Name
Title | ||
|---|---|---|
Exploration Into Single Image Super-Resolution Via Self Similarity By Sparse Representation |
Abstract | ||
|---|---|---|
A novel method for single image super resolution without any training samples is presented in the paper By sparse representation the method attempts to recover at each pixel its best possible resolution Increase based on the self similarity of the Image patches across different scale and rotation transforms The experiments indicate that the proposed method can produce robust and competitive results. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1587/transinf.E93.D.3144 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | Field | DocType |
super resolution, self similarity, sparse coding | Computer vision,Pattern recognition,Computer science,Neural coding,Sparse approximation,Artificial intelligence,Pixel,Superresolution,Self-similarity | Journal |
Volume | Issue | ISSN |
E93D | 11 | 1745-1361 |
Citations | PageRank | References |
2 | 0.40 | 4 |
Authors | ||
4 | ||