Information theoretical assessment of digital imaging systems

Sarah John, Zia Ur Rahman, Friedrich O. Huck, Stephen E. Reichenbach

Research output: Contribution to journalConference article

Abstract

In this paper we are concerned with the end-to-end performance of image gathering, coding, and restoration as a whole rather than a chain of independent tasks. Our approach evolves from the pivotal relationship that exists between the spectral information density of the transmitted signal and the restorability of images from this signal. The information theoretical assessment accounts for (1) the information density and efficiency of the acquired signal as a function of the image-gathering system design and the radiance-field statistics, and (2) the improvement in information efficiency and data compression that can be gained by combining image gathering with coding to reduce the signal redundancy and irrelevancy. The redundancy reduction is concerned mostly with the statistical properties of the acquired signal, and the irrelevancy reduction is concerned mostly with the visual properties of the scene and the restored image. The results of this assessment lead to intuitively appealing insights about the end-to-end performance of image gathering, coding, and restoration. Foremost is the realization that images can be restored with better quality and from less data as the information efficiency of the data is increased, providing that the restoration correctly accounts for the image gathering and coding processes and effectively suppresses the image-display degradations. High information efficiency, in turn, is attained by minimizing image-gathering degradations as well as signal redundancy. Further data compression can often be gained by matching the irrelevancy reduction to a specific restoration filter.

Original languageEnglish (US)
Pages (from-to)53-66
Number of pages14
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume1309
DOIs
StatePublished - Oct 1 1990
EventInfrared Imaging Systems: Design, Analysis, Modeling, and Testing 1990 - Orlando, United States
Duration: Apr 16 1990Apr 20 1990

Fingerprint

Digital Imaging
Imaging System
Imaging systems
Redundancy
Data compression
Image reconstruction
Image coding
Restoration
restoration
coding
redundancy
Degradation
Image Coding
Image Restoration
Data Compression
data compression
Coding
Systems analysis
Display devices
Statistics

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Information theoretical assessment of digital imaging systems. / John, Sarah; Rahman, Zia Ur; Huck, Friedrich O.; Reichenbach, Stephen E.

In: Proceedings of SPIE - The International Society for Optical Engineering, Vol. 1309, 01.10.1990, p. 53-66.

Research output: Contribution to journalConference article

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