Non-linear image recovery from a single frame super resolution using pearson type VII density
Super-resolution (SR) aims to recover a high resolution (HR) image from one or more low resolution (LR) images. The limitations of the capturing source often results in loss of resolution and the introduction of additive noise. Thus, the capturing image will be distorted and will be insufficient to...
Saved in:
Main Author: | |
---|---|
Format: | Conference Paper |
Language: | en_US |
Published: |
2015
|
Subjects: | |
Online Access: | http://ddms.usim.edu.my/handle/123456789/9221 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.usim-9221 |
---|---|
record_format |
dspace |
spelling |
my.usim-92212015-08-26T01:21:10Z Non-linear image recovery from a single frame super resolution using pearson type VII density S.A., Pitchay, High resolution image Ill posed problem; Image recovery Low resolution; Low resolution images Non-linear; Recovering process Super resolution Systems engineering Recovery Super-resolution (SR) aims to recover a high resolution (HR) image from one or more low resolution (LR) images. The limitations of the capturing source often results in loss of resolution and the introduction of additive noise. Thus, the capturing image will be distorted and will be insufficient to sample the image with adequate resolution. In this scenario when there exists only a single frame of low resolution, often the observed frame is deficient or noisy, which makes the recovering process an ill-posed problem where the solution does not exist or is unique. © 2011 Springer Science+Business Media, LLC. 2015-08-26T01:21:10Z 2015-08-26T01:21:10Z 2011-01-01 Conference Paper 9781-4614-0372-2 1876-1100 http://ddms.usim.edu.my/handle/123456789/9221 en_US |
institution |
Universiti Sains Islam Malaysia |
building |
USIM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universit Sains Islam i Malaysia |
content_source |
USIM Institutional Repository |
url_provider |
http://ddms.usim.edu.my/ |
language |
en_US |
topic |
High resolution image Ill posed problem; Image recovery Low resolution; Low resolution images Non-linear; Recovering process Super resolution Systems engineering Recovery |
spellingShingle |
High resolution image Ill posed problem; Image recovery Low resolution; Low resolution images Non-linear; Recovering process Super resolution Systems engineering Recovery S.A., Pitchay, Non-linear image recovery from a single frame super resolution using pearson type VII density |
description |
Super-resolution (SR) aims to recover a high resolution (HR) image from one or more low resolution (LR) images. The limitations of the capturing source often results in loss of resolution and the introduction of additive noise. Thus, the capturing image will be distorted and will be insufficient to sample the image with adequate resolution. In this scenario when there exists only a single frame of low resolution, often the observed frame is deficient or noisy, which makes the recovering process an ill-posed problem where the solution does not exist or is unique. © 2011 Springer Science+Business Media, LLC. |
format |
Conference Paper |
author |
S.A., Pitchay, |
author_facet |
S.A., Pitchay, |
author_sort |
S.A., Pitchay, |
title |
Non-linear image recovery from a single frame super resolution using pearson type VII density |
title_short |
Non-linear image recovery from a single frame super resolution using pearson type VII density |
title_full |
Non-linear image recovery from a single frame super resolution using pearson type VII density |
title_fullStr |
Non-linear image recovery from a single frame super resolution using pearson type VII density |
title_full_unstemmed |
Non-linear image recovery from a single frame super resolution using pearson type VII density |
title_sort |
non-linear image recovery from a single frame super resolution using pearson type vii density |
publishDate |
2015 |
url |
http://ddms.usim.edu.my/handle/123456789/9221 |
_version_ |
1645152565819604992 |
score |
13.214268 |