Color histogram equalization using probability smoothing

A novel color histogram equalization approach is proposed that not only takes into consideration the correlation between color components in the color space, but it is also enhanced by a multi-level smoothing technique adopted from the field of language modeling. In this way, the correlation between color components is taken into account and the problem of unseen values for a color component, either considered independently or in combination with others, is efficiently dealt with. The proposed method is conducted in the HSI color space for intensity (I) component and saturation (S) component given the I component. The quality of the visually appealing equalized images was confirmed by means of the entropy and the Kullback-Leibler divergence estimates between the resulted color histogram and the multivariate uniform probability density function.

[1]  Bruno O. Shubert,et al.  Random variables and stochastic processes , 1979 .

[2]  B. Kapralos,et al.  I An Introduction to Digital Image Processing , 2022 .

[3]  Wayne Nilback.  An introduction to digital image processing , 1985 .

[4]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[5]  Sanjit K. Mitra,et al.  A new algorithm based on saturation and desaturation in the xy chromaticity diagram for enhancement and re-rendition of color images , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[6]  Guillermo Sapiro,et al.  Color histogram equalization through mesh deformation , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[7]  Arthur R. Weeks,et al.  Histogram specification of 24-bit color images in the color difference (C-Y) color space , 1999, J. Electronic Imaging.

[8]  Arthur Robert Weeks,et al.  Histogram specification of 24-bit color images in the color difference (C-Y) color space , 1999, Electronic Imaging.

[9]  Hinrich Schütze,et al.  Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.

[10]  Ioannis Pitas,et al.  Multichannel techniques in color image enhancement and modeling , 1996, IEEE Trans. Image Process..

[11]  Robin N. Strickland,et al.  Digital Color Image Enhancement Based On The Saturation Component , 1987 .

[12]  Sven C. Martin,et al.  Statistical Language Modeling Using Leaving-One-Out , 1997 .

[13]  Guoping Qiu,et al.  Novel histogram processing for colour image enhancement , 2004, Third International Conference on Image and Graphics (ICIG'04).

[14]  Jeffrey J. Rodríguez,et al.  A multivariate contrast enhancement technique for multispectral images , 1995, IEEE Trans. Geosci. Remote. Sens..

[15]  P. A. Mlsna,et al.  A recursive technique for 3-D histogram enhancement of color images , 1996, Proceeding of Southwest Symposium on Image Analysis and Interpretation.

[16]  Qiang Zhang,et al.  3-D histogram modification of color images , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[17]  I. M. Bockstein.  Color equalization method and its application to color image processing , 1986 .

[18]  Panos Trahanias,et al.  Color image enhancement through 3-D histogram equalization , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol. III. Conference C: Image, Speech and Signal Analysis,.