Colorization by Example
| dc.contributor.author | Irony, Revital | en_US |
| dc.contributor.author | Cohen-Or, Daniel | en_US |
| dc.contributor.author | Lischinski, Dani | en_US |
| dc.contributor.editor | Kavita Bala and Philip Dutre | en_US |
| dc.date.accessioned | 2014-01-27T14:48:47Z | |
| dc.date.available | 2014-01-27T14:48:47Z | |
| dc.date.issued | 2005 | en_US |
| dc.description.abstract | We present a new method for colorizing grayscale images by transferring color from a segmented example image. Rather than relying on a series of independent pixel-level decisions, we develop a new strategy that attempts to account for the higher-level context of each pixel. The colorizations generated by our approach exhibit a much higher degree of spatial consistency, compared to previous automatic color transfer methods [WAM02]. We also demonstrate that our method requires considerably less manual effort than previous user-assisted colorization methods [LLW04]. Given a grayscale image to colorize, we first determine for each pixel which example segment it should learn its color from. This is done automatically using a robust supervised classification scheme that analyzes the low-level feature space defined by small neighborhoods of pixels in the example image. Next, each pixel is assigned a color from the appropriate region using a neighborhood matching metric, combined with spatial filtering for improved spatial coherence. Each color assignment is associated with a confidence value, and pixels with a sufficiently high confidence level are provided as micro-scribbles to the optimization-based colorization algorithm of Levin et al. [LLW04], which produces the final complete colorization of the image. | en_US |
| dc.description.seriesinformation | Eurographics Symposium on Rendering (2005) | en_US |
| dc.identifier.isbn | 3-905673-23-1 | en_US |
| dc.identifier.issn | 1727-3463 | en_US |
| dc.identifier.uri | https://doi.org/10.2312/EGWR/EGSR05/201-210 | en_US |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Categories and Subject Descriptors (according to ACM CCS): 1.4.9 [Image Processing and Computer Vision]: Applications | en_US |
| dc.title | Colorization by Example | en_US |
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