A Generalised Unsharp Masking Algorithm Using Bilateral Filter

  ijett-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2013 by IJETT Journal
Volume-4 Issue-7                      
Year of Publication : 2013
Authors : Sunkari Sridhar , Dr.Shaik Meeravali


Sunkari Sridhar , Dr.Shaik Meeravali. "A Generalised Unsharp Masking Algorithm Using Bilateral Filter". International Journal of Engineering Trends and Technology (IJETT). V4(7):2896-2902 Jul 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group.


we propose a new generalized algorithm using the exploratory data model as unified frame work. Enhancement of contrast and sharpness of an image is required in many applications. In applications like medical radiography enhancing movie features and obser ving the planets it is necessary to enhance the contrast and sharpness of an image. Unsharp masking is good tool for sharpness enhancement; it is an anti blurring filter. By using unsharp masking algorithm for sharpness enhancement, the resultant image suf fering with two problems, first one is a hallo is appear around the edges of an image, and second one is rescaling process is needed for the resultant image. The aim of this paper is to enhance the contrast and sharpness of an image simultaneously and to s olve the problems. In the proposed algorithm, we can adjust the two parameters controlling the contrast and sharpness to produce the desired output. The proposed algorithm is designed to address issues:1) simultaneously enhancing contrast and sharpness by means of individual treatment of the model component and the residual,2)reducing the halo effect by means of an edge - preserving filter using Bilateral filter. Experimental results, which comparable to recent published results, shows that proposed algorithm is able to significantly improve the sharpness and contrast of an image. This makes the proposed algorithm practically useful.


[1] G. Ramponi, “A cubic unsharp masking technique for contrast enhancement,” Signal Process. , pp. 211 – 222, 1998.
[2] S. J. Ko and Y. H. Lee, “Center weighted median filters and their applications to image enhancement,” IEEE Trans. Circuits Syst. , vol. 38, no. 9, pp. 984 – 993, Sep. 1991.
[3] M. Fischer, J. L. Paredes, and G. R. Arce, “Weighted median image sharpeners for the world wide web,” IEEE Trans. Image Process. , vol. 11, no. 7, pp. 717 – 727, Jul. 2002.
[4] R. Lukac, B. Smolka, and K. N. Platan iotis, “Sharpening vector median filters,” Signal Process. , vol. 87, pp. 2085 – 2099, 2007.
[5] E. Peli, “Contrast in complex images,” J. Opt. Soc. Amer. , vol. 7, no. 10, pp. 2032 – 2040, 1990.
[6] S. Pizer, E. Amburn, J. Austin, R. Cromartie, A. Geselowitz, T . Greer, B. Romeny, J. Zimmerman, and K. Zuiderveld, “Adaptive histogram equalization and its variations,” Comput. Vis. Graph. Image Process. , vol. 39, no. 3, pp. 355 – 368, Sep. 1987.
[7] J. Stark, “Adaptive image contrast enhancement using generalizations of histogram equalization,” IEEE Trans. Image Process. , vol. 9, no. 5, pp. 889 – 896, May 2000.
[8] E. Land and J. McCann, “Lightness and retinex theory,” J. Opt. Soc. Amer. , vol. 61, no. 1, pp. 1 – 11, 1971.
[9] M. Elad, “Retinex by two bilateral filters,” in Proc. Scale Space , 2005, pp. 217 – 229.
[10] J. Zhang and S. Kamata, “Adaptive local contrast enhancement for the visualization of high dynamic range images,” in Proc. Int. Conf. Pattern Recognit. , 2008, pp. 1 – 4.
[11] F. Durand and J. Dorsey, “Fast bilat eral filtering for the display of highdynamic - range images,” in Proc. 29th Annu. Conf. Comput. Graph.Interactive Tech. , 2002, pp. 257 – 266.
[12] H. Shvaytser and S. Peleg, “Inversion of picture operators,” Pattern Recognit. Lett. , vol. 5, no. 1, pp. 49 – 61, 1987.
[13] L. Meylan and S. Süsstrunk, “High dynamic range image rendering using a retinex - based adaptive filter,” IEEE Trans. Image Process. , vol. 15, no. 9, pp. 2820 – 2830, Sep. 2006.
[14] D. Marr , Vision: A Computational Investigation into the Hu man Representation and Processing of Visual Information . San Francisco, CA: Freeman, 1982.
[15] D. G. Myers , Digital Signal Processing Efficient Convolution and Fourier Transform Technique . Upper Saddle River, NJ: Prentice - Hall, 1990.
[16] G. Deng and L. W. Cahill, “Image enhancement using the log - ratio approach,” in Proc. 28th Asilomar Conf. Signals, Syst. Comput.s , 1994, vol. 1, pp. 198 – 202.
[17] L. W. Cahill and G. Deng, “An overview of logarithm - based image processing techniques for biomedical applica tions,” in Proc. 13th Int.Conf. Digital Signal Process. , 1997, vol. 1, pp. 93 – 96.
[18] J. Pinoli, “A general comparative study of the multiplicative homomorphic log - ratio and logarithmic image processing approaches,” SignalProcess. , vol. 58, no. 1, pp. 11 – 45, 1997.
[19] Z. Farbman, R. Fattal, D. Lischinski, and R. Szeliski, “Edge - preserving decompositions for multi - scale tone and detail manipulation,” ACM Trans. Graph. , vol. 27, no. 3, pp. 67:1 – 67:10, 2008.
[20] J. W. Tukey , Exploratory Data Analysis . Rea ding, MA: Addison - Wesley, 1977.
[21] C. Tomasi and R. Manduchi, “Bilateral filtering for gray and color images,” in Proc. IEEE ICCV , Jan. 1998, pp. 839 – 846.
[22] G.Deng, “A Generalized Unmasking Algorithm”, IEEE Trans. Image Process. ,vol. 20, no. 5, pp. 1 249 - 1261,May 2011

Bilateral filter , edge - preserving filter, exploratory data model , Image Enhancement, Unsharp Masking .