The orithogonal subspace projection (OSP) method needs all the endmember spectral information of observation area
which is usually unavailable in actual situation. In order to extend the application of OSP method, this paper proposes an
algorithm without any priori information based on OSP. Firstly, the background endmember spectral matrix is obtained by
using unsupervised method. Then, the OSP projection operator is calculated with the background endmember matrix.
Finally, the detection operator is constructed by using the projection operator, which is used to detect the hyperspectral
imagery pixel by pixel. In order to increase the detection rate, local processing is proposed for anomaly detection with no
prior knowledge. The algorithm is tested with AVIRIS hyperspectral data, and binary image of targets and ROC curves are
given in the paper. Experimental results show that the proposed anomaly detection method based on OSP is more effective
than the classic RX detection algorithm under the case of insufficient prior knowledge, and the detection rate is
significantly increased by using the local processing.