Feb 2, 2021 · Abstract: Orthogonal subspace projection (OSP) has been widely used in many applications for hyperspectral data exploitation.
Experiments show that implementing OSP in conjunction with data sphering and LRaSMD significantly improves OSP in target detection and BKG suppression, and also ...
Experiments show that implementing OSP in conjunction with data sphering and LRaSMD significantly improves O SP in target detection and BKG suppression, ...
Sep 27, 2021 · Zhao, “A spectral-spatial method based on low-rank and sparse matrix decomposition for hyperspectral anomaly detection,”. Int. J. Remote Sens ...
Its idea is to implement ATGP on the background (BKG) and target subspaces constructed from the low-rank matrix L and sparse matrix S generated by OSP-GoDec to ...
Orthogonal subspace projection using data sphering and low-rank and sparse matrix decomposition for hyperspectral target detection. IEEE Transactions on ...
PDF | Low-rank and sparsity-matrix decomposition (LRaSMD) has received considerable interests lately. One of effective methods for LRaSMD is called go.
ABSTRACT: Anomaly detection is an active field in the hyperspectral imagery (HSI) processing, which distinguishes anomaly targets from complex backgrounds ...
Missing: Sphering | Show results with:Sphering
Orthogonal subspace projection using data sphering and low-rank and sparse matrix decomposition for hyperspectral target detection. IEEE Trans. Geosci ...
Nov 11, 2022 · This chapter explores two fundamental principles, pigeon-hole principle and orthogonality principle, behind design and development of ...