Very Low Resolution Face Image Super-Resolution Based on DCT

Xiaoyu Wang; Yazhou Zhang; Xiaozhong Guo

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Very Low Resolution Face Image Super-Resolution Based on DCT

机译：基于DCT的超低分辨率人脸图像超分辨率

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摘要

This paper introduces the Very Low Resolution (VLR) problem in the field of face image super-resolution reconstruction. With the extensive application of the surveillance cameras, the very low resolution problem happens in many face recognition applications, which has brought great inconvenience to users. In order to research this problem, this paper proposes the improved DCT algorithm, and our final experimental results have compared with the common DCT algorithm, Cubic B-Spline interpolation algorithm and Baker et al's method. Experimental results show that the improved DCT algorithm can get better performance in the very low resolution face image super-resolution reconstruction problem.

机译：本文介绍了人脸图像超分辨率重建领域中的超低分辨率（VLR）问题。随着监控摄像机的广泛应用，在许多人脸识别应用中出现了分辨率很低的问题，给用户带来了极大的不便。为了研究这个问题，本文提出了一种改进的DCT算法，并将我们的最终实验结果与常见的DCT算法，三次B样条插值算法和Baker等人的方法进行了比较。实验结果表明，改进的DCT算法在超低分辨率人脸图像超分辨率重建问题上具有较好的性能。

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来源
《Journal of information and computational science》 |2014年第11期|3807-3813|共7页
作者
Xiaoyu Wang; Yazhou Zhang; Xiaozhong Guo;
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作者单位

School of Computer Science and Technology, Harbin University of Science and Technology Harbin 150080, China;

School of Computer Science and Technology, Harbin University of Science and Technology Harbin 150080, China;

School of Computer Science and Technology, Harbin University of Science and Technology Harbin 150080, China;

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正文语种 eng
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关键词
DCT; The Very Low Resolution; Face Recognition;

机译：DCT;极低的分辨率;人脸识别;

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3. Enhancing Blurred Low-Resolution Images via Exploring the Potentials of Learning-Based Super-Resolution [J] . Shao Wen-Ze, Bao Bing-Kun, Li Hai-Bo International Journal of Pattern Recognition and Artificial Intelligence . 2019,第7期

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4. Image Super-Resolution using DCT Interpolation and Sparse Learning-based Method [C] . Saulo R. S. Reis, Graca Bressan International conference on digital image processing . 2013

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5. Blind deconvolution and super-resolution of low-resolution images and videos. [D] . Faramarzi, Esmaeil. 2012

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6. Reconstruction of super-resolution STORM images using compressed sensing based on low-resolution raw images and interpolation [O] . Tao Cheng, Danni Chen, Bin Yu, 2017

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7. Projections onto Convex Sets Super-Resolution Reconstruction Based on Point Spread Function Estimation of Low-Resolution Remote Sensing Images [O] . Chong Fan, Chaoyun Wu, Grand Li, 2017

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Very Low Resolution Face Image Super-Resolution Based on DCT

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