A New Comparative Study of Radiometric Correction on Satellite Images Using Kalman Filter and Levenberg Marquardt Algorithm


  • Priti Tyagi University of Mumbai
  • Udhav Bhosle University of Mumbai




Satellite Image, Radiometric Correction, Kalman Filter, Levenberg Algorithm, prediction


With the development of satellite and remote sensing techniques, more and more multi-temporal image data from airborne/satellite sensors have been collected and used in huge amounts to monitor the changes in land use and land cover. Radiometric consistency among collected multi-temporal imagery is difficult to maintain, because of variations in sensor characteristics, atmospheric conditions, solar angle, and sensor view angle. Radiometric corrections are used to remove the effects that alter the spectral characteristics of land features, except for actual changes in ground target, becoming mandatory in multi-sensor, multi-date studies. In this paper, a comparative analysis of radiometric correction of satellite images is made between Kalman filter and Levenberg algorithm. In first phase, the satellite images such as Landsat, Liss-3 have been corrected using Kalman filter technique. In the second phase, by using Levenberg algorithm radiometric correction has been performed. After that comparative study is made between the results of both techniques using different performance measures such as completeness, correctness and quality.

Author Biography

Priti Tyagi, University of Mumbai

Electronics Engineering Department



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How to Cite

Tyagi, P., & Bhosle, U. (2014). A New Comparative Study of Radiometric Correction on Satellite Images Using Kalman Filter and Levenberg Marquardt Algorithm. European Journal of Applied Sciences, 2(4), 53–65. https://doi.org/10.14738/aivp.24.421