Non-Linear Mapping for Improvement of Display Comprehension of Low Resolution Images

Abstract

This paper describes the development and testing of Nonlinear Display Mapping (NDM), which is high- speed digital signal processing to quickly manipulate displayed images. The identification performance of observers using an automated algorithm and observers using NDM are compared. The observer utilizes NDM to improve image understanding. No algorithm or automatic method can optimize thermal displays for every environment, condition and target. Often, the manual controls are used when "auto mode" does not work well. The commonly available manual brightness and contrast controls are difficult to use and do not fully realize the potential of digital systems. Also, recent experiments showed that the auto mode might combine contrast shades such that targets or target features are hidden from the observer. Current display algorithms employ a wide variety of methods, including histogram equalization, local area processing, and region of interest processing. Non-linear Display Mapping (NDM) differs from these because it allows the user to manipulate the displayed intensity of different regions of the sensor output by real-time non-linear mapping to pixel values. The user can thus allocate or "tune" pixel intensities (gray shades) to output regions expected to contain targets. This avoids squandering the system's limited dynamic range on image features such as cold sky, clouds, trees or water. In other words, NDM enables the user to tune the sensor to the scene.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2002
Accession Number
ADP023108

Entities

People

  • Jeffrey T. Olson
  • John D. O'connor

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Automatic
  • Contrast
  • Detectors
  • Digital Data
  • Digital Signal Processing
  • Histograms
  • Human Factors Engineering
  • Identification
  • Intensity
  • Low Resolution
  • Night Vision
  • Observers
  • Perception
  • Recognition
  • Signal Processing
  • Temperature Gradients

Readers

  • Aviation Science / Aeronautics.
  • Computer Vision.
  • Sensor Fusion and Tracking Systems.