基于单像素相机的压缩感知测量矩阵设计与重建算法并行化研究

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题名	基于单像素相机的压缩感知测量矩阵设计与重建算法并行化研究
作者	秦书嘉
学位类别	博士
答辩日期	2016-05-26
授予单位	中国科学院沈阳自动化研究所
导师	席宁 ; 刘连庆
关键词	压缩感知单像素相机阿达马变换结构化采样并行算法
其他题名	Compressed Sensing Measurement Matrix Design and Reconstruction Algorithm Parallelization Based on the Single-Pixel Camera
学位专业	模式识别与智能系统
中文摘要	本文在分析了现有的单像素相机技术与压缩感知理论的基础上，对单像素相机目前面临的瓶颈展开了研究，研究内容包括单像素相机曝光阶段的测量矩阵设计的问题，以及在信号重建阶段的算法问题。本文的主要工作有：1、总结了现有单像素相机的功能结构，采样原理以及算法，并定量解释了阿达马矩阵能成为单像素相机测量矩阵的原因，使用总变差域稀疏的概念对单像素相机的压缩感知意义进行了阐述。2、研究了目前单像素相机曝光阶段测量矩阵生成的两难问题（硬件上的随机数生成器生成测量矩阵，曝光阶段效率高，但没有结构性，图像重建慢；乱序阿达马矩阵作为测量矩阵，图像重建快，但需要预先保存在大量内存中，曝光阶段再读取，曝光阶段效率低），提出了一种生成乱序阿达马矩阵的硬件结构，综合了两种方法各自的优点。3、研究了目前最先进的单像素相机图像重建算法中的耗时操作，在此基础上提出了通用的阿达马变换任务级并行算法。　　本文的研究提供了一种可行的单像素相机百万像素级以上成像应用的快速曝光方案。考虑所提出采样结构的简洁高效性，该方案还能运用到其它大规模二值采样的压缩感知应用中。而快速阿达马变换被广泛应用于信号与图像处理，通信系统，数字逻辑等领域中，本文在单像素相机算法背景下研究的通用阿达马变换任务级并行算法，对这些相关应用中规模较大的阿达马变换计算的问题也有贡献。
英文摘要	Based on the analyses of current technology of SPCs and the compressed sensing theory, this thesis studies the bottleneck of the SPC, including the measurement matrix design within the exposure phase of imaging and the reconstruction algorithm within the signal reconstruction phase. The main contributions are: 1) Summarizes the functional structure, sampling principle and algorithms of the current SPCs, quantitatively explains why Hadamard matrices can be the measurement matrices of SPCs, and demonstrates the compressed sensing nature in SPCs by using the concept of the “total variation sparse domain”. 2) Studies the current dilemma of SPCs in the exposure phase (using hardware random number generator for measurement matrices has high performance in the exposure phase, but low efficiency in reconstruction because of the lack of a structural measurement; using permuted Hadamard matrices for measurement matrices has high efficiency in reconstruction, but this scheme requires unacceptably large memory to store the matrix data, and suffers a long loading time in the exposure phase), and proposes a hardware structure that can generate permuted Hadamard matrices benefiting from the advantages of both conventional methods. 3) Studies the time-consuming operations in the state-of-the-art algorithm for the image reconstruction of SPCs, and proposes a general parallel algorithm for the fast Hadamard transform. The study of the thesis presents a feasible fast exposure scheme for mega-pixel imaging of SPCs, which can be applied to other large-scale binary compressed sampling problems because of its simplicity and efficiency. Besides, since the fast Hadamard transform is widely used in diverse fields such as signal and image processing, communication systems, and digital logic, the proposed task-level parallelized Hadamard transform will have contributions for the corresponding large-scale problems in these areas.
语种	中文
产权排序	1
页码	113页
内容类型	学位论文
源URL	[http://ir.sia.cn/handle/173321/19672]
专题	沈阳自动化研究所_机器人学研究室
推荐引用方式 GB/T 7714	秦书嘉. 基于单像素相机的压缩感知测量矩阵设计与重建算法并行化研究[D]. 中国科学院沈阳自动化研究所. 2016.