Photographic Assessment of Dark Spots in Night Vision Device Images

Abstract

Visible defects in night vision device (NVD) images, arising from image intensifier (I2) tube defects and dirt on the device's optics, can become more than cosmetic blemishes. They can act as visual distractions and may be large enough to mask critical information pilots need to conduct normal night vision operations. This paper is concerned with the assessment of NVD dark spots. Current methods of assessing dark spots examine only the image intensifier tube, ignoring spots due to dirt and dust introduced during night vision device assembly. Current methods are limited in the size of spot that can be counted and do not address the issue of spot contrast. This paper discusses a photographic method for classifying, locating, and counting dark spots in an assembled night vision device. Also documented in this paper is an experiment to determine an observer's ability to classify round dark spots, conducted as part of an effort to determine the accuracy of the photographic test procedure. To quantify the defects, they were classified by size and then counted. Inspectors used a comparison key as an aid in categorizing dots by size. The defect specification should not exceed the classifiers' visual discrimination capabilities. This study directly examined the dot size classification performance of observers using dots of 3, 4, and 6 minutes of arc (MOA) in diameter.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1998
Accession Number
ADA430299

Entities

People

  • Alan R. Pinkus
  • H. L. Task
  • Peter L. Marasco

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Air Force Research Laboratories
  • Cameras
  • Classification
  • Contrast
  • Data Acquisition
  • Diameters
  • Fungi
  • Luminance
  • Night Vision
  • Night Vision Devices
  • Photographs
  • Photography
  • Specifications
  • Standards
  • Test Methods

Readers

  • Computer Vision.
  • Human-Computer Interaction (HCI).
  • Systems Analysis and Design