基于局部约束的人脸图像超分辨率重构算法

基于超完备稀疏表示理论,并根据人脸图像的特征,提出一种基于局部约束的人脸图像超分辨率重构算法。该算法首先通过样本训练出一对高、低分辨率相关联的冗余字典;再根据局部范围内人脸图像的相关性,重构出高分辨率图像;最后对图像进行全局优化。为验证算法的有效性,本文利用ORL标准图像库进行了对比实验,实验结果表明,该算法能够有效提高峰值信噪比,同时能够更好地恢复人脸图像的高频信息,有一定的实用价值。

Face image super-resolution reconstruction based on local constraint

Based on the overcomplete sparse representation theory,a face image super-resolution reconstruction method based on local constraint is proposed.First,a pair of associated redundant dictionary,including high-resolution (HR)and low-resolution (LR),are calculated through sample training.Based on the correlation in local scope of face image,the high-resolution image is reconstructed.Then,the image is optimized globally.To verify the validity of the algorithm,the contrast experiment is made by using ORL standard image,the results show that the algorithm can work well in the actual conditions,and can recover the high-resolution information perfectly.