| 发明名称 |
FULL REFERENCE IMAGE QUALITY ASSESSMENT BASED ON CONVOLUTIONAL NEURAL NETWORK |
| 摘要 |
Embodiments generally relate to providing systems and methods for assessing image quality of a distorted image relative to a reference image. In one embodiment, the system comprises a convolutional neural network that accepts as an input the distorted image and the reference image, and provides as an output a metric of image quality. In another embodiment, the method comprises inputting the distorted image and the reference image to a convolutional neural network configured to process the distorted image and the reference image and provide as an output a metric of image quality. |
| 申请公布号 |
US2016358321(A1) |
申请公布日期 |
2016.12.08 |
| 申请号 |
US201514732518 |
申请日期 |
2015.06.05 |
| 申请人 |
Xu Xun;Ye Peng |
发明人 |
Xu Xun;Ye Peng |
| 分类号 |
G06T7/00;G06N3/08;G06K9/46;G06K9/62;G06T5/00;G06K9/66 |
主分类号 |
G06T7/00 |
| 代理机构 |
|
代理人 |
|
| 主权项 |
1. A system for assessing image quality of a distorted image relative to a reference image, the system comprising:
a convolutional neural network that accepts as an input the distorted image and the reference image, and provides as an output a metric of image quality. |
| 地址 |
Cupertino CA US |
