Joint Image Registration and Super-Resolution From Low-Resolution Images With Zooming Motion

This paper proposes a new framework for joint image registration and high-resolution (HR) image reconstruction from multiple low-resolution (LR) observations with zooming motion. Conventional super-resolution (SR) methods typically formulate the SR problem as a two-stage process, namely, image regis...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on circuits and systems for video technology Vol. 23; no. 7; pp. 1224 - 1234
Main Authors YUSHUANG TIAN, YAP, Kim-Hui
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.07.2013
Institute of Electrical and Electronics Engineers
Subjects
Applied sciences
Detection, estimation, filtering, equalization, prediction
Estimation
Exact sciences and technology
Image processing
Image reconstruction
Image registration
Image resolution
image super-resolution (SR)
Information, signal and communications theory
Joints
Minimization
Signal and communications theory
Signal processing
Signal, noise
Telecommunications and information theory
Vectors
zooming
Image registration
High resolution
Multistage method
Image resolution
Image processing
Superresolution
Iterative method
Low resolution
Algorithm
Image reconstruction
Image quality
image super-resolution (SR)
Zoom
Multistage circuit
zooming
Online AccessGet full text

Cover

More Information
Summary:This paper proposes a new framework for joint image registration and high-resolution (HR) image reconstruction from multiple low-resolution (LR) observations with zooming motion. Conventional super-resolution (SR) methods typically formulate the SR problem as a two-stage process, namely, image registration followed by HR reconstruction. An important step in image SR is the effective estimation of motion parameters. However, the registration algorithms in these two-stage processes experience various degrees of errors. This could degrade the quality of subsequent HR reconstruction. In view of this, this paper presents a new approach that performs joint image registration and SR reconstruction. The proposed iterative SR framework enables the HR image and motion parameters to be estimated simultaneously and progressively. This could increase the potential SR improvement as more accurate estimates of motion parameters could be obtained iteratively. Experimental results show that the proposed method is effective in performing image registration and SR for simulated and real-life images and videos.
ISSN:1051-8215
1558-2205
DOI:10.1109/TCSVT.2013.2242593