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Proceedings Paper

Polarization image fusion method based on traditional wavelet decomposition and its improvement
Author(s): Gao Yang; Yang Zhou; Kuan Lu; Hong Chang
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Paper Abstract

Aiming at the problems of polarization imaging detection technology in image fusion, an improved image fusion method based on traditional wavelet decomposition is proposed. Firstly, the fusion method of wavelet function and wavelet decomposition is analyzed. Secondly, the problems in the fusion method are improved from wavelet base and filtering and denoising. In order to verify the effectiveness of the improved method, the real images is used for image fusion, and the fusion and improvement results are evaluated by using information entropy and edge definition. The results show that the improved image fusion method significantly improves the sharpness of the fused image, and the high frequency loss is suppressed to a certain extent.

Paper Details

Date Published: 31 January 2020
PDF: 6 pages
Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114273F (31 January 2020);
Show Author Affiliations
Gao Yang, Beijing Aerospace Institute for Metrology & Measurement Technology (China)
Yang Zhou, Beijing Aerospace Institute for Metrology & Measurement Technology (China)
Kuan Lu, Harbin Institute of Technology (China)
Hong Chang, Beijing Aerospace Institute for Metrology & Measurement Technology (China)


Published in SPIE Proceedings Vol. 11427:
Second Target Recognition and Artificial Intelligence Summit Forum
Tianran Wang; Tianyou Chai; Huitao Fan; Qifeng Yu, Editor(s)

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