Paper
4 March 2015 Image fusion based on fractional Fourier domain phase and amplitude
Longlong Li, Qiming Zou, Qian Huang, Yan Zhang, Fei Wang
Author Affiliations +
Proceedings Volume 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014); 94431B (2015) https://doi.org/10.1117/12.2179513
Event: Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2014, Beijing, China
Abstract
Applying fractional Fourier transform (FRFT) on an image, the phase and amplitude portion have different capability to reflect spectral information of the source image. Generally, the phase portion is of more importance. Taking advantage of these characters, a novel image fusion algorithm, named as FRFT-phase-amplitude, is proposed. Firstly, apply FRFT on source images, and then the amplitude and the phase information are separated. Secondly, fuse the amplitude portion in FRFT domain using the largest absolute value fusion rule. Thirdly, do inverse fractional Fourier transform (IFRFT) on phase portions to get reconstructed phase images, and fuse them in spatial domain by selecting the larger pixel value, then process FRFT on this fused phase image. Finally, combine fused phase portion with fused amplitude portion in fractional domain, and apply IFRFT on the combination to create the fused image. Experiments reveal that the FRFT-phase- amplitude algorithm can produce better fusion effects than methods based on wavelet transform and FRFT.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Longlong Li, Qiming Zou, Qian Huang, Yan Zhang, and Fei Wang "Image fusion based on fractional Fourier domain phase and amplitude", Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94431B (4 March 2015); https://doi.org/10.1117/12.2179513
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KEYWORDS
Image fusion

Image processing

Fractional fourier transform

Spatial frequencies

Fourier transforms

Image information entropy

Image quality

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