Perceptual image compression for data transmission on the battlefield

José Gerardo González, Mark J.T. Smith, Ingo Hontsch, Lina Karam, Kamesh Namuduri, Harold Szu

Research output: Contribution to journalConference articlepeer-review


This paper treats the compression of Synthetic Aperture Radar (SAR) imagery. SAR images are difficult to compress, relative to natural images, because SAR contains an inherent high frequency speckle. Today's state-of-the-art coders are designed to work with natural images, which have a lower frequency content. Thus, their performance on SAR is under par. In this paper we give an overview performance report on the popular compressions techniques, and investigate three approaches to improve the quality of SAR compression at low-bit rates. First, we look at the design of optimal quantizers which we obtain by training on SAR data. Second, we explore the use of perceptual properties of the human visual system to improve subjective coding quality. Third, we consider the use of a model that separates the SAR image into structural and textural components. The paper concludes with a subjective evaluation of the algortihms based on the CCIR recommendation for the assesment of picture quality.

Original languageEnglish (US)
Pages (from-to)56-67
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Jul 6 1998
EventVisual Information Processing VII 1998 - Orlando, United States
Duration: Apr 13 1998Apr 17 1998


  • Image compression
  • Model-based compression
  • Perceptual coding
  • SAR
  • Subjective quality assessment

ASJC Scopus subject areas

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


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