Back to Search
Start Over
PRED: A Parallel Network for Handling Multiple Degradations via Single Model in Single Image Super-Resolution
- Source :
- ICIP
- Publication Year :
- 2019
- Publisher :
- IEEE, 2019.
-
Abstract
- Existing SISR (single image super-resolution) methods mostly assume that a low-resolution (LR) image is bicubicly down-sampled from its high-resolution (HR) counterpart, which inevitably give rise to poor performance when the degradation is out of assumption. To address this issue, we propose a framework PRED (parallel residual and encoder-decoder network) with an innovative training strategy to enhance the robustness to multiple degradations. Consequently, the network can handle spatially variant degradations, which significantly improves the practicability of the proposed method. Extensive experimental results on real LR images show that the proposed method can not only produce favorable results on multiple degradations, but also reconstruct visually plausible HR images.
- Subjects :
- Single model
Computer science
business.industry
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Pattern recognition
02 engineering and technology
Iterative reconstruction
010501 environmental sciences
01 natural sciences
Superresolution
Robustness (computer science)
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Artificial intelligence
Single image
business
Image resolution
0105 earth and related environmental sciences
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2019 IEEE International Conference on Image Processing (ICIP)
- Accession number :
- edsair.doi...........41f58dea2c70bc1d20c210eea0e4aea5