Improved Multi Scale DR Medical Image Enhancement Algorithm

Xiao Jing Sun; Ai Bin Chen

doi:10.4028/www.scientific.net/AMM.530-531.413

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 530-531Improved Multi Scale DR Medical Image Enhancement...

Improved Multi Scale DR Medical Image Enhancement Algorithm

Abstract:

The original DR image is decomposed into different scale and frequency of the band image sequence by using Laplace gaussian pyramid model methods. Using multi-scale image enhancement algorithm to enhance the High frequency component of the decomposed image, Then adjust the light of the low frequency part to make the reconstructed image illumination contrast more reasonable. The enhanced process according to different frequency layer image feature make the different gain weight for the different frequency layer image characteristics,so different frequency image layer realize respectively noise smoothing, dimensionality reduction and enhance the effect of edge character.The simulation experiments showed that this Image Processing Algorithm effect is very good.

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Periodical:

Applied Mechanics and Materials (Volumes 530-531)

Pages:

413-417

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.530-531.413

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Online since:

February 2014

Authors:

Xiao Jing Sun, Ai Bin Chen

Keywords:

Gauss Laplacian Multiscale, Image Processing, Laplacian Pyramid Decomposition

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References

[1] G. Eason, B. Noble, and I. N. Sneddon, On certain integrals of Lipschitz-Hankel type involving products of Bessel functions, Phil. Trans. Roy. Soc. London, vol. A247, p.529–551, April (1955).

DOI: 10.1098/rsta.1955.0005

Google Scholar

[2] J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, p.68–73.

Google Scholar

[3] I. S. Jacobs and C. P. Bean, Fine particles, thin films and exchange anisotropy, in Magnetism, vol. III, G. T. Rado and H. Suhl, Eds. New York: Academic, 1963, p.271–350.

Google Scholar

[4] K. Elissa, Title of paper if known, unpublished.

Google Scholar

[5] R. Nicole, Title of paper with only first word capitalized, J. Name Stand. Abbrev., in press.

Google Scholar

[6] Y. Yorozu, M. Hirano, K. Oka, and Y. Tagawa, Electron spectroscopy studies on magneto-optical media and plastic substrate interface, IEEE Transl. J. Magn. Japan, vol. 2, p.740.

DOI: 10.1109/tjmj.1987.4549593

Google Scholar

[7] M. Young, The Technical Writer's Handbook. Mill Valley, CA: University Science, (1989).

Google Scholar

[8] BURT,P. J，AND ADELSON，The Laplacian pyramid as a compact image code. IEEE Transactions on Communication 31, 4, 532–540.

DOI: 10.1109/tcom.1983.1095851

Google Scholar