基于稀疏表示的人脸图像超分辨率技术研究-计算机技术专业论文.docx

上海交通大学硕士学位论文 上海交通大学硕士学位论文 万方数据 万方数据 基于稀疏表示的人脸图像超分辨率技术研究 摘要 随着社会信息化程度的提高，图像作为一种直观的信息载体，人 们对其质量的要求与日俱增。图像超分辨率技术作为提高图像分辨率 的有效手段已成为学者们重点研究的方向。另外，由于人脸图像在视 频监控应用中具有关键性作用，针对人脸图像的超分辨率技术已经单 独成为一项重要的研究课题。 本文深入研究了基于稀疏表示理论的超分辨率算法，在此基础上 根据人脸图像的特性，分别提出了适用于人脸图像的局部自适应超分 辨率算法和全局自适应超分辨率算法。局部自适应超分辨率算法针对 基于稀疏表示的超分辨率算法中对每个分块所采用的字典缺乏适应性 的问题，提出对每个局部分块自适应地从字典数据库中选取匹配的字 典进行重构，匹配失败时就自适应地选取与目标低分辨率分块相似的 训练子集来训练适合的字典，更新到字典库中并用新字典进行重构， 另外匹配阈值和相似度阈值会根据目标图像自适应调整大小。全局自 适应超分辨率算法考虑到人脸图像的多样性，提出根据目标低分辨率 人脸图像的全局特征自适应地从包含大量不同类别的人脸图像训练总 集中选取最适合的训练子集，最后用该子集训练得到的字典进行超分 辨率。仿真实验表明，这两种算法均具有较好的图像重构效果。 以上述两种算法为核心，本文设计实现了人脸图像超分辨率应用 软件。该软件具有良好的实用性。 关键词：人脸图像、超分辨率、稀疏表示、字典数据库 I RESEARCH ON SUPER-RESOLUTION BASED ON SPARSE REPRESENTATION FOR HUMAN FACE IMAGES ABSTRACT Since the image is an intuitional information carrier, the requirement for its quality is increasing with the rise of social informatization level. Image super-resolution as the effective measure to improve the resolution has become an important research field. In addition, due to the fact that the human face image works as a key role in the video surveillance application, super-resolution for human face images has become an important research topic on its own. This paper analyzes the super-resolution algorithms based on sparse representation in detail. On this basis, according to the characteristics of human face images, this paper puts forward a local adaptive super-resolution algorithm and a global adaptive super-resolution algorithm respectively for human face images. The local adaptive super-resolution algorithm makes up the shortage of the super resolution algorithm based on sparse representation that the dictionary pair for each block lacks adaptability. In the proposed algorithm the matching dictionary pair is self-adaptively selected from the dictionary library for each local block. If matching fails, the similar block training subset to the target low-resolution one is self-adaptively selected for suitable dictionary pair training. Then the new