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A new modelisation of noise in image remote sensing

Author

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  • Granville, V.
  • Rasson, J. P.

Abstract

Instead of considering an additive Gaussian noise, we present a model where the observed image is a mixture of an arbitrary noise process with the true but unknown image. We have obtained consistent estimators for the proportions of the mixture. We have also estimated the distribution of the colours in the true image. The differences between the discrete and the non-discrete case is then discussed. Finally, an application with simulated images is given at the end of the paper.

Suggested Citation

  • Granville, V. & Rasson, J. P., 1992. "A new modelisation of noise in image remote sensing," Statistics & Probability Letters, Elsevier, vol. 14(1), pages 61-65, May.
    • Handle: RePEc:eee:stapro:v:14:y:1992:i:1:p:61-65
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    Cited by:

    1. Granville, V. & Rasson, J. P., 1995. "Bayesian filtering and supervised classification in image remote sensing," Computational Statistics & Data Analysis, Elsevier, vol. 20(2), pages 203-225, August.

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