Multi-source Color Transfer Based on Active Contours Exploration
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摘要: 传统的多源色彩迁移算法常常利用欧氏色彩距离来分割目标图像,由于色彩序列的模糊性与不确定性,使得这种分割极易出现色彩扭曲现象. 针对这个问题,提出一种基于主动轮廓探索的多源色彩迁移算法. 首先,为将目标图像的主体与背景分离开,利用一种主动进化的方法生成虚拟轮廓线,并采用能量函数评价机制迫使虚拟轮廓线逐渐逼近实际轮廓线. 其次,合理利用源图像与目标图像在RGB、Gray和LMS等不同色彩空间的表示、分割、转换,实现其在lαβ空间的多源色彩迁移. 最后,将在lαβ空间迁移得到的目标图像逆向操作后恢复为RGB显示. 单源与多源色彩迁移的对比、灰度化色彩通道的选择以及各色彩空间不同色彩通道间的干涉性对比等实验验证了所提算法的合理性与有效性.Abstract: Traditional multi-source color transfer algorithms often use Euclidean color distance to split the target image. However, the vagueness and uncertainty of the color sequence easily make the image segmentation prone to color distortion. In order to solve this problem, a multi-source color transfer based on active contours exploration algorithm is proposed. Firstly, for the purpose of splitting the object and background of the target image, an active evolutionary method is used to generate a virtual contour and an energy function evaluation mechanism is used to force the virtual contour gradually to approach the real contour. Secondly, representation, segmentation and transformation of the source and target images in different color spaces, i.e., RGB, Gray and LMS, are exploited to transfer color style from source images to the target image in the lαβ color space. Finally, the processed image in lαβ color space is operated backwards and is displayed in the RGB space. Simulation studies involving comparison of single-source and multi-source color transfers, selection for optimal color channel in Gray space, and analysis of mutual interference between color channels in different color spaces have verified the rationality and effectiveness of the proposed algorithm.
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Key words:
- Active contours exploration /
- image segmentation /
- color space /
- multi-source transfer /
- local transfer
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[1] Jiang Yi-Zhang, Deng Zhao-Hong, Wang Shi-Tong. Mamdani-Larsen type transfer learning fuzzy system. Acta Automatica Sinica, 2012, 38(9): 1393-1490(蒋亦樟, 邓赵红, 王士同. ML型迁移学习模糊系统. 自动化学报, 2012, 38(9): 1393-1490) [2] Reinhard E, Adhikhmin M, Gooch B, Shirley P. Color transfer between images. IEEE Computer Graphics and Applications, 2001, 21(5): 34-41 [3] Zhang M, Ren J Y. Driving and image enhancement for CCD sensing image system. In: Proceedings of the 3rd IEEE International Conference on Computer Science and Information Technology. Chengdu, China: IEEE, 2010. 216-221 [4] Wang W H, Xu Y F. Color transfer algorithm in medical images. In: Proceedings of the 2007 International Society for Optical Engineering. Wuhan, China: SPIE, 2007. 1-5 [5] Rouf M, Lau C, Heidrich W. Gradient domain color restoration of clipped highlights. In: Proceedings of the 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. Providence, USA: IEEE, 2012. 7-14 [6] Su Heng, Zhou Jie, Zhang Zhi-Hao. Survey of super-resolution image reconstruction methods. Acta Automatica Sinica, 2013, 39(8): 1202-1213(苏衡, 周杰, 张志浩. 超分辨率图像重建方法综述. 自动化学报, 2013, 39(8): 1202-1213) [7] Chen Bei-Jing, Sun Xing-Ming, Wang Ding-Cheng, Zhao Xiao-Ping. Color face recognition using quaternion representation of color image. Acta Automatica Sinica, 2012, 38(11): 1815-1823(陈北京, 孙星明, 王定成, 赵晓平. 基于彩色图像四元数表示的彩色人脸识别. 自动化学报, 2012, 38(11): 1815-1823) [8] Zeng K, Zhang R M, Lan X D, Pan Y, Lin L. Color style transfer by constraint locally linear embedding. In: Proceedings of the 18th IEEE International Conference on Image Processing. Brussels, Belgium: IEEE, 2011. 1121-1124 [9] Tai Y W, Jia J, Tang C K. Local color transfer via probabilistic segmentation by expectation-maximization. In: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego, CA, USA: IEEE, 2005. 747-754 [10] Xiang Y, Zou B J, Wang H, Li H, Xie Z. Multi-source color transfer for natural images. In: Proceedings of the 15th IEEE International Conference on Image Processing. San Diego, CA, USA: IEEE, 2008. 469-472 [11] Guo Y J, Li H, Zhang W, Xiang Y. Multi-source color transfer based on multi-labeled decision tree. In: Proceedings of the 9th International Conference for Young Computer Scientists. Hunan, China: IEEE, 2008. 820-825 [12] Chan T F, Vese L A. Active contours without edges. IEEE Transactions on Image Processing, 2001, 10(2): 266-277 [13] Hasler D, Süsstrunk S. Measuring colourfulness in natural images. In: Proceedings of the 2003 International Society for Optical Engineering. Santa Clara, CA, USA: SPIE, 2003. 87 -95
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