Name
Abstract | ||
|---|---|---|
Objective measures of image quality generally operate by comparing pixels of a “degraded” image to those of the original. Relative to human observers, these measures are overly sensitive to resampling of texture regions (e.g., replacing one patch of grass with another). Here, we develop the first full-reference image quality model with explicit tolerance to texture resampling. Using a convolutiona... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TPAMI.2020.3045810 | IEEE Transactions on Pattern Analysis and Machine Intelligence |
Keywords | DocType | Volume |
Visualization,Image quality,Distortion measurement,Nonlinear distortion,Indexes,Databases,Convolution | Journal | 44 |
Issue | ISSN | Citations |
5 | 0162-8828 | 14 |
PageRank | References | Authors |
0.63 | 40 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Keyan Ding | 1 | 39 | 3.77 |
| Kede Ma | 2 | 773 | 27.93 |
| Shiqi Wang | 3 | 1281 | 120.37 |
| Eero P Simoncelli | 4 | 1485 | 168.07 |