Dependence of image information content on gray-scale resolution

Ram M. Narayanan, T. S. Sankaravadivelu, Stephen E. Reichenbach

Research output: Contribution to conferencePaperpeer-review

8 Scopus citations


Remote sensing images acquired in various spectral bands are used to estimate certain geophysical parameters or detect the presence or extent of geophysical phenomena. In a majority of cases, the raw image acquired by the sensor is processed using various operations such as filtering, compression, enhancement, etc. In performing these operations, the analyst is attempting to maximize the information content in the image to fulfill the end objective. The information content in a remote sensing image for a specific application is greatly dependent on the gray-scale resolution of the image. One of the measures to quantify information content is classification accuracy. Our research reveals that the loss in information is exponential with respect to the number of gray levels. The model is seen to be applicable for Landsat TM and SIR-C images. Using our mathematical model for the information content of images as a function of gray-scale resolution, one can specify an `optimal' gray-scale resolution for an image.

Original languageEnglish (US)
Number of pages3
StatePublished - 2000
Event2000 Interantional Geoscience and Remote Sensing Symposium (IGARSS 2000) - Honolulu, HI, USA
Duration: Jul 24 2000Jul 28 2000


Other2000 Interantional Geoscience and Remote Sensing Symposium (IGARSS 2000)
CityHonolulu, HI, USA

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • General Earth and Planetary Sciences

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