SAR Image Super-resolution Based on Regularization of l_k Norm
Wang Xiong-liang, Zhengming Wang, Xia Zhao, Jubo Zhu · Journal of Astronautics · 2005
Enhancing the resolution of SAR image can improve ATR significantly.At present,super-resolution methods of SAR image are mostly based on single frame of SAR image.SAR super-resolution mentioned in this paper indicates the post-processing of SAR images that has been carried out the imaging formation.So that it differ very much from super-resolution methods of SAR imaging,such as modern spectral estimation techniques and data extrapolation techniques etc.One regularization method based on l_k norm used for super-resolution processing of SAR image is discussed in this paper.The observation relationship model is established in the complex image domain.So there is no need to construct the SAR projection operator.Based on parameter selection of Tikhonov regularization,Automatic optimal regularization parameter selection method of l_knorm Regularization is also proposed.Regularization method based on l_k norm exploits the useful prior information which is well consistent to the actual background of SAR imaging,makes up the additional constraint condition which implied sparseness constraint,turns the problem of super-resolution processing of SAR image into the simple-formed constrained optimization problem.The Simulation results and real data computation proves its validity.