Image composition with color harmonization

Image composition is a very important technique in computer generated imagery (CGI). Besides some factors such as contrast, texture, noise that affect the quality of the composition, color harmony between fore- and background is also an important issue that should be carefully dealt with. However, in the previous image composition techniques, the color harmony between fore- and background is seldom considered. In this paper, an optimization method is presented to deal with the color harmonization problem that used in image composition. A cost function is derived from the observation of the local smoothness of the hue values. And the image is harmonized by minimizing the cost function. A new matching function is presented to select the best matching harmonic schemes, and a new component based pre-harmonization strategy is also presented to preserve the hue distribution of the harmonized images. Our approach overcomes several shortcomings of the existed color harmonization methods. We validate the performance of the method and demonstrate its effectiveness in a variety of experiments.

[1]  Patrick Pérez,et al.  Poisson image editing , 2003, ACM Trans. Graph..

[2]  Jian Sun,et al.  Drag-and-drop pasting , 2006, SIGGRAPH 2006.

[3]  Noriaki Muranaka,et al.  Color design support system considering color harmony , 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

[4]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  Daniel Cohen-Or,et al.  Color harmonization , 2006, ACM Trans. Graph..

[6]  Zeev Farbman,et al.  Coordinates for instant image cloning , 2009, ACM Trans. Graph..

[7]  David Salesin,et al.  Interactive digital photomontage , 2004, ACM Trans. Graph..

[8]  Niloy J. Mitra,et al.  Color Harmonization for Videos , 2008, 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing.

[9]  Todor Georgiev.  Photoshop Healing Brush : a Tool for Seamless Cloning , 2004 .

[10]  Michael F. Cohen,et al.  Image and Video Matting: A Survey , 2007, Found. Trends Comput. Graph. Vis..

[11]  Micah K. Johnson,et al.  Multi-scale image harmonization , 2010, ACM Trans. Graph..

[12]  Eitan Grinspun,et al.  Sparse matrix solvers on the GPU: conjugate gradients and multigrid , 2003, SIGGRAPH Courses.

[13]  Narendra Ahuja,et al.  Seamless video editing , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[14]  Liqing Zhang,et al.  Color conceptualization , 2007, ACM Multimedia.

[15]  Dani Lischinski,et al.  A Closed-Form Solution to Natural Image Matting , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  Dani Lischinski,et al.  Colorization using optimization , 2004, ACM Trans. Graph..

[17]  Yair Weiss,et al.  Segmentation using eigenvectors: a unifying view , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.