Analysis of Compression Techniques for Common Mapping Standard (CMS) raster Data

Abstract

Current Common Mapping Standard (CMS) data, produced for the Mission Support System (MSSII) and other fielded systems, are in a spatially and color- reduced format, but are uncompressed. The next generation of CMS data must satisfy the functional, performance and quality requirements of a wide variety of systems from the mission planning, Theater Battle Management (TBM), intelligence and aircraft communities. Previous studies have indicated that a Vector Quantization(VQ) compression approach, combined with spatial downsampling and color reduction, can be implemented to achieve high quality compressed map products. The investigations described in this report use the previous studies as a base for this follow-on VQ compression analysis; further research has been performed in order to define a spatial reduction and VQ compression approach that can support both ground and airborne systems. The report recommends an approach to be used in the reduction and compression of the next generation CMS data that will satisfy the requirements of spatial density, displayed and printed image quality, image format and performance for CMS systems. CMS, Compression.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1994
Accession Number
ADA283396

Entities

People

  • Nancy J. Markuson

Organizations

  • MITRE Corporation

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Algorithms
  • Battle Management
  • Computer Graphics
  • Data Compression
  • Data Processing
  • Digital Images
  • Digital Maps
  • Display Systems
  • Graphics
  • Image Compression
  • Image Processing
  • Navigation
  • Software Development
  • Standards
  • United States

Fields of Study

  • Engineering

Readers

  • Human-Computer Interaction (HCI).
  • Naval Mine Countermeasure Systems Development.
  • Speech Processing/Speech Recognition.