Color Palette Reduction and Enhancement Techniques

Abstract

The Naval Research Laboratory's Map Data Formatting Facility is developing a seamless, compressed, digital database of the world called the Compressed Aeronautical Chart (CAC). The CAC consists of scanned, aeronautical chart images. The CAC's primary purpose is to support Navy and Marine Corps aircraft mission planning and digital moving map systems. However, other users on various platforms have expressed interest in using the CAC. Therefore, the CAC must be capable of adapting to the graphics capabilities of other platforms. The CAC uses a set of custom color palettes that consists of 240 distinct colors. Each pixel from the precompressed data at full-color(24-bit) indexes to its closest color palette entry as decided by Euclidean distance. Custom color palettes tend to maintain color integrity between the CAC and the original data. Since graphics capabilities vary from platform to platform, the ability to reduce and remap a color palette is a useful tool. This paper describes the technique chosen to remap the CAC color palettes to the desired, reduced set of colors. An enhancement technique that uses a contrast stretch algorithm is also described. The enhancement is achieved by first calculating a given palette's luminance (Y) values. Then a ratio of the contrast stretch luminance to the original luminance is derived for each color in a given color palette.

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Document Details

Document Type
Technical Report
Publication Date
Nov 11, 1993
Accession Number
ADA280793

Entities

People

  • L. Riedlinger
  • M. Gendron
  • M. Trenchard
  • S. Myrick

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Aircrafts
  • Computer Graphics
  • Contrast
  • Databases
  • Display Systems
  • Graphics
  • Images
  • Luminance
  • Maps
  • Marine Corps
  • Marine Corps Aircraft
  • Military Research
  • National Security
  • Numbers
  • Optical Storage
  • Platforms
  • Square Roots

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Computer Vision.
  • Military Logistics and Supply Chain Management