Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 641-644, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-641-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 641-644, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-641-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

DESPECKLING POLSAR IMAGES BASED ON RELATIVE TOTAL VARIATION MODEL

C. Jiang1,2, X. F. He2, L. J. Yang1, J. Jiang1, D. Y. Wang1, and Y. Yuan1 C. Jiang et al.
  • 1Dept. of Suveying and Geoinformatics, Nanjing University of Posts and Telecommunications, Nanjing, P.R.China
  • 2School of Earth Sciences and Engineering, Hohai University, Nanjing, P.R.China

Keywords: PolSAR, Despeckling, Relative Total Variationl, Wishart Measure, PolRTV

Abstract. Relatively total variation (RTV) algorithm, which can effectively decompose structure information and texture in image, is employed in extracting main structures of the image. However, applying the RTV directly to polarimetric SAR (PolSAR) image filtering will not preserve polarimetric information. A new RTV approach based on the complex Wishart distribution is proposed considering the polarimetric properties of PolSAR. The proposed polarization RTV (PolRTV) algorithm can be used for PolSAR image filtering. The L-band Airborne SAR (AIRSAR) San Francisco data is used to demonstrate the effectiveness of the proposed algorithm in speckle suppression, structural information preservation, and polarimetric property preservation.