Inversion of imaging mechanisms by regularization of inverse Volterra models
- 作者：Inglada ; Jordi ; Le Caillec ; Jean-Marc ; Garello ; René
- 关键词：Imaging mechanism ; Modeling ; Volterra series expansion ; Inverse probelm ; Regularization ; Nonlinear diffusion filtering
- 刊名：Signal Processing
- 出版年：2004
- 期刊代码：162_01651684
- 类别：et
- 出版时间：June, 2004
- 卷：84
- 期：6
- 页码：1021-1034
- 文件大小：379 K
摘要
An imaging mechanism is defined as the process by which a sensor obtains an image of a physical reality. The inversion of the imaging mechanism can be a solution when one needs to measure some physical magnitude from imaging data. In this paper we propose a general method to model and invert such imaging mechanisms. Our approach consists of building a forward model based on the knowledge of the physical properties of the mechanism. Since imaging mechanisms can be nonlinear, we introduce the Volterra series expansion as a tool for the modeling. In order to illustrate our approach, we apply this technique to the estimation of underwater bottom topography using synthetic aperture radar images of the ocean surface.