Weighted contrast enhancement based enhancement for remote sensing images

Ashok Kumar Dakarapu, V. Anuragh, G Sravan Kumar, N.S.Murthy Sarma

Abstract


This paper discuss a novel approach based on dominant brightness level analysis and adaptive intensity transformation to enhance the contrast for remote sensing images. In this approach  we first perform discrete wavelet (DWT) on the input images and then decompose the bLL sub band into low-, middle-, and high-intensity layers using the log-average luminance. After estimating the intensity transformation, the resulting enhanced image is obtained by using the inverse DWT. The proposed algorithm overcomes this problem using the adaptive intensity transfer function. The experimental results show that the proposed algorithm enhances the overall contrast and visibility of local details better than existing techniques.


Keywords


DWT, high intensity layers, bLL.

References


R. Gonzalez and R. Woods, Digital Image Processing, 3rd ed.Englewood Cliffs, NJ: Prentice-Hall, 2007.

Y. Kim, “Contrast enhancement using brightness preserving bi-histogram equalization,” IEEE Trans. Consum. Electron., vol. 43, no. 1, pp. 1–8, Feb. 1997.

Y. Wan, Q. Chen, and B. M. Zhang, “Image enhancement based on equal area dualistic sub-image histogram equalization method,” IEEE Trans. Consum. Electron., vol. 45, no. 1, pp. 68–75, Feb. 1999.

S. Chen and A. Ramli, “Contrast enhancement using recursive meanseparate histogram equalization for scalable brightness preservation,” IEEE Trans. Consum. Electron., vol. 49, no. 4, pp. 1301–1309, Nov. 2003.

T. Kim and J. Paik, “Adaptive contrast enhancement using gaincontrollable clipped histogram equalization,” IEEE Trans. Consum. Electron., vol. 54, no. 4, pp. 1803–1810, Nov. 2008.

H. Demirel, C. Ozcinar, and G. Anbarjafari, “Satellite image contrast enhancement using discrete wavelet transform and singular value decomposition,” IEEE Geosci. Reomte Sens. Lett., vol. 7, no. 2, pp. 3333–337,Apr. 2010.

H. Demirel, G. Anbarjafari, and M. Jahromi, “Image equalization based on singular value decomposition,” in Proc. 23rd IEEE Int. Symp. Comput. Inf. Sci., Istanbul, Turkey, Oct. 2008, pp. 1–5. [8] E. Reinhard, M. Stark, P. Shirley, and J. Ferwerda, Photographic tone reproduction for digital images,” in Proc. SIGGRAPH Annu. Conf. Comput.Graph., Jul. 2002, pp. 249–256.

L. Meylan and S. Susstrunk, “High dynamic range image rendering with a retinex-based adaptive filter,” IEEE Trans. Image Process., vol. 15, no. 9, pp. 2820–2830, Sep. 2006.

S. Chen and A. Beghdadi, “Nature rendering of color image based on retinex,” in Proc. IEEE Int. Conf. Image Process., Nov. 2009, pp. 1813–1816.

Eunsung Lee, Sangjin Kim, Wonseok Kang, Doochun Seo, and Joonki Paik “Contrast Enhancement Using Dominant Brightness Level Analysis and Adaptive Intensity Transformation for Remote Sensing Images” IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 1545-598X/$31.00 © 2012.


Full Text: PDF [FULL TEXT]

Refbacks

  • There are currently no refbacks.


Copyright © 2013, All rights reserved.| ijseat.com

Creative Commons License
International Journal of Science Engineering and Advance Technology is licensed under a Creative Commons Attribution 3.0 Unported License.Based on a work at IJSEat , Permissions beyond the scope of this license may be available at http://creativecommons.org/licenses/by/3.0/deed.en_GB.