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CLC number: TP391.41

On-line Access: 2010-04-28

Received: 2009-06-08

Revision Accepted: 2009-08-11

Crosschecked: 2010-03-29

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Journal of Zhejiang University SCIENCE C 2010 Vol.11 No.5 P.365-374

http://doi.org/10.1631/jzus.C0910344


High quality multi-focus polychromatic composite image fusion algorithm based on filtering in frequency domain and synthesis in space domain


Author(s):  Lei Zhang, Peng Liu, Yu-ling Liu, Fei-hong Yu

Affiliation(s):  State Key Lab of Modern Optical Instrumentation, Department of Optical Engineering, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   feihong@zju.edu.cn

Key Words:  Multi-focus image, Polychromatic image, Image fusion, Fast Fourier transform (FFT)


Lei Zhang, Peng Liu, Yu-ling Liu, Fei-hong Yu. High quality multi-focus polychromatic composite image fusion algorithm based on filtering in frequency domain and synthesis in space domain[J]. Journal of Zhejiang University Science C, 2010, 11(5): 365-374.

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author="Lei Zhang, Peng Liu, Yu-ling Liu, Fei-hong Yu",
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doi="10.1631/jzus.C0910344"
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%T High quality multi-focus polychromatic composite image fusion algorithm based on filtering in frequency domain and synthesis in space domain
%A Lei Zhang
%A Peng Liu
%A Yu-ling Liu
%A Fei-hong Yu
%J Journal of Zhejiang University SCIENCE C
%V 11
%N 5
%P 365-374
%@ 1869-1951
%D 2010
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C0910344

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T1 - High quality multi-focus polychromatic composite image fusion algorithm based on filtering in frequency domain and synthesis in space domain
A1 - Lei Zhang
A1 - Peng Liu
A1 - Yu-ling Liu
A1 - Fei-hong Yu
J0 - Journal of Zhejiang University Science C
VL - 11
IS - 5
SP - 365
EP - 374
%@ 1869-1951
Y1 - 2010
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C0910344


Abstract: 
A novel multi-focus polychromatic image fusion algorithm based on filtering in the frequency domain using fast Fourier transform (FFT) and synthesis in the space domain (FFDSSD) is presented in this paper. First, the original multi-focus images are transformed into their frequency data by FFT for easy and accurate clarity determination. Then a Gaussian low-pass filter is used to filter the high frequency information corresponding to the image saliencies. After an inverse FFT, the filtered images are obtained. The deviation between the filtered images and the original ones, representing the clarity of the image, is used to select the pixels from the multi-focus images to reconstruct a completely focused image. These operations in space domain preserve the original information as much as possible and are relatively insensitive to misregistration scenarios with respect to transform domain methods. The polychromatic noise is well considered and successfully avoided while the information in different chromatic channels is preserved. A natural, nice-looking fused microscopic image for human visual evaluations is obtained in a dedicated experiment. The experimental results indicate that the proposed algorithm has a good performance in objective quality metrics and runtime efficiency.

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Reference

[1]Burt, P., Andelson, E.H., 1983. The Laplacian pyramid as a compact image code. IEEE Trans. Commun., 31(4):532-540.

[2]Burt, P., Hanna, K., Lolczynski, R., 1993. Enhanced Image Capture through Fusion. Proc. 4th Int. Conf. on Computer Vision, p.173-182.

[3]De, I., Chanda, B., 2006. A simple and efficient algorithm for multifocus image fusion using morphological wavelets. Signal Process., 86(5):924-936.

[4]Eskicioglu, A., Fisher, P., 1995. Image quality measures and their performance. IEEE Trans. Commun., 43(12):2959-2965.

[5]Forster, B., van de Ville, D., Berent, J., Sage, D., Unser, M., 2004. Complex wavelets for extended depth-of-field: a new method for the fusion of multichannel microscopy images. Microsc. Res. Techn., 65(1-2):33-42.

[6]Gabarda, S., Cristóbal, G., 2005. On the use of a joint spatial-frequency representation for the fusion of multi-focus images. Pattern Recogn. Lett., 26(16):2572-2578.

[7]Helmy, A.E., Sam, K., 2003. A computationally efficient algorithm for multifocus image reconstruction. SPIE, 5017:332-341.

[8]Huang, W., Jing, Z., 2007. Multi-focus image fusion using pulse coupled neural network. Pattern Recogn. Lett., 28(9):1123-1132.

[9]Li, H., Manjunath, B., Mitra, S., 1995. Multi-sensor image fusion using the wavelet transform. Graph. Models Image Process., 57(3):235-245.

[10]Li, S., James, T.K., Wang, Y., 2001. Combination of images with diverse focuses using the spatial frequency. Inf. Fus., 2(3):169-176.

[11]Liu, Q., Zhao, T., Zhang, W., Yu, F., 2008. Image restoration based on generalized minimal residual methods with antireflective boundary conditions in a wavefront coding system. Opt. Eng., 47(12):127005.

[12]Matsopoulos, G., Marshall, S., Brunt, J., 1994. Multiresolution morphological fusion of MR and CT images of the human brain. IEE Proc.-Vis. Image Signal Process., 141(3):137-142.

[13]Oliver, R., 1996. Pixel-Level Fusion of Image Sequences Using Wavelet Frames. Proc. 16th Leeds Applied Research Workshop, p.149-154.

[14]Pajares, G., Cruz, J., 2004. A wavelet-based image fusion tutorial. Pattern Recogn., 37(9):1855-1872.

[15]Rajagopalan, A.N., Chaudhuri, S., 1997. Space-variant approaches to recovery of depth from defocused images. Comput. Vis. Image Underst., 68(3):309-329.

[16]Sroubek, F., Gabarda, S., Redondo, R., Fischer, S., Cristobal, G., 2005. Multifocus fusion with oriented windows. SPIE, 5839:264-273.

[17]Toet, A., Valeton, J., van Ruyven, L., 1989. Merging thermal and visual images by a contrast pyramid. Opt. Eng., 28(7):789-792.

[18]Yang, X., Yang, W., Pei, J., 2000. Different Focus Points Images Fusion Based on Wavelet Decomposition. Proc. 3rd Int. Conf. on Information Fusion, MOD3/3-8.

[19]Zhao, H., Li, Q., Feng, H., 2008. Multi-focus color image fusion in the HIS space using the sum-modified-Laplacian and a coarse edge map. Image Vis. Comput., 26(9):1285-1295.

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