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An Alternative Single-Image Super Resolution Framework Employing High Frequency Prediction Using A Robust Huber Rational Function

by Kornkamol Thakulsukannant; Vorapoj Patanavijit

Title:

An Alternative Single-Image Super Resolution Framework Employing High Frequency Prediction Using A Robust Huber Rational Function

Author(s):

Kornkamol Thakulsukannant
Vorapoj Patanavijit

Contributor(s):

Vincent Mary School of Engineering

Issued date:

2015-11

Citation:

ICIIBMS 2015, Track3: Bioinformatics, Medical Imaging and Neuroscience, Okinawa, Japan, 351-354

Abstract:

In general prospective, SI-SR or Single-Image Super-Resolution, which is one of the most useful algorithms of Super Resolution-Reconstruction (SRR) algorithms, is a mathematical procedure for acquiring a high-resolution image from only one coarse-resolution image, which is usually computed by Digital Image Processing (DIP). Even thought there have been substantially researched during the last decade, Single - Image Super-Resolution for applying on real implementations still keeps throw down the gauntlet. One of the practical Single- Image Super-Resolution is the resolution enhancement using prediction of the high-frequency image because of its high performance and its less comple xity however the rational function C(x, y) of high-frequency image prediction process of this technique is depend upon three parameters (b, h, k) therefore the parameter turning is difficult for maximizing its performance. From this problem prospective, this paper presents the alternative SI-SR framework employing robust rational function based on Huber function, which is depend upon only one parameter (T), instead of three parameters like the rational function C(x,y). Using up to fourteen standard images, which are crooked by varied noise models, in analysis testing section, the proposed SI-SR is demonstrated to be somewhat simper than the original SI-SR with equivalent efficiency because the saving in parameter turning time will be very important for SI-SR in real implementations.

Keyword(s):

SRR (Super Resolution-Reconstruction)
SI-SR (Single-Image Super-Resolution)
Digital image reconstruction

Resource type:

Conference Paper

Extent:

4 pages

Type:

Text

File type:

application/pdf

Language:

eng

Rights holder(s):

Kornkamol Thakulsukanant
Vorapoj Patanavijit

URI:

http://repository.au.edu/handle/6623004553/21015
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Copyright © Assumption University.
All Rights Reserved.

Contact Us

The St. Gabriel's Library   
Hua Mak Campus  
Ramkhamhaeng 24, Hua Mak  
Bangkok Thailand 10240  
Tel.: (662) 3004543-62 Ext. 3402  
Fax.: (662) 7191544  
E-Mail Library : library@au.edu  


The Cathedral of Learning Library
Suvarnabhumi Campus
Bang Na-Trad Km. 26 Bangsaothong
Samuthprakarn Thailand 10540
Tel.: (662) 7232024, 7232025
Fax.: (662) 7191544
E-Mail Library : library@au.edu
 

 

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