Abstract
This paper deals with high-speed all-in-focus image reconstruction by merging multiple differently focused images. Previously, we proposed a method of generating an all-in-focus image from multi-focus imaging sequences based on spatial frequency analysis using three-dimensional FFT. In this paper, first, we combine the sequence into a two-dimensional image having fine quantization step size. Then, just by applying a certain convolution using two-dimensional FFT to the image, we realize high-speed reconstruction of all-in-focus images robustly. Some simulations utilizing synthetic images are shown and conditions achieving the good quality of reconstructed images are discussed. We also show experimental results of high-speed all-in-focus image reconstruction compared with those of the previous method by using real images.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Subbarao, M., Wei, T.-C., Surya, G.: Focused Image Recovery from Two Defocused Images Recorded with Different Camera Settings. IEEE Transactions on Image Processing 4(12), 1613–1627 (1995)
Sezan, M.I., et al.: Survey of Recent Developments in Digital Image Restoration. Optical Engineering 29(4), 393–404 (1990)
Burt, P.J., Kolczynski, R.J.: Enhanced Image Capture Through Fusion. In: Proc. 4th ICCV, pp. 173–182 (1993)
Pavel, M., Larimer, J., Ahumada, A.: Sensor Fusion for Synthetic Vision. In: AIAA Computing in Aerospace Conference, pp. 164–173 (1991)
Li, H., Manjunath, B.S., Mitra, S.K.: Multi-Sensor Image Fusion Using the Wavelet Transform. In: 1994 IEEE International Conference on Image Processing, vol. I, pp. 51–55 (1994)
Subbarao, M., Agarwal, N.B., Surya, G.: Application of Spatial-Domain Convolution/Deconvolution Transform for Determining Distance from Image Defocus. Computer Vision Laboratory, Stony Brook, Tech.Report 92.01.18 (1992)
Kubota, A., Kodama, K., Aizawa, K.: Registration and blur estimation methods for multiple differently focused images. In: 1999 IEEE International Conference on Image Processing, vol. II, pp. 447–451 (1999)
Aizawa, K., Kodama, K., Kubota, A.: Producing Object-Based Special Effects by Fusing Multiple Differently Focused Images. IEEE Transactions on Circuits and Systems for Video Technology 10(2), 323–330 (2000)
Kodama, K., Mo, H., Kubota, A.: All-in-Focus Image Generation by Merging Multiple Differently Focused Images in Three-Dimensional Frequency Domain. In: Ho, Y.-S., Kim, H.J. (eds.) PCM 2005. LNCS, vol. 3767, pp. 303–314. Springer, Heidelberg (2005)
Kodama, K., Mo, H., Kubota, A.: Free Viewpoint, Iris and Focus Image Generation by Using a Three-Dimensional Filtering based on Frequency Analysis of Blurs. In: 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. II, pp. 625–628 (2006)
Ohba, K., Ortega, J.C.P., Tanie, K., Tsuji, M., Yamada, S.: Microscopic vision system with all-in-focus and depth images. Machine Vision and Applications 15(2), 55–62 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kodama, K., Mo, H., Kubota, A. (2006). High-Speed All-in-Focus Image Reconstruction by Merging Multiple Differently Focused Images. In: Zhuang, Y., Yang, SQ., Rui, Y., He, Q. (eds) Advances in Multimedia Information Processing - PCM 2006. PCM 2006. Lecture Notes in Computer Science, vol 4261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11922162_103
Download citation
DOI: https://doi.org/10.1007/11922162_103
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-48766-1
Online ISBN: 978-3-540-48769-2
eBook Packages: Computer ScienceComputer Science (R0)