Cover Image

Single frame image recovery for super resolution with parameter estimation of pearson type VII density

Image recovery of super resolution aims to recover a single high resolution image from one or more low resolution frames. It is an ill-posed problem when the solution does not exist or it is unique. Thus, we introduce the prior based on Pearson type VII density integrated with a Markov Random Field...

Full description

Saved in:
Bibliographic Details
Main Author: Pitchay S.A.
Format: Article
Language:English
Published: 2017
Subjects:
Compressive measurement; MRF model; Pearson type VII; Suingle frame super resolution
Online Access:http://ddms.usim.edu.my:80/jspui/handle/123456789/15344
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.usim-15344
record_format dspace
spelling my.usim-153442017-10-30T06:57:02Z Single frame image recovery for super resolution with parameter estimation of pearson type VII density Pitchay S.A. Compressive measurement; MRF model; Pearson type VII; Suingle frame super resolution Image recovery of super resolution aims to recover a single high resolution image from one or more low resolution frames. It is an ill-posed problem when the solution does not exist or it is unique. Thus, we introduce the prior based on Pearson type VII density integrated with a Markov Random Field (MRF) model. We devise two different versions, one that acts on the pixel level and another one that acts on the entire image. Here we present our parameter estimation and evaluate our approach using qualitative measurement in both compressive measurement and classical super resolution. Our estimation is theoretically simple and easy to implement. 2017-10-30T06:57:02Z 2017-10-30T06:57:02Z 2011 Article 1819656X http://ddms.usim.edu.my:80/jspui/handle/123456789/15344 en
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 English
topic Compressive measurement; MRF model; Pearson type VII; Suingle frame super resolution
spellingShingle Compressive measurement; MRF model; Pearson type VII; Suingle frame super resolution
Pitchay S.A.
Single frame image recovery for super resolution with parameter estimation of pearson type VII density
description Image recovery of super resolution aims to recover a single high resolution image from one or more low resolution frames. It is an ill-posed problem when the solution does not exist or it is unique. Thus, we introduce the prior based on Pearson type VII density integrated with a Markov Random Field (MRF) model. We devise two different versions, one that acts on the pixel level and another one that acts on the entire image. Here we present our parameter estimation and evaluate our approach using qualitative measurement in both compressive measurement and classical super resolution. Our estimation is theoretically simple and easy to implement.
format Article
author Pitchay S.A.
author_facet Pitchay S.A.
author_sort Pitchay S.A.
title Single frame image recovery for super resolution with parameter estimation of pearson type VII density
title_short Single frame image recovery for super resolution with parameter estimation of pearson type VII density
title_full Single frame image recovery for super resolution with parameter estimation of pearson type VII density
title_fullStr Single frame image recovery for super resolution with parameter estimation of pearson type VII density
title_full_unstemmed Single frame image recovery for super resolution with parameter estimation of pearson type VII density
title_sort single frame image recovery for super resolution with parameter estimation of pearson type vii density
publishDate 2017
url http://ddms.usim.edu.my:80/jspui/handle/123456789/15344
_version_ 1645153894959939584
score 13.214268

Similar Items