Multi-scale face hallucination based on frequency bands analysis

Xiaodan Du, F. Jiang, Debin Zhao
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引用次数: 1

Abstract

In this paper, a multi-scale face hallucination method is proposed to produce high-resolution (HR) face images from low-resolution (LR) ones according to the specific face characteristics and priors based on frequency bands analysis. In the first scale, the middle-resolution (MR) images are generated based on a patch-based learning method in DCT domain. In this scale, the DC coefficients and AC coefficients are estimated separately. In the second scale, a DCT upsampling for low frequency band restoration and a high frequency band restoration are combined to generate the final high-resolution face images. Extensive experiments show that the proposed algorithm achieves significant improvement.
基于频带分析的多尺度面部幻觉
本文提出了一种基于频带分析的多尺度人脸幻觉方法,根据特定的人脸特征和先验信息,将低分辨率人脸图像转化为高分辨率人脸图像。在第一个尺度上,在DCT域采用基于patch的学习方法生成中分辨率(MR)图像。在这个量表中,直流系数和交流系数是分开估计的。在第二个尺度上,结合DCT上采样进行低频恢复和高频恢复,生成最终的高分辨率人脸图像。大量的实验表明,该算法取得了显著的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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