Semantic Source Coding for Flexible Lossy Image Compression

Abstract

Semantic Source Coding for Lossy Video Compression investigates methods for Mission-oriented lossy image compression, by developing methods to use different compression levels for different portions of an image based on their utility in understanding the scene depicted. We have used semantic methods, including pattern discovery, wavelet-based segmentation and texture segmentation to extract the essential predictive information in the image. Described are mission oriented approaches to image pre-processing, image and video segmentation, quality comparison, compression, and two complete systems for lossy video compression.

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Document Details

Document Type
Technical Report
Publication Date
Mar 29, 2007
Accession Number
ADA464658

Entities

People

  • Mendel Schmiedekamp
  • Shashi Phoha

Organizations

  • Pennsylvania State University

Tags

Communities of Interest

  • Autonomy
  • Electronic Warfare
  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Applied Computer Science
  • Artificial Intelligence
  • Coding
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Data Compression
  • Electrical Engineering
  • Formal Languages
  • Image Compression
  • Image Processing
  • Information Operations
  • Language
  • Military Research
  • Recognition
  • Theses

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Image Processing and Computer Vision.