Single image super resolution based on learning features to constrain back projection
- Resource Type
- Conference
- Authors
- Badran, Yasser K.; Salama, Gouda I.; Mahmoud, Tarek A.; Mousa, Aiman; Moussa, Adel E.
- Source
- 2019 International Conference on Innovative Trends in Computer Engineering (ITCE) Innovative Trends in Computer Engineering (ITCE), 2019 International Conference on. :23-28 Feb, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Image resolution
Image reconstruction
Image restoration
Mathematical model
Feature extraction
Dictionaries
image restoration
example based super resolution
single image super resolution
- Language
Image super-resolution (SR) is an active research point due to its added value for many image processing applications. The classical SR aims to obtain a high resolution (HR) image using multiple low resolution (LR) images. Recently many research works are directed towards obtaining such HR image from a single LR image which is known as single image SR restoration.This paper presents a fast single-image SR approach based on learning the functions that can transfer LR patch into HR features. Then, these features are used to reconstruct the HR image through a process called constrained back-projection. The experimental results show that the proposed approach is capable of providing a high quality super-resolution images.