TY - GEN
T1 - A multichannel approach to metric-based SAR autofocus
AU - Morrison, Robert L.
AU - Do, Minh N.
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2005
Y1 - 2005
N2 - The autofocus problem in synthetic aperture radar (SAR) is con sidered. We precisely characterize the multichannel nature or the SAR autofocus problem by constructing a low-dimensional subspace where the perfectly-focused image resides. To obtain a unique solution, we perform a sharpness optimization within this subspace. The subspace characterization enables the sharpness optimization to be performed in a vector space, which is conceptually simpler, and allows the SAR autofocus problem to be cast into a similar framework with other image restoration problems where fast algorithms and efficient methods have been established. We present experimental results demonstrating that the proposed framework can be used to bring the ideas of blind multichannel deconvolution techniques to the SAR autofocus problem, allowing the dimension of the solution subspace to be reduced further.
AB - The autofocus problem in synthetic aperture radar (SAR) is con sidered. We precisely characterize the multichannel nature or the SAR autofocus problem by constructing a low-dimensional subspace where the perfectly-focused image resides. To obtain a unique solution, we perform a sharpness optimization within this subspace. The subspace characterization enables the sharpness optimization to be performed in a vector space, which is conceptually simpler, and allows the SAR autofocus problem to be cast into a similar framework with other image restoration problems where fast algorithms and efficient methods have been established. We present experimental results demonstrating that the proposed framework can be used to bring the ideas of blind multichannel deconvolution techniques to the SAR autofocus problem, allowing the dimension of the solution subspace to be reduced further.
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U2 - 10.1109/ICIP.2005.1530244
DO - 10.1109/ICIP.2005.1530244
M3 - Conference contribution
AN - SCOPUS:33749627741
SN - 0780391349
SN - 9780780391345
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 1070
EP - 1073
BT - IEEE International Conference on Image Processing 2005, ICIP 2005
T2 - IEEE International Conference on Image Processing 2005, ICIP 2005
Y2 - 11 September 2005 through 14 September 2005
ER -