A Hybrid Detector for High Resolution Remote Sensing Image Based on Spectral Matching and Tensor Analysis

We proposed a hybrid detector based on spectral matching and tensor analysis, which is designed for hyperspectral and high resolution remote sensing images. Firstly, a spectral matching is performed in vector space using adaptive coherence/cosine estimator (ACE). Then, the result pixels of whose spectral are similar with targets spectral are further processed by support tensor machine (STM) to detect the real targets from the background pixels. The experimental results on CRI dataset demonstrate that the proposed approach could obviously reduce the processing time and improve the targets detection precision.