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Performance assessment of a compressive sensing single-pixel imaging system

机译：压缩传感单像素成像系统的性能评估

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摘要

Conventional sensors measure the light incident at each pixel in a focal plane array. Compressive sensing (CS) involves capturing a smaller number of unconventional measurements from the scene, and then using a companion process to recover the image. CS has the potential to acquire imagery with equivalent information content to a large format array while using smaller, cheaper, and lower bandwidth components. However, the benefits of CS do not come without compromise. The CS architecture chosen must effectively balance between physical considerations, reconstruction accuracy, and reconstruction speed to meet operational requirements. Performance modeling of CS imagers is challenging due to the complexity and nonlinearity of the system and reconstruction algorithm. To properly assess the value of such systems, it is necessary to fully characterize the image quality, including artifacts and sensitivity to noise. Imagery of a two-handheld object target set was collected using an shortwave infrared single-pixel CS camera for various ranges and number of processed measurements. Human perception experiments were performed to determine the identification performance within the trade space. The performance of the nonlinear CS camera was modeled by mapping the nonlinear degradations to an equivalent linear shift invariant model. Finally, the limitations of CS modeling techniques are discussed.
机译：常规传感器测量在焦平面阵列中每个像素处入射的光。压缩感测（CS）涉及从场景中捕获少量非常规测量值，然后使用伴随过程恢复图像。 CS具有使用大型，廉价和带宽较低的组件采集具有与大型阵列等效的信息内容的图像的潜力。但是，CS的好处并非没有妥协。所选的CS架构必须在物理考虑因素，重建精度和重建速度之间达到有效平衡，以满足运营要求。由于系统和重建算法的复杂性和非线性，CS成像仪的性能建模具有挑战性。为了正确评估此类系统的价值，有必要全面表征图像质量，包括伪影和对噪声的敏感性。使用短波红外单像素CS相机收集两个手持对象目标集的图像，以获取各种范围和处理后的测量值。进行了人类感知实验，以确定交易空间内的识别性能。非线性CS相机的性能是通过将非线性退化映射到等效线性位移不变模型来建模的。最后，讨论了CS建模技术的局限性。

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  • 来源
    《Optical engineering》 |2017年第4期|041313.1-041313.10|共10页
  • 作者

    Todd W. Du Bosq; Bradley L. Preece;

  • 作者单位

    U.S. Army Research, Development and Engineering Command, Communications-Electronics Research, Development and Engineering Center, Night Vision and Electronic Sensors Directorate, Fort Belvoir, Virginia, United States;

    U.S. Army Research, Development and Engineering Command, Communications-Electronics Research, Development and Engineering Center, Night Vision and Electronic Sensors Directorate, Fort Belvoir, Virginia, United States;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    performance modeling; compressive sensing; computational imaging; night vision integrated performance model; single-pixel camera;

    机译：绩效建模;压缩感测计算成像;夜视综合性能模型;单像素相机;

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