An Experimental Study of the Performance of Histogram Equalization for Image Enhancement
Keywords:
Histogram manipulation, Pixel, Remapping, Histogram equalization, Image enhancement, Contrast, BrightnessAbstract
Histogram equalization is one of the image enhancement techniques which has gained widespread popularity nowadays. It is a spatial domain histogram manipulation technique which mainly deals with brightness value remapping for recovering the lost contrast. In this paper an experimental study of the performance of histogram equalization technique on images has been done using matlab. Image multiplication and image division techniques are done on images in such a way that by adjusting the respective constant values, the contrast of the image is been made poor. To recover the lost contrast and the image back, the technique of histogram equalization is used and a comparison of the resultant image with original image and an analysis of the performance of this technique is done. The appearance of the images get enhanced by histogram equalization. The method uses the principle of stretching out the grey levels of the less contrast, darker image thereby producing a uniformly distributed flat histogram and a more contrast clear image.
References
S. Lau, “Global image enhancement using local information,” Electronics Letters, vol. 30, pp. 122–123, Jan. 1994.
Rafael C. Gonzalez, Richard E. Woods, “Digital Image Processing”, 2nd edition, Prentice Hall, 2002.
A. K. Jain, “Fundamentals of Digital Image Processing”. Englewood Cliffs, NJ: Prentice-Hall, 1991.
Yeong-Taeg Kim, “Contrast enhancement using brightness preserving bi-histogram equalization,” IEEE Trans. Consumer Electronics, vol. 43, no. 1, pp. 1-8, 1997.
] M. Abdullah-Al-Wadud, Md. Hasanul Kabir, M. Ali Akber Dewan, Oksam Chae, “A dynamic histogram equalization for image contrast enhancement”, IEEE Transactions. Consumer Electron., vol. 53, no. 2, pp. 593- 600, May 2007.
Chen SD and Ramli A, “Contrast Enhancement Using Recursive Mean-Separate Histogram Equalization For Scalable Brightness Preservation”, Consumer Electronics, IEEE Transactions on, (2003), vol. 49, no. 4. pp. 1301-1309.
Kim YT, “Contrast Enhancement Using Brightness Preserving Bi-Histogram Equalization”, Consumer Electronics, IEEE Transactions on, (1997), vol. 43, no.1, pp.1-8.
Wang C and Zhongfu Ye, “Brightness Preserving Histogram Equalization With Maximum Entropy: A Variational Perspective”, IEEE Trans. Consumer Electronics, Nov (2005) vol. 51, no. 4, pp. 1326- 1334.
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