A robust and fast geometry based unmixing algorithm for hyperspectral imagery

摘要

A geometry based unmixing method is proposed in this paper. A sequential algorithm is used to find a convex cone under the maximum angle criterion. Initialization of this algorithm was improved by an algebra method and its speed was improved with sequential angle subspace updating strategy. In order to demonstrate the performance of the proposed unmixing method, two other unmixing methods, convex cone analysis (CCA) and sequential maximum angle convex cone SMACC, are used for comparison. The experimental results indicate that the proposed method is more robust and faster.