Real-Time Aggressive Image Data Compression

Abstract

The objective of the proposed research is to develop reliable algorithms that can achieve aggressive image data compression (with a compression ratio of 60 times or more) for real-time implementation. Typical applications of such algorithms include terrestrial HDTV broadcasting, space communications, and handling and disposing of toxic materials and nuclear wastes with remotely controlled robots. The state-of-the-art techniques are hampered by serious technical barriers of codebook design complexity. The proposed approach is built on a vector quantization (VQ) algorithm recently developed by the PI. The codebook design complexity of this VQ algorithm is only linearly proportional to the codebook size (significantly less than conventional algorithms) and the encoding complexity is independent of codebook size. Highlighting the proposed approach is a piecewise-linear transform preceding VQ based on the concept of entropy partitioning. The novelty of the proposed algorithm is due to the following: (1) introduction of a piecewise-linear transform to VQ so as to retain more input information: (2) exploiting both inter-block and intra-block redundancy, (3) use of parallel distributed network for real-time codebook design. The proposed research is significant as (1) it addresses the imminent demands of solving the aforementioned real-world problems; (2) its accomplishment will alleviate the serious complexity barrier of conventional VQ algorithms; (3) it pushes forward the technical frontiers of data compression.

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Document Details

Document Type
Technical Report
Publication Date
Mar 31, 1990
Accession Number
ADA249364

Entities

People

  • Ruey-wen Liu
  • Yih-fang Huang

Organizations

  • University of Notre Dame

Tags

Communities of Interest

  • Advanced Electronics
  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Adaptive Filters
  • Adaptive Systems
  • Algorithms
  • Artificial Intelligence
  • Coding
  • Computational Complexity
  • Computational Science
  • Computer Programming
  • Computers
  • Data Compression
  • Difference Equations
  • Differential Equations
  • Electrical Engineering
  • Information Retrieval
  • Information Science
  • Information Theory
  • Signal Processing

Fields of Study

  • Computer science
  • Engineering

Readers

  • Image Processing and Computer Vision.
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Space