Analysis of single and multi-channel SAR data using fuzzy logic

Abstract

Two main problems reduce the acceptance of SAR sensors: The huge data rate impairs real-time distribution and the interpretation of SAR images requires special SAR knowledge by the user. While scientific applications will still need the whole amount of data, many users will only consider SAR data for their tasks, if they can access pre-classified data easily and in (near) real-time. Therefore, an application dependent SAR classification has to be applied on the data to extract the required information. Classification will not only simplify data interpretation but it will also lead to a significant data compression. This paper proposes a fuzzy system to build such an adaptive remote sensing classification module. Fuzzy logic allows simple algorithms, gives the system a high tolerance to parameter variations and adaptivity can easily be implemented. One SAR channel classification is described. It allows a user to define interactively the data classes of interest and thus realizes a flexible analysis of SAR data. The system adapts itself to the various user requirements. In many cases one data source does not deliver enough information to perform the required classification. Data fusion of several sensors or various sensor channels has to be taken into account. A new approach is presented for the fusion of the classification results of three SAR polarization channels. The algorithm uses the FLVQ's output of each channel and consists mainly of a fuzzy rule base. This rule base is adaptive to the data sets and to the user requirements.