Name
Title | ||
|---|---|---|
Globally Variance-Constrained Sparse Representation and Its Application in Image Set Coding |
Abstract | ||
|---|---|---|
Sparse representation leads to an efficient way to approximately recover a signal by the linear composition of a few bases from a learnt dictionary based on which various successful applications have been achieved. However, in the scenario of data compression, its efficiency and popularity are hindered. It is because of the fact that encoding sparsely distributed coefficients may consume more bits... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TIP.2018.2823546 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
Image coding,Dictionaries,Channel coding,Machine learning,Entropy,Matching pursuit algorithms | Pattern recognition,Computer science,Neural coding,Sparse approximation,Coding (social sciences),Gaussian,Artificial intelligence,Data compression,Entropy (information theory),Optimization problem,Encoding (memory) | Journal |
Volume | Issue | ISSN |
27 | 8 | 1057-7149 |
Citations | PageRank | References |
1 | 0.35 | 48 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiang Zhang | 1 | 88 | 12.61 |
| Sun Jiarui | 2 | 1 | 0.35 |
| Siwei Ma | 3 | 2229 | 203.42 |
| Zhouchen Lin | 4 | 4805 | 203.69 |
| Jian Zhang | 5 | 304 | 26.09 |
| Shiqi Wang | 6 | 1281 | 120.37 |
| Wen Gao | 7 | 74 | 13.14 |