SAR Image Targets Superresolution Based on Regularization with Variable Norms

WANG Guang-xin; WANG Zheng-ming

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SAR Image Targets Superresolution Based on Regularization with Variable Norms

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- SAR Image Targets Superresolution Based on Regularization with Variable Norms
- Acta Electronica Sinica Vol. 36, Issue 12, Pages: 2389-2393(2008)
- 作者机构：
  
  1. 国防科学技术大学理学院,湖南,长沙,410073
  2. 桂林空军学院,广西,桂林,541003
  3. 国防科学技术大学理学院湖南长沙,410073
  4. 桂林空军学院广西桂林,541003
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN957
- Published Online：25 December 2008，
  
  Published：2008
- 稿件说明：
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WANG Guang-xin, WANG Zheng-ming. SAR Image Targets Superresolution Based on Regularization with Variable Norms[J]. Acta Electronica Sinica, 2008, 36(12): 2389-2393.
DOI：

WANG Guang-xin, WANG Zheng-ming. SAR Image Targets Superresolution Based on Regularization with Variable Norms[J]. Acta Electronica Sinica, 2008, 36(12): 2389-2393. DOI：

摘要

基于正则化变分的框架

提出了SAR图像目标超分辨的变范数算法.考虑目标在成像区域中的稀疏特性

利用广义高斯分布对目标区域的幅度进行建模

在Bayes估计的框架下

推导了

范数约束的正则化变分模型和广义高斯分布形状参数的关系.采用迭代的方法在逐次估计真实图像的过程中

将

的取值与逐次估计结果相关联

逐步估计目标区域分布的形状参数

并修正

范数的具体形式

由此得到变范数的正则化模型.该方法克服了通过经验选取

值的局限

以及由观测数据估计

值的误差.仿真和实测SAR图像的处理结果表明了该方法的有效性.

Abstract

Based on the framework of regularization variation

we proposed a superresolution algorithm of SAR image targets using variable norms.Considering the sparseness of scatterings in the scene

the generalized Gaussian distribution(GGD) is used to model the amplitude of the targets data.Following Bayesian framework

we deduced the relationship between

norm regularization and the shape parameter of GGD.Under an iterative scheme

we associated the parameter

with the estimated results of each iteration step.The estimated parameter

was then used to modify the model and to construct a superresolution model with variable

norms.Our method overcomes the shortcomings of the fixed

norm regularization m

odel

which selects the parameter

by experience.Finally

we demonstrated the performance of our method on simulated and real SAR scene.Experiments show that the method selects parameter

automatically in an iterative way

and produces super-resolved SAR images.

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