THE SUR

Thermal Imaging Enhancement with Super-Resolution

 Coordinatore ASELSAN Elektronik Sanayi ve Ticaret A.S. 

 Organization address address: MEHMET AKIF ERSOY MAHALLESI 296 CADDE 16
city: YENIMAHALLE ANKARA
postcode: 6172

contact info
Titolo: Dr.
Nome: S. Kubilay
Cognome: Pakin
Email: send email
Telefono: 90 312 8475300
Fax: 903128000000

 Nazionalità Coordinatore Turkey [TR]
 Totale costo 100˙000 €
 EC contributo 100˙000 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call FP7-PEOPLE-IRG-2008
 Funding Scheme MC-IRG
 Anno di inizio 0
 Periodo (anno-mese-giorno) 0000-00-00   -   0000-00-00

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    ASELSAN Elektronik Sanayi ve Ticaret A.S.

 Organization address address: MEHMET AKIF ERSOY MAHALLESI 296 CADDE 16
city: YENIMAHALLE ANKARA
postcode: 6172

contact info
Titolo: Dr.
Nome: S. Kubilay
Cognome: Pakin
Email: send email
Telefono: 90 312 8475300
Fax: 903128000000

TR (YENIMAHALLE ANKARA) coordinator 100˙000.00

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

incorporated    registration    accurate    classes    filter    multiple    surveillance    object    ls    algorithm    images    resolution    imaging    limitations   

 Obiettivo del progetto (Objective)

'High resolution (HR) images are of interest in many fields such as medical imaging, surveillance, and satellite imaging. Signal processing based resolution enhancement methods have been finding increasing use due to the limitations in the physical principles as well as limitations in optics and electronics technology. However, none of the methods in curent use performs satisfactorily when applied to accurate registration. Robust registration models and solutions for multiple object motion and occlusions should be incorporated into these methods. We propose using a super-resolution (SR) reconstruction algorithm based on least squares (LS) filtering combined with a spatiotemporal classification algorithm. Using these classified images with corresponding LS filter modes and classes, we intend to generate higher resolution images. Registration and multiple object movements will be incorporated into different LS filter classes without requiring accurate estimation of these changes. The proposed technique will be demonstrated on surveillance images acquired from thermal imaging sensors.'

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