Name
Abstract | ||
|---|---|---|
In this paper, two new image multi-color transfer algorithms for still images and image sequences are proposed. These methods can be used to capture the artistic ambience or \"mood\" of the source image and transfer that same color ambience to the target image. The performance and effectiveness of these new algorithms are demonstrated through simulations and comparisons to other state of the art methods, including Alla's, Reinhard's and Pitie's methods. These algorithms are straight-forward, automatic, and suitable for various practical recoloring applications, including coloring, color correction, animation and color restoration for imaging tools and consumer products. This work is also useful for fast implementation of special effects for the entertainment industry and reduces manual labor costs for these types of tasks. Another contribution of this paper is the introduction of a new color transfer quality measure. The new measure is highly consistent with human perception, even compared to other current color transfer quality measures such as Xiao's measure and Xiang's measure1. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TCE.2016.7613196 | IEEE Trans. Consumer Electronics |
Keywords | Field | DocType |
Image color analysis,Algorithm design and analysis,Current measurement,Transforms,Histograms,Image quality | Computer vision,Entertainment industry,k-means clustering,Histogram,Data visualization,Algorithm design,Computer science,Algorithm,Image quality,Color correction,Animation,Artificial intelligence | Journal |
Volume | Issue | ISSN |
62 | 3 | 0098-3063 |
Citations | PageRank | References |
1 | 0.37 | 26 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Karen Panetta | 1 | 540 | 40.40 |
| Long Bao | 2 | 208 | 10.52 |
| Sos S. Agaian | 3 | 744 | 83.01 |