Recently Fractional Fourier transform (FrFT) has got a variety of applications in digital signal and image processing. This paper presents a novel hardware architecture for real-time computation of Discrete Fractional Fourier Transform (DFrFT), which can easily be extended to other fractional transforms. The proposed architecture has been verified on Xilinx FPGA(XC6VLX240T), which can run at a frequency up to 291MHz while with high accuracy.
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.
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