| 基于小波域学习的单幅图像超分辨率复原 |
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| 引用本文： | 徐震寰,林茂松,张红英.基于小波域学习的单幅图像超分辨率复原[J].微型机与应用,2013(18):40-43,46. |
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| 作者姓名： | 徐震寰 林茂松 张红英 |
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| 作者单位： | 西南科技大学 信息工程学院 特殊环境机器人技术四川省重点实验室,四川 绵阳,621010 |
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| 基金项目： | 国防技术基础研究项目(科工技【2011】869号)；国防预研基金项目( B3120110005)；四川省教育厅项目 |
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| 摘 要： | 提出了一种有效的高分辨率图像复原方法，将单幅图像的超分辨率复原转换到小波域中，对小波域的3个高频信息块分别进行处理，再通过基于学习的超分辨率复原方法来实现单幅图像的复原。实验表明，通过该算法恢复的高分辨率图像具有更好的视觉效果与峰值信噪比。
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| 关 键 词： | 小波变换 基于学习 自相似性 超分辨率 |
A single image super-resolution based on wavelet domain learning |
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| Xu Zhenhuan
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Lin Maosong
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Zhang Hongying.A single image super-resolution based on wavelet domain learning[J].Microcomputer & its Applications,2013(18):40-43,46. |
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| Authors: | Xu Zhenhuan Lin Maosong Zhang Hongying |
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| Affiliation: | (Sichuan Province Key Laboratory of Special Environment of Robot Technology, School of Information Engineering Southwest University of Science and Technology, Mianyang 621010, China) |
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| Abstract: | The paper shows an effective high-resolution image recovery tion recovery to the wavelet domain, and processes the three high-frequency ing the examples-based super-resolution method to achieve the recovery shows that the high-resolution images recovered by this algorithm has better method, which changes the single image super-resolu- information of the wavelet domain respectively. And us- of the single image super-resolution. The experiment visual effects and peak signal-to-noise ratio. |
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| Keywords: | wavelet transform example-based patch redundancy super-resolution |
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