Landsat TM satellite image restoration using Kalman filter

Danny Arbel, N. S. Kopeika

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


Satellites orbit the Earth and obtain continuous imagery of the ground below along their orbital path. The quality of satellite images propagating through the atmosphere is affected by phenomena such as scattering and absorption of light, and turbulence, which degrade the image by blurring it and reducing its contrast. The atmospheric Wiener filter, which corrects for turbulence blur, aerosol blur, and path radiance simultaneously, is implemented in digital restoration of Landsat TM (Thematic Mapper) imagery. Digital restoration results of Landsat TM imagery using the atmospheric Wiener filter were presented in the past. Here, a new approach for digital restoration of Landsat TM is presented by implementing a Kalman filter as an atmospheric filter, which corrects for turbulence blur, aerosol blur, and path radiance simultaneously. Turbulence MTF is calculated from meteorological data or estimated if no meteorological data were measured. Aerosol MTF is consistent with optical depth. The product of the two yields atmospheric MTF, which is implemented in both the atmospheric Wiener and Kalman filters. Restoration improves both smallness of size of resolvable detail and contrast. Restorations are quite apparent even under clear weather conditions. Here, restorations results of the atmospheric Kalman filter are presented along with those for the atmospheric Wiener filter. A way to determine which is the best restoration result and how good is the restored image is presented by a visual comparison and by considering several mathematical criteria. In general the Kalman restoration is superior, and inclusion of turbulence blur also leads to slightly improved restoration.

Original languageEnglish
Pages (from-to)311-322
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 1 Dec 2001
EventAdvanced Signal Processing: Algorithms, Architectures and Implementations XI - San Diego, CA, United States
Duration: 1 Aug 20013 Aug 2001


  • Adjacency effect
  • Aerosol blur
  • Atmospheric Wiener filter
  • Contrast enhancement
  • Kalman filter
  • MTF
  • Optical depth (thickness)
  • Turbulence blur
  • Vertical imaging

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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