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Multiplex optical sensors for reference structure tomography and compressive spectroscopy.

机译:用于参考结构层析成像和压缩光谱的多重光学传感器。

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摘要

With the emergence of ubiquitous embedded digital processing and inexpensive focal planes, imaging and sensor systems that integrate optical and electronic processing have increasingly become attractive. These systems are regarded as "integrated computational imaging systems" because they use non-conventional optical elements to preprocess the field for digital analysis.;Computational imaging systems, also referred to as multiplex imagers, are particularly attractive as they achieve increased depth of field, multidimensional or multispectral imaging, improved data or computational efficiency and improved target recognition or tracking capabilities. Some of the capabilities of these computational systems are: multidimensional imaging, source analysis, data compression and analysis and sensor array data fusion.;In this thesis, a novel computational imaging system termed "Reference structure tomography (RST)" is proposed. RST makes use of a new form of volume optical element, a tomographic reference structure which modulates the visibility of the source space to improve the efficiency of object analysis. This thesis will describe RST and demonstrate three-dimensional imaging and source analysis with reference structures.;This thesis also proposes a new multiplex optical sensing system for compressive sampling in the physical layer. Compressive sampling enables signal reconstruction using fewer than one measurement per estimated signal value. A measurement efficient optical wavemeter and a compressive spectrometer will be described to demonstrate compressive sampling. The optical wavemeter efficiently measures the spectral densities of quasi-monochromatic and spectrally sparse sources. The compressive spectrometer measures the spectrum of a broad-band source with fewer measurements than the number of estimated spectral channels. The compressive spectrometer is designed to physically measure the Haar wavelet coefficients of the spectral source and the spectrum is estimated from these coefficients.
机译:随着无处不在的嵌入式数字处理和廉价的焦平面的出现,集成了光学和电子处理的成像和传感器系统变得越来越有吸引力。这些系统之所以被视为“集成计算成像系统”,是因为它们使用非常规光学元件对场进行预处理以进行数字分析。计算成像系统(也称为多路复用成像器)在实现更高的景深方面尤其具有吸引力,多维或多光谱成像,改进的数据或计算效率以及改进的目标识别或跟踪功能。这些计算系统的一些功能包括:多维成像,源分析,数据压缩和分析以及传感器阵列数据融合。;本文提出了一种新型的计算成像系统,称为“参考结构层析成像(RST)”。 RST利用一种新形式的体光学元件,即一种层析参考结构,可以调节源空间的可见性,从而提高对象分析的效率。本文将对RST进行描述,并通过参考结构演示三维成像和源分析。本文还提出了一种用于物理层压缩采样的新型多路光学传感系统。压缩采样使每个估计的信号值使用少于一次的测量即可进行信号重建。将描述测量有效的光波表和压缩光谱仪,以演示压缩采样。光波计可以有效地测量准单色光源和光谱稀疏光源的光谱密度。压缩光谱仪以比估计光谱通道数更少的测量值来测量宽带源的光谱。压缩光谱仪设计用于物理测量光谱源的Haar小波系数,并从这些系数估算光谱。

著录项

  • 作者

    Potuluri, Prasant.;

  • 作者单位

    Duke University.;

  • 授予单位 Duke University.;
  • 学科 Engineering Electronics and Electrical.;Physics Optics.
  • 学位 Ph.D.
  • 年度 2004
  • 页码 107 p.
  • 总页数 107
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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