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
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;
Conference_Titel :
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location :
Paris
DOI :
10.1109/ICIP.2014.7025431
