Abstract
High dynamic range image (HDR) is widely used since it is capable of capturing more fine information. However, problems remain in its display. A good rendering of HDR color images requires careful treatment of both the brightness and chromaticity information. In this work, we first prove that the global logarithmic mapping of the R, G, B channels may result in desaturation. We then propose an improved way for HDR image rendering. Specifically, by keeping the chromaticity fixated, we use a global transformation and the Retinex-based adaptive filter only in the brightness channel. We finally transfer them back to the RGB space after combining the new brightness and the original chromaticity together. Our model works well in keeping the chromaticity information. Global mapping only in the brightness channel is a good way to avoid desaturation. In addition, our model ensures a good independence between brightness and chromaticity. By applying our method on HDR images, the details in both dark areas and bright areas can be well displayed with better appearance in hue and saturation.
S. Gao and W. Han—Contribute equally to this work.
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References
Choi, D.H., Jang, I.H., Kim, M.H., Kim, N.C.: Color image enhancement using single-scale retinex based on an improved image formation model. In: Proceedings of the EUSIPCO (2008)
Devlin, K.: A review of tone reproduction techniques. Technical report, Computer Science, University of Bristol, CSTR-02-005 (2002)
Drago, F., Myszkowski, K., Annen, T., Chiba, N.: Adaptive logarithmic mapping for displaying high contrast scenes. Comput. Graph. Forum. 22, 419–426 (2003). Wiley Online Library
Fattal, R., Lischinski, D., Werman, M.: Gradient domain high dynamic range compression. ACM Trans. Graph. (TOG) 21, 249–256 (2002)
Fu, X., Sun, Y., LiWang, M., Huang, Y., Zhang, X.P., Ding, X.: A novel retinex based approach for image enhancement with illumination adjustment. In: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1190–1194. IEEE (2014)
Funt, B., McCann, J., Ciurea, F.: Retinex in matlab. J. Electron. Imag. 13(1), 48–57 (2004)
Gao, S., Han, W., Yang, K., Li, C., Li, Y.: Efficient color constancy with local surface reflectance statistics. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014, Part II. LNCS, vol. 8690, pp. 158–173. Springer, Heidelberg (2014)
Gao, S., Li, Y.: A retinal mechanism based color constancy model. In: Liu, C.-L., Zhang, C., Wang, L. (eds.) CCPR 2012. CCIS, vol. 321, pp. 422–429. Springer, Heidelberg (2012)
Gao, S., Yang, K., Li, C., Li, Y.: A color constancy model with double-opponency mechanisms. In: 2013 IEEE International Conference on Computer Vision (ICCV), pp. 929–936. IEEE (2013)
Gao, S., Yang, K., Li, C., Li, Y.: Color constancy using double-opponency. IEEE Trans. Pattern Anal. Mach. Intell. (2015) (in press). doi:10.1109/TPA-MI.2015.2396053
Hood, D.C., Finkelstein, M.A.: Sensitivity to light. In: Boff, K.R., Kaufman, L., Thomas, J.P. (eds.) Handbook of Perception and Human Performance. Sensory Processes and Perception, vol. 1. Wiley, New York (1986)
Horn, B.K.: Determining lightness from an image. Comput. Graph. Image Process. 3(4), 277–299 (1974)
Jobson, D.J., Rahman, Z.U., Woodell, G.A.: A multiscale retinex for bridging the gap between color images and the human observation of scenes. IEEE Trans. Image Process. 6(7), 965–976 (1997)
Kimmel, R., Elad, M., Shaked, D., Keshet, R., Sobel, I.: A variational framework for retinex. Int. J. Comput. Vis. 52(1), 7–23 (2003)
Land, E.H., McCann, J.: Lightness and retinex theory. JOSA 61(1), 1–11 (1971)
Meylan, L., Susstrunk, S.: High dynamic range image rendering with a retinex-based adaptive filter. IEEE Trans. Image Process. 15(9), 2820–2830 (2006)
Pattanaik, S.N., Ferwerda, J.A., Fairchild, M.D., Greenberg, D.P.: A multiscale model of adaptation and spatial vision for realistic image display. In: Proceedings of the 25th annual conference on Computer graphics and interactive techniques, pp. 287–298. ACM (1998)
Rahman, Z.U., Jobson, D.J., Woodell, G.A.: Retinex processing for automatic image enhancement. J. Electron. Imag. 13(1), 100–110 (2004)
Reinhard, E., Stark, M., Shirley, P., Ferwerda, J.: Photographic tone reproduction for digital images. ACM Trans. Graph. (TOG) 21, 267–276 (2002)
Webster, M.A.: Human colour perception and its adaptation. Netw. Comput. Neural Syst. 7(4), 587–634 (1996)
Yang, K., Gao, S., Li, C., Li, Y.: Efficient illuminant estimation for color constancy using grey pixels. In: 2015 IEEE Conference on CVPR, pp. 1–10 (2015)
Acknowledgments
This work was supported by the 973 Project under Grant 2013CB329401 and the NSFC under Grant 61375115, 91420105. The work was also supported by the 111 Project of China (B12027).
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Gao, S., Han, W., Ren, Y., Li, Y. (2015). High Dynamic Range Image Rendering with a Luminance-Chromaticity Independent Model. In: He, X., et al. Intelligence Science and Big Data Engineering. Image and Video Data Engineering. IScIDE 2015. Lecture Notes in Computer Science(), vol 9242. Springer, Cham. https://doi.org/10.1007/978-3-319-23989-7_23
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