A Novel Multi-focus Image Capture and Fusion System for Macro Photography - Advances in Image and Graphics Technologies - page 27

Table 2. Quantitative evaluation for the second data set

Standard deviation Information entropy Average gradient

47.6883 5.3884 0.0006481

47.9520 5.4691 0.0008176

49.2818 5.6032 0.0010000

6 Conclusion

In this paper, a novel multi-focus image capture and fusion system for macro photo-
graphy is proposed. The hardware component can capture multiple in-focus images
with high precision. The software component can align a sequence of multi-focus
images and fuse them. The proposed multi-focus fusion method is based on the Gaus-
sian and Laplacian pyramids with weight maps extension. In order to make the
evaluation of image quality more effective and more comprehensive, subjective and
objective evaluations are adopted. Experiments demonstrate that the proposed system
is flexible and efficient for macro photography capture and fusion.

References

1. Antonio, M.: Digital macro photography of cactus and succulent plants. Cactus and Succu-
lent Journal 85, 101-106 (2013)
2. Burt, P., Kolczynski, R.: Enhanced image capture through fusion. In: Proceedings of 4th
International Conference on Computer Vision, Berlin, pp. 173-182 (1993)
3. Wang, H., Jin, Z., Li, J.: Research and Development of Multiresolution Image Fusion.
Control Theory and Applications 21, 145-149 (2004)
4. Jin, H., Yang, X., Jiao, L.: Image Enhancement via Fusion Based on Laplacian Pyramid
Directional Filter Banks. In: Proceedings of International Conference on Image Analysis
and Recognition, Toronto, pp. 239-246 (2005)
5. Haghighat, M., Aghagolzadeh, A., Seyedarabi, H.: Multi-Focus Image Fusion for Visual
Sensor Networks in DCT Domain. Computers and Electrical Engineering 37, 789-797
(2011)
6. Haghighat, M., Aghagolzadeh, A., Seyedarabi, H.: Real-time fusion of multi-focus images
for visual sensor networks. In: Proceedings of 6th Iranian Machine Vision and Image
Processing, pp. 1-6. IEEE Press, New York (2010)
7. Pu, T., Ni, G.: Contrast-based image fusion using the discrete wavelet transform. Optical
Engineering 39, 2075-2082 (2000)
8. Wen, Y., Li, Y.: The Image Fusion Method Based on Wavelet Transform in Auto-analysis
of Pashm. Journal of Sichuan University 37, 36-40 (2000)
9. Wang, H., Peng, J., Wu, W.: Remote Sensing Image Fusion Using Wavelet Packet Trans-
form. Journal of Image and Graphics 9, 922-937 (2002)
10. Wang, H., Jing, Z., Li, J.: Image fusion using non-separable wavelet frame. Chinese Optics
Letters 9, 523-552 (2003)
11. Long, G., Xiao, L., Chen, X.: Overview of the applications of Curvelet transform in image
processing. Journal of Computer Research and Development 2, 1331-1337 (2005)