Methods for Inhomogenity Correction of Images from Microbolometric Sensors
Metody korekce nehomogenity obrazu z mikrobolometrických senzorů
Authors
Supervisors
Reviewers
Editors
Other contributors
Journal Title
Journal ISSN
Volume Title
Publisher
České vysoké učení technické v Praze
Czech Technical University in Prague
Czech Technical University in Prague
Date
Abstract
Tato diplomová práce se věnuje teoretickému rozboru používaných metod pro korekci nehomogenit na snímcích z mikrobolometrických senzorů a následným návrhem algoritmu pro korekci nehomogenit způsobených jak rozdílným offsetem a ziskem senzoru, tak zejména vinětací objektivu. Navržený algoritmus, založený na běžných metodách pro zpracování snímků z mikrobolometrických senzorů respektive z IRFPA (infrared focal plane array), je implementován ve vývojovém prostředí Matlab. Následně je tento algoritmus otestován na snímcích z infračervené kamery a porovnán s korigovanými snímky přímo z kamery. Na závěr jsou shrnuty výsledky, pozitiva a negativa navrženého algoritmu.
The thesis is focused on the theoretical analysis of methods which are used for the non-uniformity correction of images from microbolometer sensors and on the subsequent design of the algorithm for the non-uniformity correction of an image caused by different offset and gain of each bolometer and vignetting of lens. The proposed algorithm is based on conventional methods of processing images from microbolometer sensors, respectively IRFPA (infrared focal plane array) and is implemented in Matlab development environment. Subsequently this algorithm is tested on the images from an infrared camera and is compared with the corrected images from the camera. In conclusion we summarize the results, the positives and the negatives of the proposed algorithm.
The thesis is focused on the theoretical analysis of methods which are used for the non-uniformity correction of images from microbolometer sensors and on the subsequent design of the algorithm for the non-uniformity correction of an image caused by different offset and gain of each bolometer and vignetting of lens. The proposed algorithm is based on conventional methods of processing images from microbolometer sensors, respectively IRFPA (infrared focal plane array) and is implemented in Matlab development environment. Subsequently this algorithm is tested on the images from an infrared camera and is compared with the corrected images from the camera. In conclusion we summarize the results, the positives and the negatives of the proposed algorithm.