JOINT VIDEO FUSION AND SUPER RESOLUTION BASED ON MARKOV RANDOM FIELDS

被引：0
|
作者：
Chen, Jin [1 ]
Nunez-Yanez, Jose [1 ]
Achim, Alin [1 ]
机构：
[1] Univ Bristol, Vis Informat Lab, Bristol BS8 1TH, Avon, England
来源：
2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2014年
关键词：
Video fusion; Video Super-Resolution; Generalized Gaussian Markov Random Field; IMAGE FUSION;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
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.
引用
收藏
页码：2150 / 2154
页数：5
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