methods of the fusion image quality. The paper describes the mostly widely used from the above: the averaging method, the masking technique fusion, the interlacing fusion, fusion of images Fourier spectrum. The quality of the resulting image was assessed on the basis of the calculation of the cross entropy, brightness dispersion and excess of the Fourier spectrum function. Based on the research findings we can state that the images obtained by the mask technique methods, by averaging and the Fourier spectrum fusion methods have the highest information entropy. The best quality feature, in terms of the brightness dispersion and excess of the Fourier spectrum function, was demonstrated by the averaging method. The method allows reducing noise components of an image on the account of smoothing of its local brightness variations smoothing thus the contrast is improved.

Citation Download Citation

Aleksandr S. Vasilev and Valery V. Korotaev "Research of the fusion methods of the multispectral optoelectronic systems images", Proc. SPIE 9530, Automated Visual Inspection and Machine Vision, 953007 (22 June 2015); https://doi.org/10.1117/12.2184554

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