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Enhancement of IR Images using Homomorphic Filtering in Fast Discrete Curvelet Transform (FDCT)

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 96 - Number 8
Year of Publication: 2014
Authors:
Athar A. Ein-shoka
Hamdy M. Kelash
Osama S. Faragallah
Hala S. El-sayed
10.5120/16816-6568

Athar A Ein-shoka, Hamdy M Kelash, Osama S Faragallah and Hala S El-sayed. Article: Enhancement of IR Images using Homomorphic Filtering in Fast Discrete Curvelet Transform (FDCT). International Journal of Computer Applications 96(8):22-25, June 2014. Full text available. BibTeX

@article{key:article,
	author = {Athar A. Ein-shoka and Hamdy M. Kelash and Osama S. Faragallah and Hala S. El-sayed},
	title = {Article: Enhancement of IR Images using Homomorphic Filtering in Fast Discrete Curvelet Transform (FDCT)},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {96},
	number = {8},
	pages = {22-25},
	month = {June},
	note = {Full text available}
}

Abstract

This paper presents an efficient model for enhancement of Infrared images. The proposed method is employing homomorphic filtering in the Fast Discrete Curvelet Transform (FDCT). It based on mixing the advantages of FDCT for representing curves and clarifying features on it with Homomorphic filtering which is an efficient method for enhancing the appearance of IR images. Also, we investigate the influence of FDCT coefficients on the Infrared images. The proposed method gives good results with respect to objective and subjective measurements when using only the first and last FDCT coefficients.

References

  • R. F. Soliman, M. Amin, and F. E. A. El-Samie. C22. 2012. Enhanced fusion for Infrared and visible images. Radio Sci. Conf. , no. April, pp. 335–343.
  • H. Liu, W. Chen, N. Xu, B. Li, and J. Z. J. Zheng. 2005. Infrared video enhancement system design and implementation using FPGA components. Int. Conf. Inf. Acquis. , no. july, pp. 281–284.
  • H. I. Ashiba, K. H. Awadallah, S. M. El-Halfawy, and F. E. A. El-Samie. 2008. Homomorphic enhancement of Infrared images using the additive wavelet transform. Electromagn. Res. C, vol. 1, pp. 123–130
  • K. Delac, M. Grgic, and T. Kos. 2006. Sub-Image Homomorphic Filtering Technique for Improving Facial Identification under Difficult Illumination Conditions. Int. Conf. Syst. Signals Image Process no. 1, pp. 95–98.
  • J. Li, C. Lu, F. Zhang, and W. Han. 2010. Contrast enhancement for images of raised characters on region of interest. World Congr. Intell. Control Autom. no. 2, pp. 6258–6261.
  • H. Etemadnia and M. Alsharif. 2003. Automatic Image Shadow Identification using LPF in Homomorphic Processing System. DICTA. pp. 10–12.
  • Y. Kumar. 2009. Techniques applied to preclinical images:fast discrete curvelet transform using wrapping techniques &wavelet transform.
  • A. Pure. 2013. A New Image Fusion Method based on Integration of Wavelet and Fast Discrete Curvelet Transform. vol. 69, no. 18, pp. 31–34.
  • E. Candes, L. Demanet, D. Donoho, and L. Ying. 2006. Fast discrete curvelet transforms. Multiscale Model. vol. 40698, pp. 1–44.
  • X. Qu, F. Zhang, and Y. Zhang. 2013. Feature-level Fusion of Dual-band Infrared Images Based on Gradient Pyramid Decomposition. Proc. 2nd Int. Conference. pp. 2279–2282.