Single image super‐resolution based on sparse representation using dictionaries trained with input image patches-Reference-Cited by-同舟云学术

Single image super‐resolution based on sparse representation using dictionaries trained with input image patches

Published:2020-05-14 Issue:8 Volume:14 Page:1587-1593
ISSN:1751-9667
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Asgarian Dehkordi Rasoul¹,Khosravi Hossein¹^ORCID,Ahmadyfard Alireza¹^ORCID

Affiliation:

1. Electrical and Robotics Engineering DepartmentShahrood University of TechnologyShahroodIran

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2019.0129

Reference22 articles.

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2. LinF. FookesB. andChandranVet al: ‘Investigation into optical flow super‐resolution for surveillance applications’ 2005

3. Limits on super‐resolution and how to break them;Baker S.;IEEE Trans. Pattern Anal.,2003

4. Fundamental limits of reconstruction-based superresolution algorithms under local translation

5. Super‐resolution of remotely sensed images with variable‐pixel linear reconstruction;Merino M. T.;IEEE Trans. Remote Sens.,2007

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