4x4 High-Magnification Image Reconstruction Based on Hybrid of Multi-frame SR Approach and Image Super Resolve Algorithm

Published date
2015-11
Resource type
Publisher
ISBN
ISSN
DOI
Call no.
Other identifier(s)
Edition
Copyrighted date
Language
eng
File type
application/pdf
Extent
5 pages
Other title(s)
Advisor
Other Contributor(s)
Citation
IEEE International Conference on Intelligent Informatics and BioMedical Sciences (ICIIBMS 2015), Okinawa, Japan, Nov. 2015, 342-346
Degree name
Degree level
Degree discipline
Degree department
Degree grantor
Abstract
From tremendously soliciting high quality and high resolution images, sundry image reconstruction algorithms have been researched and implemented during the last fifteen years, especially for high-magnification image reconstructions. In this paper, we develop high-magnification image reconstruction based on hybrid of a multi-frame SR approach and an image super resolve algorithm for 4x4 magnifying in resolution. First, a group of polluted low resolution images are amalgamated for 2x2 magnifying in resolution and suppressing the noise in each polluted low resolution images. Next, the 2x2 magnified image is reconstructed by using image super resolve algorithm based on the high-frequency image prediction to be the 4x4 magnified image. In the performance testing section, the outcomes on both benchmark (in PSNR) and virtual quality, contrasting with previous classical algorithms from the research literature (such as a classical interpolation technique, a classical SRR and an image super resolve algorithm), expose that the proposed hybrid framework has the better performance in both benchmark (in PSNR) and virtual quality.
Table of contents
Description
punsarn.dc.description.sponsorship
Spatial Coverage
Subject(s)
Rights
Access rights
Rights holder(s)
Location
View External Resources