Name
Title | ||
|---|---|---|
Improved hybrid demosaicing and color super-resolution implementation using quasi-Newton algorithms |
Abstract | ||
|---|---|---|
Super-resolution algorithms can be used to reconstruct a high-resolution high-quality image from a set of low-quality images. A novel hybrid demosaicing and color super-resolution approach proposed by Farsiu, Elad, and Milanfar relies on the minimization of a nonconvex multiterm objective function using a rudimentary fixed step-size steepest-descent approach. In this paper, we show that improved performance can be achieved by implementing this approach in terms of powerful quasi-Newton algorithms. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CCECE.2009.5090241 | St. John's, NL |
Keywords | Field | DocType |
concave programming,image colour analysis,image reconstruction,image resolution,minimisation,color super-resolution implementation,hybrid demosaicing,image reconstruction,image resolution,nonconvex multiterm objective function minimization,quasiNewton algorithms,rudimentary fixed step-size steepest-descent approach,Image processing,demosaicing,quasi-Newton algorithms,super-resolution | Iterative reconstruction,Computer vision,Colors of noise,Computer science,Algorithm,Filter (signal processing),Image processing,Demosaicing,Minification,Artificial intelligence,Pixel,Image resolution | Conference |
ISSN | ISBN | Citations |
0840-7789 E-ISBN : 978-1-4244-3508-1 | 978-1-4244-3508-1 | 0 |
PageRank | References | Authors |
0.34 | 5 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Diego A. Sorrentino | 1 | 0 | 0.34 |
| A. Antoniou | 2 | 267 | 30.79 |