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Mark Andrews
Also published under:M. Andrews
Affiliation
Department of Electrical and Computer Engineering, University of Auckland, Auckland, New Zealand
Topic
Measurement Matrix,Spectral Bands,Total Variation Regularization,Abundance Maps,Hyperspectral Data,Hyperspectral Image Data,Linear Mixed Model,Pure Pixels,Regularization Parameter,Search Direction,Subgradient Method,Adjacent Bands,Alunite,Blind Spectral Unmixing,Blind Technique,Calcite,Complexity Reduction,Compressive Measurements,Computational Expense,Constrained Optimization Problem,Continuous Strategy,Convergence Rate,Convex Optimization,Current Iteration,Differentiable Function,End Of Each Iteration,Endmember Spectra,Endmembers,Equivalency,Factorization,Faster Convergence,Feasible Set,Fraction Of Pixels,Fractional Abundance,Future Iterations,Gradient Descent,Hyperspectral,Image Reconstruction,Invertible,Kaolinite,LU Factorization,Lagrange Multiplier,Line Search,Linear Mixing,Low Complexity,Low-rank Structure,N-FINDR Algorithm,Number Of Materials,Number Of Replacements,Objective Function,
Biography
Mark Andrews (M’86) received the B.E. (Hons.) degree in electrical and electronic engineering and the Ph.D. degree in engineering from the University of Auckland, Auckland, New Zealand, in 1985 and 1990, respectively, where he has been with the Department of Electrical and Computer Engineering since 1990. His research interests include signal processing, hyperspectral image processing, and computer vision. He has served as a Committee Member and the Chairman of the IEEE New Zealand North Branch.