A Review of various Global Contrast Enhancement Techniques for still Images using Histogram Modification Framework
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2013 by IJETT Journal|
|Year of Publication : 2013|
|Authors : V. Rajamani , P.Babu , S. Jaiganesh|
V. Rajamani , P.Babu , S. Jaiganesh. "A Review of various Global Contrast Enhancement Techniques for still Images using Histogram Modification Framework". International Journal of Engineering Trends and Technology (IJETT). V4(4):1045-1048 Apr 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group.
This paper presents the evaluation and comparison of some popular image contrast enhancement algorithms using Histogram modificat ion framework. Histogram based techniques is one of the important digital image processing techniques which can be used for image enhancement. Histogram based techniques is mainly based on equalizing the histogram of the image and increasing the dynamic ra nge corresponding to the image. Histogram equalization is widely used in different ways to perform contrast enhancement in images. As a result, such image creates side - effects such as washed out appearance and false contouring due to the significant change in brightness. To overcome this weakness, we proposed a new method based on Histogram modification framework that works well with still images, and it enhances the images without making any loss in image details.
 S. C. Pei, Y. C. Zeng, and C. H. Chang, “V irtual restoration of ancient Chinese paintings using color contrast enhancement and lacuna texture synthesis,” IEEE Trans actions on Image Processing, Vol. 13, pp. 416 – 429 , 2004.
[2 ] A. Torre, A. M. Peinado, J. C. Segura, J. L. Perez - Cordoba, M. C.Beni tez, and A. J. Rubio, “Histogram equalization of speech representation for robust speech recognition , ” IEEE Trans actions on speech Audio Processing, Vol. 13, pp. 355 – 366. , 2005
 S . D.Chen, and A. R. Ramli, “Contrast enhancement using recursive mean - separate histogram equalization for scalable brightness preservation” , IEEE Transactions on Consumer Electronics, Vol. 49, No. 4, pp.1301 - 1309 , 2003
 R. C. Gonzalez, “Digital Image Processin g”, 2nd Edition, Addison - Wesley, 1992
 K . Jain, “ Fundamentals of digital image processing, ” Englewood Cliffs, NJ, Prentice - Hall , 1989
 J.Y . Kim , L.S . Kim and S.H . Hwang, “ An advanced contrast enhancement usin g partially overlapped sub - block histogram equalization,” IEEE Tra nsactions on Circuits and Systems for Video Technology, Vol.11, pp. 475 – 484 , 2001
 Y . Wang , Q. Chen and B. Zhang, , “Image enhancement based on equal area dualistic sub - image histogram equalization method,” IEEE Tran sactions on Consumer Elect ron ics , Vol. 45, No. 1, pp. 68 – 75 , 1999
 S. D. Chen, and A. R. Ramli, “Minimum mean brightness error bi - histogram equalization in contrast enhancement,” IEEE Trans actions on . Consumer Electron ics , Vol . 49, No. 4, pp.1310 – 1319 , 2003
 C.C. Sun, S.J. Ruan, M.C. Shie, and T. W. Pai, “Dynamic contrast enhancement based on histogram specification,” IEEE Transactions on Consumer Electronics, Vol. 51, No. 4, pp. 1300 – 1305 , 2005
 Z. Y. Chen, B. R. Abidi, D. L. Page, “Gray - level gro uping (GLG): An automatic method for optimized image contrast enhancement — Part I: The method ” , IEEE Trans actions on Image Process ing, vol. 15, N o. 8, pp.2290 - 2302, 2006
 Q . Wang and R. K. Ward, “Fast image/video contrast enhancement based on weighted thresholded histogram equalization,” IEEE Transactions on Consumer Electronics, vol. 53, no. Vol. 53, No. 2, pp. 757 - 764 , 2007
 Y . T. Kim , “Contrast Enhancement using Brightness Preserving Bi H istogram Equalization ”, IEEE Transactions on Consumer Electronics , Volume 43, Issue 1. pp . 01 – 08 , 1997
 S. Agaian, B. Silver and K. Panetta, “Transform coefficient histogram based image enhancement algorithms using contrast entropy,” IEEE Trans a ctions on Image Process ing , vol. 16, N o. 3, pp. 741 – 758, 2007
 A. Polesel, G. Ramponi and V. Mathews, “Image enhancement via adaptive unsharp masking,” IEEE Transactions on Image Processing , vol. 9, N o. 3, pp. 505 – 510 , 2000
. Haidi Ibrahim a nd N.S.P. Kong, “Image sharpening using Sub - Regions Histogram Equalization”, IEEE Trans. Consumer Electron., Volume 55, Issue 2, pp : 891 - 895 , 2009
 M. Sundaram, K. Ramar, N. Arumugam and G.Prabin, “Histogram modified l ocal contrast enhancement for mammogram images”, Applied soft computing, Elsevier, Volume11, pp .5809 - 5816 ,201 1
Contrast enhancement, Histogram equalization, Dynamic histogram specification, Histogram modification, Global Contrast enhancement