Low Resolution Facial Image Restoration Based on Sparse Representation

摘要：

In this paper, a strategy of reconstructing high resolution facial image based on that of low resolution is put forward. Rather than only relying on low resolution input image, we construct a face representation dictionary based on training high resolution facial images to compensate for the information di.erence between low and high resolution images. This restoration is realized through enrolling a low resolution facial image dictionary which is acquired through directly downsampling the learned high resolution dictionary. After the representation coe.cient vector of a low resolution input image on low resolution dictionary is obtained through 1-optimization algorithm, this coe.cient can be transplanted into high resolution dictionary directly to restore the high resolution image corresponding to input face. This approach was validated on the Extended Yale database.

关键词： Low resolution restoration facial image image interpolation sparse representation 1-optimization overcomplete dictionary

作者: Yuelong Li Junjie Bian Jufu Feng

作者单位: Key Laboratory of Machine Perception (MOE) School of Electronics Engineering and Computer Science, P Key Laboratory of Machine Perception (MOE)School of Electronics Engineering and Computer Science, Pe

会议类型: 国际会议

会议名称: 第七届多光谱图象处理与模式识别国际学术会议

会议地点: 桂林

会议语种:英文

页码: 1-6

在线出版日期: 2011-11-01（万方平台首次上网日期，不代表论文的发表时间）