[1]李欣,崔子冠,陈杰,等. 基于局部回归和自相似性的图像超分辨率重建[J].计算机技术与发展,2016,26(10):17-21.
 LI Xin,CUI Zi-guan,CHEN Jie,et al. Image Super-resolution Reconstruction Based on Local Regression and Self-similarity[J].,2016,26(10):17-21.
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 基于局部回归和自相似性的图像超分辨率重建()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年10期
页码:
17-21
栏目:
智能、算法、系统工程
出版日期:
2016-10-10

文章信息/Info

Title:
 Image Super-resolution Reconstruction Based on Local Regression and Self-similarity
文章编号:
1673-629X(2016)10-0017-05
作者:
 李欣崔子冠陈杰朱秀昌
 南京邮电大学 通信与信息工程学院
Author(s):
 LI XinCUI Zi-guanCHEN JieZHU Xiu-chang
关键词:
 超分辨率自相似性局部回归字典学习稀疏表示
Keywords:
 super-resolutionself-similaritylocal regressiondictionary learningsparse representation
分类号:
TP301.6
文献标志码:
A
摘要:
 近年来,基于样本的图像超分辨率重建逐渐成为研究热点,该算法一般利用外部训练样本,测试图像与训练样本的相似度在一定程度上影响着重建结果。针对此类问题,提出一种基于局部回归和自相似性的图像超分辨率重建算法。应用不同尺度图像间的自相似特性,对图像块建立一阶回归模型完成重建的算法,充分利用图像自身信息,并用稀疏表示的方法替代遍历搜索自相似块的方法,可以在自相似块不足的情况下保证重建质量。实验结果表明,该算法的重建质量较高,可以一定程度减少外部训练样本带来的虚假高频问题,且在重建质量与重建时间上有着较好的折中。
Abstract:
 In recent years,image super-resolution reconstruction based on samples has gradually become a hot research topic,which usual-ly uses the external training samples. The similarity between the test image and the training samples affects the reconstruction results to a certain extent. To solve this problem,a super-resolution image reconstruction algorithm based on local regression and self-similarity is proposed. This algorithm,which makes use of the self-similarity between images at different scales and reconstructs the image by establis-hing the first-order autoregressive model of the patches,could make full use of the information of the image itself,and replace the travers-al search of self-similar patches with the sparse representation method. So it can guarantee the reconstruction quality even the number of the self-similar patches is not enough. The experimental results show that the reconstruction quality of this algorithm is high. It can allevi-ate the false high-frequency problem brought by the external training samples to a certain extent and have a good tradeoff between the re-construction quality and reconstruction time.

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更新日期/Last Update: 2016-11-25