Fully automatic coloring of grayscale images

This paper introduces a methodology for adding color to grayscale images in a way that is completely automatic. Towards this goal, we build on a technique that was recently developed to transfer colors from a user-selected source image to a target grayscale image. More specifically, in order to eliminate the need for manual selection of the source image, we use content-based image retrieval methods to find suitable source images in an image database. To assess the merit of our methodology, we performed a survey where volunteers were asked to rate the plausibility of the colorings generated automatically for grayscale images. In most cases, automatically-colored images were rated either as totally plausible or as

[1]  Donald H. House,et al.  Image Recoloring Induced by Palette Color Associations , 2003, WSCG.

[2]  Shih-Fu Chang,et al.  Image Retrieval: Current Techniques, Promising Directions, and Open Issues , 1999, J. Vis. Commun. Image Represent..

[3]  Michael Ashikhmin,et al.  Fast Texture Transfer , 2003, IEEE Computer Graphics and Applications.

[4]  Sung Yong Shin,et al.  On pixel-based texture synthesis by non-parametric sampling , 2006, Comput. Graph..

[5]  Tao Wang,et al.  Constraint Based Region Matching for Image Retrieval , 2004, International Journal of Computer Vision.

[6]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Paul A. Viola,et al.  Boosting Image Retrieval , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[8]  Michael J. Swain,et al.  Color indexing , 1991, International Journal of Computer Vision.

[9]  Thierry Pun,et al.  Learning from User Behavior in Image Retrieval: Application of Market Basket Analysis , 2004, International Journal of Computer Vision.

[10]  Aleksandra Mojsilovic,et al.  Semantic-Friendly Indexing and Quering of Images Based on the Extraction of the Objective Semantic Cues , 2004, International Journal of Computer Vision.

[11]  Nuria Oliver,et al.  Curve Analogies , 2002, Rendering Techniques.

[12]  Gary R. Edgerton.  “The Germans Wore Gray, You Wore Blue”: Frank Capra, Casablanca, and the Colorization Controversy of the 1980s , 2000 .

[13]  David Salesin,et al.  Image Analogies , 2001, SIGGRAPH.

[14]  Abby Goodrum,et al.  Image Information Retrieval: An Overview of Current Research , 2000, Informing Sci. Int. J. an Emerg. Transdiscipl..

[15]  Cordelia Schmid,et al.  Weakly Supervised Learning of Visual Models and Its Application to Content-Based Retrieval , 2004, International Journal of Computer Vision.

[16]  Alex Pentland,et al.  Photobook: Content-based manipulation of image databases , 1996, International Journal of Computer Vision.

[17]  Klaus Mueller,et al.  Transferring color to greyscale images , 2002, ACM Trans. Graph..

[18]  Michael Gleicher,et al.  Retargetting motion to new characters , 1998, SIGGRAPH.

[19]  Alexei A. Efros,et al.  Image quilting for texture synthesis and transfer , 2001, SIGGRAPH.

[20]  Jing Huang,et al.  Image indexing using color correlograms , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[21]  D. Ruderman,et al.  Statistics of cone responses to natural images: implications for visual coding , 1998 .

[22]  Jitendra Malik,et al.  Color- and texture-based image segmentation using EM and its application to content-based image retrieval , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[23]  Paul E. Debevec,et al.  Acquiring the reflectance field of a human face , 2000, SIGGRAPH.

[24]  Erik Reinhard,et al.  Color Transfer between Images , 2001, IEEE Computer Graphics and Applications.

[25]  Yueting Zhuang,et al.  Towards Data-Adaptive and User-Adaptive Image Retrieval by Peer Indexing , 2004, International Journal of Computer Vision.