On ambiguities in super-resolution modeling

Some models for super-resolution restoration assume that low-resolution (LR) images are formed from high-resolution (HR) ones by a warping first, blurring second (followed by decimating) imaging process; whereas others adopt a blurring first, warping second imaging constraint. These models are abuse...

Full description

Saved in:
Bibliographic Details
Published in:IEEE signal processing letters 2004-08, Vol.11 (8), p.678-681
Main Authors: Wang, Z., Qi, F.
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Ambiguity
Blurring
Cameras
High-resolution imaging
Image analysis
Image generation
Image resolution
Image restoration
Imaging
Motion estimation
Optical imaging
Physics
Signal processing
Systematic errors
Warpage
Warping
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Some models for super-resolution restoration assume that low-resolution (LR) images are formed from high-resolution (HR) ones by a warping first, blurring second (followed by decimating) imaging process; whereas others adopt a blurring first, warping second imaging constraint. These models are abused to some extent and respective conditions for usability of them are not identified. Such ambiguities are analyzed and cleared up in this letter. Conclusions are: The warping-blurring model coincides with the general imaging physics, but it is usable only if the motion among HR images is known a priori. When the motion is estimated from LR images, this model may cause systematic error, but the use of the blurring-warping model is more appropriate, and leads to better performance.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2004.831674