Toward domain transfer for no-reference quality prediction of asymmetrically distorted stereoscopic images
We have presented a no-reference quality prediction method for asymmetrically distorted stereoscopic images, which aims to transfer the information from source feature domain to its target quality domain using a label consistent K-singular value decomposition classification framework. To this end, w...
Saved in:
Main Authors: | Shao, Feng, Zhang, Zhuqing, Jiang, Qiuping, Lin, Weisi, Jiang, Gangyi |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/142241 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Unified no-reference quality assessment of singly and multiply distorted stereoscopic images
by: Jiang, Qiuping, et al.
Published: (2020) -
Optimizing multistage discriminative dictionaries for blind image quality assessment
by: Jiang, Qiuping, et al.
Published: (2020) -
BLIQUE-TMI : blind quality evaluator for tone-mapped images based on local and global feature analyses
by: Jiang, Qiuping, et al.
Published: (2020) -
Learning sparse representation for objective image retargeting quality assessment
by: Jiang, Qiuping, et al.
Published: (2020) -
No-reference view synthesis quality prediction for 3-D videos based on color-depth interactions
by: Shao, Feng, et al.
Published: (2020)