Scatterometer Image Reconstruction Using Total Variation Regularization

The spaceborne scatterometers which are in operation with a general resolution 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.