摘要
针对多帧图像超分辨率重建问题,利用一阶泰勒展式,在亚像素级上对图像退化过程进行建模,并建立极小化能量函数,选择Graph-cut算法进行能量极小化求解.为了验证本文算法的有效性,采用模拟图像退化过程和直接用相机拍摄两种方式获得低分辨率图像序列.从4×4倍重建结果的比较来看,本文算法不仅对模拟退化过程产生的低分辨率图像序列有效,而且在提高真实低分辨率图像的分辨能力方面也有很好的效果.此外,实验结果表明本文算法对噪声有较好的抗干扰能力.
This paper studies the problem of multi-frame image super-resolution reconstruction. The process of image degradation is modeled by using the first-order Taylor expansion based on sub-pixel. Then the energy minimization function is established and the graph-cut algorithm is chosen to solve the energy minimization. In order to confirm this algorithm, we obtain the low resolution images by two ways： simulating image degradation and taking photos. By comparing the 4 x4 times reconstruction results, it is shown that this algorithm is valid not only for simulation of low resolution images but also for real images. Besides, experimental results show that this algorithm possesses good anti-interference ability of noise.
出处
《自动化学报》
EI
CSCD
北大核心
2014年第12期2851-2861,共11页
Acta Automatica Sinica
基金
国家自然科学基金(61373077)
国防基础科研计划(B0110155)
国防科技重点实验室基金(9140C30211ZS8)
高等学校博士学科点专项科研基金(20110121110020)
福建省自然科学基金(2011J01365)
福建省重点项目(2014H0034)
航空科学基金(20125168001)
黄慧贞集美大学学科建设基金(ZC2014010)资助~~
