Wavelet Domain Multidictionary Learning for Single Image Super-Resolution
Image super-resolution (SR) aims at recovering the high-frequency (HF) details of a high-resolution (HR) image according to the given low-resolution (LR) image and some priors about natural images. Learning the relationship of the LR image and its corresponding HF details to guide the reconstruction...
Saved in:
Main Authors: | Xiaomin Wu, Jiulun Fan, Jian Xu, Yanzi Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2015-01-01
|
Series: | Journal of Electrical and Computer Engineering |
Online Access: | http://dx.doi.org/10.1155/2015/526508 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Metasurface-Coated Liquid Microlens for Super Resolution Imaging
by: Tongkai Gu, et al.
Published: (2024-12-01) -
Unsupervised Image Super-Resolution for High-Resolution Satellite Imagery via Omnidirectional Real-to-Synthetic Domain Translation
by: Minkyung Chung, et al.
Published: (2025-01-01) -
XTNSR: Xception-based transformer network for single image super resolution
by: Jagrati Talreja, et al.
Published: (2025-01-01) -
Gradient pooling distillation network for lightweight single image super-resolution reconstruction
by: Zhiyong Hong, et al.
Published: (2025-02-01) -
Latent spectral-spatial diffusion model for single hyperspectral super-resolution
by: Yingsong Cheng, et al.
Published: (2024-12-01)