Effects of uncorrelated and correlated noise on image information content

Ram M. Narayanan, Sudhir K. Ponnappan, Stephen E. Reichenbach

Research output: Contribution to conferencePaperpeer-review

8 Scopus citations


The information content in remote sensing imagery depends upon various factors such as spatial and radiometric resolutions, radiometric contrast between different target types, and also the final application for which the imagery has been acquired. Our approach to quantifying image information content is based upon classification accuracy. As noise is added to the image, the classification accuracy reduces, thereby resulting in loss of "information". The relationship between the information content and the noise variance can be described by a negative exponential model. The model is seen to be applicable for relating the information content to noise variance for Landsat TM as well as multi-look and single-look SIR-C imagery. We observe that the relationship is independent of the type of noise (Gaussian, Rayleigh, or Gamma). However, the rate of information loss increases with the correlation distance in the case of spatially correlated noise. The rate of information loss also increases with the number of classes chosen for classifying the scene. The model is useful in deducing allowable signal-to-noise ratios (SNRs) for different sensor systems.

Original languageEnglish (US)
Number of pages3
StatePublished - 2001
Event2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001) - Sydney, NSW, Australia
Duration: Jul 9 2001Jul 13 2001


Conference2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001)
CitySydney, NSW

ASJC Scopus subject areas

  • Computer Science Applications
  • General Earth and Planetary Sciences


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