A New Multi-focus Image Fusion Method Using Principal Component Analysis in Shearlet Domain

Author(s):  
Biswajit Biswas ◽  
Ritamshirsa Choudhuri ◽  
Kashi Nath Dey ◽  
Amlan Chakrabarti
2012 ◽  
Vol 500 ◽  
pp. 659-665
Author(s):  
Min Cao ◽  
Shan Shan Tan ◽  
Quan Fei Shen

After analysising the principle of nonsubsampled contourlet transform, the image fusion model based on HIS transform and nonsubsampled contourlet transform is proposed. By taking of ALOS image as an example, the image fusion of multi-spectral band and panchromatic band at the same time is carried out by different fusion methods such as the method combining HIS transform and nonsubsampled contourlet transform (NSCT), HIS transform fusion method, principal component analysis (PCA), Brovey and static wavelet transform (SWT). By calculating the quantitative evaluation indicators of the different fused image, it is conclued that the fusion effection of static wavelet transform fusion method and nonsubsampled contourlet transform fusion method is better than the common methods such as HIS transform, principal component analysis and Brovey. In particular, the image fusion effection of nonsubsampled contourlet transform method, which betterly maintains the image spectral information while improving image spatial resolution at the same time, is superior than the fusion evaluation of static wavelet transform fusion method.


Author(s):  
Alaa A. Abdullatif ◽  
Firas A. Abdullatif ◽  
Amna Al Safar

The multi-focus image fusion method can fuse more than one focused image to generate a single image with more accurate description. The purpose of image fusion is to generate one image by combining information from many source images of the same scene. In this paper, a multi-focus image fusion method is proposed with a hybrid pixel level obtained in the spatial and transform domains. The proposed method is implemented on multi-focus source images in YCbCr color space. As the first step two-level stationary wavelet transform was applied on the Y channel of two source images. The fused Y channel is implemented by using many fusion rule techniques. The Cb and Cr channels of the source images are fused using principal component analysis (PCA). The proposed method performance is evaluated in terms of PSNR, RMSE and SSIM. The results show that the fusion quality of the proposed algorithm is better than obtained by several other fusion methods, including SWT, PCA with RGB source images and PCA with YCbCr source images.


2021 ◽  
Vol 92 ◽  
pp. 107174
Author(s):  
Yang Zhou ◽  
Xiaomin Yang ◽  
Rongzhu Zhang ◽  
Kai Liu ◽  
Marco Anisetti ◽  
...  

2020 ◽  
Vol 176 ◽  
pp. 107681
Author(s):  
Di Gai ◽  
Xuanjing Shen ◽  
Haipeng Chen ◽  
Pengxiang Su

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