TY - GEN
T1 - Speckle removal of multi-polarisation SAR imagery using variational method
AU - Peng, Yaxin
AU - Li, Fang
AU - Qin, Jing
AU - Shen, Chaomin
PY - 2007
Y1 - 2007
N2 - In this paper a new speckle reduction method for multi-polarisation Synthetic Aperture Radar (SAR) is proposed by using a constrained-variational model. Variational method is a new technique for SAR speckle removal. In this paper, we generalize the variational method from single-polarisation SAR into multi-polarisation SAR. For a given multi-polarisation SAR, we could define an energy functional. The energy evolves as the original image changes. When the energy reaches its minimum, the corresponding image is regarded as the desired result. In each channel of the multi-polarisation SAR, the speckle follows a Gamma law with mean μ = 1 and variance σ2 = 1/M for M-look SAR. This statistical information is used to construct the energy functional. Our energy is a regularization term, which is the integral for the norm of image gradient, with constraints coming from each channel. Then we use the variational method and heat flow method to obtain the minimizer of the energy. A three-intensity image (|HH|2, |HV|2 and |VV|2) is used to demonstrate our algorithm. Numerical experiment shows a promising result.
AB - In this paper a new speckle reduction method for multi-polarisation Synthetic Aperture Radar (SAR) is proposed by using a constrained-variational model. Variational method is a new technique for SAR speckle removal. In this paper, we generalize the variational method from single-polarisation SAR into multi-polarisation SAR. For a given multi-polarisation SAR, we could define an energy functional. The energy evolves as the original image changes. When the energy reaches its minimum, the corresponding image is regarded as the desired result. In each channel of the multi-polarisation SAR, the speckle follows a Gamma law with mean μ = 1 and variance σ2 = 1/M for M-look SAR. This statistical information is used to construct the energy functional. Our energy is a regularization term, which is the integral for the norm of image gradient, with constraints coming from each channel. Then we use the variational method and heat flow method to obtain the minimizer of the energy. A three-intensity image (|HH|2, |HV|2 and |VV|2) is used to demonstrate our algorithm. Numerical experiment shows a promising result.
KW - Euler-Lagrange equation
KW - Multi-polarisation SAR
KW - Speckle
KW - Variational method
UR - http://www.scopus.com/inward/record.url?scp=42549115220&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=42549115220&partnerID=8YFLogxK
U2 - 10.1117/12.751621
DO - 10.1117/12.751621
M3 - Conference contribution
AN - SCOPUS:42549115220
SN - 9780819469540
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - MIPPR 2007
T2 - MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications
Y2 - 15 November 2007 through 17 November 2007
ER -