Name
Abstract | ||
|---|---|---|
•We build three image datasets of local distortion, multiple distortion and single distortion.•Local and multiple distortion classifier will distinguish the locally distorted images from multiply distorted images.•Quality distortion type classifier will divide the distorted images into three types of image quality distortions.•Image quality assessment framework based on Multi-stage CNNs performs well on evaluating the quality of both locally and multiply distorted images. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.ipm.2019.102175 | Information Processing & Management |
Keywords | DocType | Volume |
Image quality assessment,Locally distorted image,Multiply distorted image,Convolutional neural network | Journal | 57 |
Issue | ISSN | Citations |
4 | 0306-4573 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuan Yuan | 1 | 0 | 1.01 |
| Hai Su | 2 | 2 | 0.71 |
| Liu Juhua | 3 | 8 | 4.91 |
| Guoqiang Zeng | 4 | 0 | 0.34 |