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Image Fusion Based on Fractional Fourier Domain Phase and Amplitude

机译:基于分数阶傅里叶域相位和幅度的图像融合

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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.
机译:在图像上应用分数阶傅立叶变换(FRFT),相位和幅度部分具有不同的能力来反射源图像的光谱信息。通常,相位部分更为重要。利用这些特征,提出了一种新颖的图像融合算法,称为FRFT-相幅。首先,在源图像上应用FRFT,然后将幅度和相位信息分离。其次,使用最大绝对值融合规则融合FRFT域中的幅度部分。第三,对相位部分进行逆分数阶傅里叶变换(IFRFT),以获得重建的相位图像,并通过选择较大的像素值将它们融合在空间域中,然后在此融合的相位图像上处理FRFT。最后,在分数域中将融合相位部分与融合幅度部分进行组合,并对组合应用IFRFT以创建融合图像。实验表明,与基于小波变换和FRFT的方法相比,FRFT的相位幅度算法可以产生更好的融合效果。

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