基于总变分正则化算法的散射计图像重构  

Scatterometer Image Reconstruction Using Total Variation Regularization

作　　者：王倩[1,2] 董晓龙[1] 

机构地区：[1]中国科学院空间科学与应用研究中心中国科学院微波遥感技术重点实验室,北京100190 [2]中国科学院大学,北京100049

出　　处：《电子与信息学报》2014年第9期2244-2250,共7页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(41006109)资助课题

摘　　要：目前业务化运行的星载散射计分辨率一般为25 km,在分辨率需求较高的应用中(如极地海冰监测、热带雨林监测、近岸风场研究等)受到了限制。散射计图像重构技术可以在不改变系统硬件的前提下,通过数据处理方法的改进,提高分辨率。现有的散射计图像重构方法(SIR)是基于图像处理领域中较早期的乘性代数重建技术(MART)。该文针对星载扇形旋转扫描散射计,将一种新的图像重构方法总变分正则化(total variation regularization)算法应用于散射计图像重构,并通过仿真实验说明,新算法可以在增强分辨率的同时减少噪声,提高重构图像的质量。The spaceborne scatterometers which are in operation with a general resoluotion of 25km are already challenged by the higher resolution requirement in some applications, such as polar ice mapping, rainforest mapping and the research of coastal wind. The scatterometer image reconstruction technology can improve the resolution through the data processing method without necessarily changing the system hardwares. The Scatterometer Image Reconstruction （SIR） algorithm that are being used currently is based on an earlier algorithm called Multiplicative Algebraic Reconstruction Technique （MART）. In this paper, a new image reconstruction method is applied to the scatterometer image reconstruction for the rotating fan-beam spaceborne scatterometer called the total variation regularization. The simulation experiments show that the new method can improve the quality of the reconstructed image through both resolution enhancement and noise reduction at the same time.

关 键 词：散射计 图像重构 总变分正则化 

分 类 号：TP732.1[自动化与计算机技术—检测技术与自动化装置]