Open Access Open Access  Restricted Access Subscription or Fee Access

An Efficient Enhancement Technique for Infrared Images

Neven Sadic, Sami A. El-dolil, Emad S. Hassan

Abstract


This paper presents an efficient technique for enhancement of infrared (IR) images. It modifies the local luminance mean of an IR image and controls the local contrast as a function of the local luminance mean of the image. The technique first separates an image into both its low-pass and high-pass filtered form components. The low-pass component then controls the amplitude of the high-pass component to increase the local contrast. The low-pass component is then subjected to a non-linearity to modify the local luminance mean of the image and is combined with the processed high-pass component. The performance of this technique when applied to IR images shows good enhancement compared with the other traditional enhancement techniques.


Keywords


Infrared Image Enhancement; Non-Linearity

Full Text:

PDF

References


A. Cohen and J. Kovacevec, “ Wavelets: The Mathematical Background,” Proceedings of the IEEE, vol. 84, no. 4, pp. 514- 522, April 1996

J. S. Lim, Two-Dimensional Signal and Image Processing. Prentice Hall Inc., 1990.

Z. H. Long, “Image Fusion Using Wavelet Transform,” in Proc. The Symposium on Geospatial Theory, Processing and Applications, 2002.

V. S. Petrovic and C. S. Xydeas, “ Gradient-Based Multiresolution Image Fusion,” IEEE Trans. Image Processing, vol. 13, no. 2, pp. 228-237, February 2004.

I. Daubechies, “Where Do Wavelets Come From?—A Personal Point of View,” Proceedings of the IEEE, vol. 84, no. 4, pp. 510- 513, April 1996.

B. Zitova and J. Flusser, “Image Registration Methods: A Survey,” Image and Vision Computing, vol. 21, pp. 977-1000, 2003.

M. Xia, and B. Liu, “Image Registration by Super Curves,” IEEE Trans. Image Processing , vol. 13, no. 5, pp.720-732, May 2004.

D. Robinson and P. Milanfar, “Fundamental Performance Limits in Image Registration,” vol. 13, no.9, pp. 1185-1199, September 2004.

W. K. Pratt, Digital Image Processing. John Wiley & Sons Inc., 1991.

H. Li, B. S. Manjunath and S. K. Mitra, “Multi-Sensor Image Fusion Using The Wavelet Transform,” in Proc. ICIP, pp. 51-55, 1994.

G. Piella and H. Heijmans, “Multiresolution Image Fusion Guided By A Multimodal Segmentation,” in Proc. ACIVS, pp. 1– 8, 2002.

J. H. Shin, J. H. Jung, J.K. Paik and M. A. Abidi, “Data Fusion-Based Spatio-Temporal Adaptive Interpolation For Low-Resolution Video,” in Proc. ICIP, 2001.

Tamer Prli and Jae S. Lim, "Adaptive Filtering for Image Enhancement", 1981 IEEE, pp. 1117-1120. .

T. T. Neo, "Fusion of Night Vision and Thermal Images', M.Sc. Thesis, Naval Postgraduate School, University of New South Wales, Australia, 2006.

S. Yin, L. Cao, Q. Tan, and G. Jin, "Infrared and Visible Image Fusion based on NSCT and Fuzzy Logic ", in Proc. of the IEEE Int. Conf. on Mechatronics and Automation, pp. 671-675, August 4-7, 2010.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.