Abstract
The realtime implementation is discussed for several detection and classification techniques: Orthogonal Subspace Projection (OSP), Filter Vector Algorithm (FVA), Generalized Likelihood Ratio Test (GLRT), RX algorithm, Constrained Energy Minimization (CEM), Target Constrained Interference Minimization Filter (TCIMF), and Constrained Linear Discriminant Analysis (CLDA). Two data dimensionality limitations are met in realtime processing. One is the number of classes to be classified cannot be larger than data dimensionality, i.e., the number of spectral bands (for some techniques), and the other is the number of independent pixel vectors used for processing must be larger than the number of bands for a data sample correlation or covariance matrix with full rank (for some techniques). In this paper, we present methods to take care of these two limitations: the former is solved by generating artificial band images to expand the data dimensionality, while the latter is solved by using a positive definite correlation matrix as initial matrix. Experiments using hyperspectral data and multispectral data demonstrate the effectiveness of these methods.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.