Name
Abstract | ||
|---|---|---|
We present efficient machine learning methods for color image compression which simultaneously learn bases for compact image representation as well as the color space. We show the benefits of representing color image patches as 2D matrices of size n 脳 3n rather than as 3D patches of size n 脳 n 脳 3. We also present a method to leverage greater representational power from a learned dictionary without increasing its size. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/DCC.2011.62 | DCC |
Keywords | Field | DocType |
compact image representation,color image compression,orthonormal bases,color image patch,greater representational power,color space,size n,learned dictionary,efficient machine,data compression,learning artificial intelligence,dictionaries,machine learning,sparse matrices,color | Computer vision,Color space,Pattern recognition,Color histogram,Computer science,Matrix (mathematics),Color image compression,Orthonormal basis,Artificial intelligence,Data compression,Sparse matrix,Color image | Conference |
ISSN | Citations | PageRank |
1068-0314 | 0 | 0.34 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Hou | 1 | 0 | 0.34 |
| karthik s gurumoorthy | 2 | 52 | 10.09 |
| Ajit Rajwade | 3 | 160 | 18.32 |