DocumentCode
248459
Title
Joint video fusion and super resolution based on Markov random fields
Author
Jin Chen ; Nunez-Yanez, Jose ; Achim, Alin
Author_Institution
Vision Inf. Lab., Univ. of Bristol, Bristol, UK
fYear
2014
fDate
27-30 Oct. 2014
Firstpage
2150
Lastpage
2154
Abstract
In this paper, a joint video fusion and super-resolution algorithm is proposed. The method addresses the problem of generating a high-resolution (HR) image from infrared (IR) and visible (VI) low-resolution (LR) images, in a Bayesian framework. In order to preserve better the discontinuities, a Generalized Gaussian Markov Random Field (MRF) is used to formulate the prior. Experimental results demonstrate that information from both visible and infrared bands is recovered from the LR frames in an effective way.
Keywords
Gaussian processes; Markov processes; image fusion; image resolution; infrared imaging; video signal processing; Bayesian framework; MRF; Markov random fields; generalized Gaussian Markov random field; high-resolution image generation; infrared image; joint video fusion and super-resolution algorithm; low-resolution image; visible image; Bayes methods; Image fusion; Image resolution; Image sensors; Joints; Sensor fusion; Generalized Gaussian Markov Random Field; Video Super-Resolution; Video fusion;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location
Paris
Type
conf
DOI
10.1109/ICIP.2014.7025431
Filename
7025431
Link To Document