Name
Abstract | ||
|---|---|---|
We present a novel method for enhancing details in a digital photograph, inspired by the principle of art photography. In contrast to the previous methods that primarily rely on tone scaling, our technique provides a flexible tone transform model that consists of two operators: shifting and scaling. This model permits shifting of the tonal range in each image region to enable significant detail boosting regardless of the original tone. We optimize these shift and scale factors in our constrained optimization framework to achieve extreme detail enhancement across the image in a piecewise smooth fashion, as in art photography. The experimental results show that the proposed method brings out a significantly large amount of details even from an ordinary low-dynamic range image. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1111/cgf.12298 | Comput. Graph. Forum |
Field | DocType | Volume |
Computer vision,Computer graphics (images),Computer science,Photography,Boosting (machine learning),Artificial intelligence,Operator (computer programming),Scaling,Piecewise,Constrained optimization | Journal | 33 |
Issue | ISSN | Citations |
2 | 0167-7055 | 5 |
PageRank | References | Authors |
0.44 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Minjung Son | 1 | 46 | 3.30 |
| Yunjin Lee | 2 | 399 | 21.22 |
| Henry Kang | 3 | 454 | 17.87 |
| Seungyong Lee | 4 | 2130 | 157.29 |