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Advanced land imager relative gain characterization and correction.

机译:先进的陆地成像仪相对增益表征和校正。

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摘要

Image data obtained from pushbroom sensors such as the Advanced Land Imager (ALI) contains striping artifacts due to mismatches in the response between individual detectors in the array. Characterization and removal of these artifacts is called relative gain correction. Histogram equalization, which uses the first and the second order statistics for each detector, is a common technique used to remove such striping. This approach is valid in the case of whiskbroom sensors where each detector sees the same image information in a statistical sense; however, it is not applicable to pushbroom sensors where each detector does not essentially see the same image information. If however, the range of data is extended over many scenes, this assumption can be used and relative gain can be estimated. Based on this concept, a relative gain characterization algorithm has been developed and implemented which produces corrections equal to or surpassing corrections based on pre-launch estimates of relative gains.
机译:从推扫式传感器(例如Advanced Land Imager(ALI))获得的图像数据包含条纹伪影,这是由于阵列中各个检测器之间的响应不匹配而造成的。这些伪影的表征和去除称为相对增益校正。直方图均衡化,它是每个检测器使用一阶和二阶统计量的一种常用技术,用于消除这种条带化。这种方法在旋转扫帚传感器的情况下是有效的,其中每个探测器在统计意义上都看到相同的图像信息。但是,它不适用于每个探测器基本上看不到相同图像信息的手推扫帚传感器。但是,如果数据范围扩展到许多场景,则可以使用此假设并可以估计相对增益。基于此概念,已经开发并实施了相对增益表征算法,该算法根据发射前相对增益估算产生的校正等于或超过校正值。

著录项

  • 作者

    Angal, Amit.;

  • 作者单位

    South Dakota State University.;

  • 授予单位 South Dakota State University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 M.S.
  • 年度 2005
  • 页码 93 p.
  • 总页数 93
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

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