Image Transmission and Coding Based on Human Vision.

Abstract

In recent years more and more attention was paid to digital image processing especially as a result of the development of highly efficient algorithms and also because of technologically better facilities. Concurrently attempts were made to find a mathematical model for human vision to achieve better understanding about that mechanism. Some of the image processing problems that were (and are) tackled are image enhancement, bandwidth reduction, image transmission, etc. Unfortunately very few have taken the mechanism of the human vision into consideration in their processes. This work is an attempt to incorporate the model of human vision in image transmission and coding. An optimal system is developed to transmit a digital image over a noisy channel. The same system is used for image bandwidth reduction utilizing a simple coding scheme which is not based on the knowledge of the statistics of the image in question. The improvement of the optimal system over other similar systems are demonstrated and provide explanation for situations where other systems failed. The model used for transmitting images can be also interpreted as the model of the visual mechanism itself and thus shed some light on human vision from a new interesting aspect.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1975
Accession Number
ADA038696

Entities

People

  • Raphael Jona Rom

Organizations

  • University of Utah

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programming
  • Computer Science
  • Convolution
  • Digital Images
  • Equations
  • Errors
  • Filtration
  • Frequency
  • Frequency Response
  • Image Processing
  • Information Processing
  • Linear Systems
  • Order Statistics
  • Power Spectra
  • Statistics
  • Truncation

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Image Processing and Computer Vision.
  • Systems Analysis and Design