基于特征空间的人脸超分辨率重构

张地; 何家忠

doi:10.3724/SP.J.1004.2012.01145

基于特征空间的人脸超分辨率重构

doi: 10.3724/SP.J.1004.2012.01145

张地^1,,
何家忠²

1.
广东医学院信息工程学院东莞 523808;
2.
韶关大学物理系韶关 512005

详细信息

通讯作者:
张地

计量
- 文章访问数: 2286
- HTML全文浏览量: 44
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- 被引次数: 0
出版历程
- 收稿日期: 2011-02-22
- 修回日期: 2011-07-01
- 刊出日期: 2012-07-20

Feature Space Based Face Super-resolution Reconstruction

ZHANG Di^1
,,
HE Jia-Zhong²

1.
School of Information Engineering, Guangdong Medical College, Dongguan 523808;
2.
Department of Physics, Shaoguan University, Shaoguan 512005

摘要

摘要: 超分辨率图像重构是利用关于同一场景的多帧低分辨率图像重构出一幅具有更高分辨率图像的过程.传统的超分辨率图像重构算法是基于像素空间,通过利用高、低分辨率像素空间之间的映射关系来求解,具有计算复杂性高等缺点. 针对低分辨率人脸放大问题,提出了一个基于特征空间的人脸超分辨率图像重构算法.与传统算法相比,该算法不仅降低了计算复杂性,还具有更好的鲁棒性.
- 超分辨率 /
- 特征空间 /
- 图像序列 /
- 图像重构
Abstract: Super-resolution image reconstruction is a process of producing a high-resolution image from a set of low-resolution images of the same scene. Previously published techniques usually perform reconstruction on pixel domain, which utilize the relationship between high-resolution and low-resolution pixel space, and suffer a high computational complexity. A feature space based super-resolution face reconstruction algorithm is proposed in this paper for application of high-resolution face reconstruction from low-resolution video surveillance. We showed that compared with normal algorithms, the proposed algorithm is more robust and more computationally efficient.
- Super-resolution /
- feature space /
- image sequence /
- image reconstruction

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参考文献(1)

[1]

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