Color transfer has been a hot research issue in the field of image processing and computer vision in recent years. The main purpose is to transfer the color of a target image to source image so that the source image has the same or similar color features with the target image. In practical applications for the color transfer of binocular stereoscopic images, the user may only need to transfer the color of the selected object while keeping the back-ground color unchanged. For this purpose, a color transfer method based on the selected object is proposed in this paper. In the method, by assigning the object of the image by user, the accurate object is segmented via graph cut, and the probability density curves of color distribution between the selected object and the target image are matched to accomplish the color transfer. In order to enhance the viewing experience provided for the user, a non-linear disparity optimization is performed after the color transfer operation. According to the histogram feature of disparity map, the disparity mapping function is calculated, and the target disparity is obtained to enhance the depth sensation of the selected object. The experimental results demonstrate that the combination of stereoscopic color transfer and disparity remapping effectively enhances the stereoscopic viewing experience.
Stereoscopic color transfer and disparity remapping based on selected object
First published at:Sep 12, 2019
 Faridul H S, Pouli T, Chamaret C, et al. A survey of color mapping and its applications[C]//Eurographics 2014 State of the Art Reports, 2014.
 Pouli T, Reinhard E. Progressive histogram reshaping for creative color transfer and tone reproduction[C]//Proceedings of the 8th International Symposium on Non-Photorealistic Animation and Rendering, 2010: 81–90.
 Reinhard E, Adhikhmin M, Gooch B, et al. Color transfer between images[J]. IEEE Computer Graphics and Applications, 2001, 21(5): 34–41.
 Pitie F, Kokaram A. The linear Monge-Kantorovitch linear colour mapping for example-based colour transfer[C]//Proceedings of the 4th European Conference on Visual Media Production, 2007.
 Evans L C. Partial differential equations and monge-kantorovich mass transfer[J]. Current Developments in Mathematics, 1997, 1997: 65–126.
 Hristova H, Le Meur O, Cozot R, et al. Style-aware robust color transfer[C]//Proceedings of the workshop on Computational Aesthetics, 2015.
 Abadpour A, Kasaei S. A fast and efficient fuzzy color transfer method[C]//Proceedings of the 4th IEEE International Symposium on Signal Processing and Information Technology, 2004: 491–494.
 Tai Y W, Jia J Y, Tang C K. Local color transfer via probabilistic segmentation by expectation-maximization[C]//Proceedings of 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005: 747–754.
 Hristova H, Le Meur O, Cozot R, et al. Transformation of the beta distribution for color transfer[C]//Proceedings of the 13th International Conference on Computer Graphics Theory and Applications, 2018: 112–121.
 Agrawal A, Raskar R. Gradient domain manipulation techniques in vision and graphics[C]//Proceedings of the 11th International Conference on Computer Vision, 2007.
 Shao F, Lin W S, Li Z T, et al. Toward simultaneous visual comfort and depth sensation optimization for stereoscopic 3-D experience[J]. IEEE Transactions on Cybernetics, 2017, 47(12): 4521–4533.
 Pascal F, Bombrun L, Tourneret J Y, et al. Parameter estimation for multivariate generalized Gaussian distributions[J]. IEEE Transactions on Signal Processing, 2013, 61(23): 5960–5971.
 Bombrun L, Pascal F, Tourneret J Y, et al. Performance of the maximum likelihood estimators for the parameters of multivariate generalized Gaussian distributions[C]//Proceedings of 2012 IEEE International Conference on Acoustics, Speech and Signal Processing, 2012: 3525–3528.
 Hristova H, Le Meur O, Cozot R, et al. Transformation of the multivariate generalized Gaussian distribution for image editing[J]. IEEE Transactions on Visualization and Computer Graphics, 2018, 24(10): 2813–2826.
 Li B F. The Research on image segmentation algorithms based on RGBD images[D]. Hefei: Hefei University of Technology, 2016.
李冰飞. 基于RGBD图像的图像分割算法研究[D]. 合肥: 合肥工业大学, 2016.
 Lang M, Hornung A, Wang O, et al. Nonlinear disparity mapping for stereoscopic 3D[J]. ACM Transactions on Graphics, 2010, 29(4): 75.
 Sun D Q, Roth S, Black M J. Secrets of optical flow estimation and their principles[C]//Proceedings of 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010: 2432–2439.
 Shamir A, Sorkine O. Visual media retargeting[C]//ACM SIGGRAPH ASIA 2009 Courses, 2009: 1–13.
 Pitié F, Kokaram A C, Dahyot R. Automated colour grading using colour distribution transfer[J]. Computer Vision and Image Understanding, 2007, 107(1–2): 123–137.
Pitie F, Kokaram A C, Dahyot R. N-dimensional probability density function transfer and its application to color transfer[C]//Proceedings of the 10th International Conference on Computer Vision, 2005: 1434–1439.
National Natural Science Foundation of China (61622109) and Natural Science Foundation of Ningbo (2017A610112)
Get Citation: Li Pengfei, Shao Feng. Stereoscopic color transfer and disparity remapping based on selected object[J]. Opto-Electronic Engineering, 2019, 46(9): 180446.