EFFICIENT CONTRAST ENHANCEMENT USING GAMMA CORRECTION WITH MULTILEVEL THRESHOLDING AND PROBABILITY BASED ENTROPY

In digital image enhancement, contrast enhancement plays an important role. The main objective of contrast enhancement is to correct the local contrast in different area of the image. So that the feature unseen in the dark or bright area is brought out and exposed to the human views. In this paper improve the brightness of the dimmed images and preservation of image feature via multilevel thresholding, gamma correction and probability based entropy. The proposed method preserves the feature of the image and brightness and also improves image quality.

[1]  Qian Chen,et al.  Image enhancement based on equal area dualistic sub-image histogram equalization method , 1999, IEEE Trans. Consumer Electron..

[2]  Shih-Chia Huang,et al.  Efficient contrast enhancement using adaptive gamma correction and cumulative intensity distribution , 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

[3]  Yeong-Taeg Kim,et al.  Contrast enhancement using brightness preserving bi-histogram equalization , 1997 .

[4]  Wilhelm Burger,et al.  Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

[5]  Ronald W. Schafer,et al.  Multilevel thresholding using edge matching , 1988, Comput. Vis. Graph. Image Process..

[6]  Min Gyo Chung,et al.  Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement , 2008, IEEE Transactions on Consumer Electronics.

[7]  J. Alex Stark,et al.  Adaptive image contrast enhancement using generalizations of histogram equalization , 2000, IEEE Trans. Image Process..

[8]  Chao Wang,et al.  Brightness preserving histogram equalization with maximum entropy: a variational perspective , 2005, IEEE Transactions on Consumer Electronics.

[9]  Rabab Kreidieh Ward,et al.  Fast Image/Video Contrast Enhancement Based on Weighted Thresholded Histogram Equalization , 2007, IEEE Transactions on Consumer Electronics.

[10]  David Menotti,et al.  Multi-Histogram Equalization Methods for Contrast Enhancement and Brightness Preserving , 2007, IEEE Transactions on Consumer Electronics.

[11]  Y. Y. Tan,et al.  Recursive sub-image histogram equalization applied to gray scale images , 2007, Pattern Recognit. Lett..

[12]  Turgay Çelik,et al.  Contextual and Variational Contrast Enhancement , 2011, IEEE Transactions on Image Processing.

[13]  Barry R. Masters,et al.  Digital Image Processing, Third Edition , 2009 .