Contribution of the inter-channel polarimetric coherence for soil classification

Fully polarimetric SAR (POL-SAR) images provide a large amount of information through the four channels HH, VV, HV and VH. They proved to be useful in many applications such as delimiting homogenous areas. Such large amounts of data require robust processing algorithms with minimal supervision and low complexity, especially for classification purposes. Most existing classification algorithms (H/A/alpha for instance) use combinations of some or all the channels as features for classification. In this paper, we present a new approach for polarimetric images classification. We are interested in the information of the inter-channel polarime-tric coherence as a feature element for the classification algorithm. The coherence information is known for being used in multi-temporal acquisitions for its advantage of detecting changes in the scenes during time. It is commonly used in in-terferometry. We want to profit from this information in the case of polarimetric images in order to take advantage of the multi-channel property of the data. This coherence classification approach (reading images, computing the coherence and the classification) will be implemented within the OTB (ORFEO ToolBox), the free software which is dedicated especially for remote sensing imagery processing. The approach is tested using images acquired by the CV-580 airborne near Ottawa, Ontario, Canada.