Color correction with zone system for color image

Color correction is a part of image processing to solve the problem of color cast which a particular and unwanted color dominates an image. The Zone system is a visual ruler that allows photographers to determine optimal film exposure and development. It is divided the full tonal levels into eleven zones ranging from zone 0 (pure black) to zone X (pure white), with zone V representing subjective middle gray which is corresponding to 18% reflectance. In this paper, we described a global color correction method with Zone system to remove the color cast from the color images. The proposed method included color cast detection and color correction two steps. In color cast detection step, we divided the histograms of chrominance components (Cb and Cr) in YCbCr color space into eleven zones. The probable adjusted pixels of color cast will be detected after the Cb and Cr values of each pixel compared with zone V. In color correction step, the adjusted image will be obtained when the RGB channel individually times gains that are derived from the mean values and minimal values of the adjusted pixels that are the top 90% of the probable adjusted pixels. Experimental results exhibited the proposed method can correct the color from the color cast. Finally, the proposed method was compared with other color correction methods in subjective and objective evaluations.

[1]  Yung-Cheng Liu,et al.  Automatic white balance of digital still camera , 1995, Proceedings of International Conference on Consumer Electronics.

[2]  E H Land,et al.  An alternative technique for the computation of the designator in the retinex theory of color vision. , 1986, Proceedings of the National Academy of Sciences of the United States of America.

[3]  Chiou-Shann Fuh,et al.  Automatic White Balance for Digital Still Cameras , 2006, J. Inf. Sci. Eng..

[4]  Kwanghoon Sohn,et al.  Automatic illumination and color compensation using mean shift and sigma filter , 2009, IEEE Transactions on Consumer Electronics.

[5]  Zia-ur Rahman,et al.  Properties and performance of a center/surround retinex , 1997, IEEE Trans. Image Process..

[6]  Li Xinwu.  A New Color Correction Algorithm for Color Printed Image , 2011 .

[7]  Zia-ur Rahman,et al.  A multiscale retinex for bridging the gap between color images and the human observation of scenes , 1997, IEEE Trans. Image Process..

[8]  Gaurav Sharma.  Digital Color Imaging Handbook , 2002 .

[9]  Li xinwu.  A New Color Correction Model for based on BP Neural Network , 2011 .

[10]  Oscar C. Au,et al.  Automatic white balancing using standard deviation of RGB components , 2004, 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512).

[11]  Jing Wang,et al.  Robust automatic white balance algorithm using gray color points in images , 2006, IEEE Transactions on Consumer Electronics.

[12]  E. Land,et al.  Lightness and retinex theory. , 1971, Journal of the Optical Society of America.

[13]  L. Blake.  THE NEGATIVE , 2020, A Silvan Tomkins Handbook.

[14]  Raimondo Schettini,et al.  Color balancing of digital photos using simple image statistics , 2004, Pattern Recognit..