The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-3/W12-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 141–146, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-141-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 141–146, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-141-2020

  05 Nov 2020

05 Nov 2020

SPECKLE NOISE REDUCTION IN SAR IMAGES USING INFORMATION THEORY

D. Chan1, J. Gambini2, and A. C. Frery3 D. Chan et al.
  • 1Universidad Tecnológica Nacional, Facultad Regional Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina
  • 2Departamento de Ingeniería Informática, Instituto Tecnológico de Buenos Aires, Buenos Aires, Argentina and Depto. de Ingeniería en Computación, Universidad Nacional de Tres de Febrero, Pcia. de Buenos Aires, Argentina
  • 3Laboratório de Computação Científica e Análise Numérica, Universidade Federal de Alagoas, Brazil

Keywords: speckle filter, h-ϕ Entropies, asymptotic variance

Abstract. In this work, a new nonlocal means filter for single-look speckled data using the Shannon and Rényi entropies is proposed. The measure of similarity between a central window and patches of the image is based on a statistical test for comparing if two samples have the same entropy and hence have the same distribution.

The results are encouraging, as the filtered image has better signal-to-noise ratio, it preserves the mean, and the edges are not severely blurred.