TY - GEN
T1 - Modified full abundance-constrained spectral unmixing
AU - Wong, Englin
AU - Chang, Chein I.
PY - 2012
Y1 - 2012
N2 - Abundance fully constrained least squares (FLCS) method has been widely used for spectral unmixing. A modified FCLS (MFCLS) was previously proposed for the same purpose to derive two iterative equations for solving fully abundance-constrained spectral unmixing problems. Unfortunately, its advantages have not been recognized. This paper conducts a comparative study and analysis between FCLS and MFCLS via custom-designed synthetic images and real images to demonstrate that while both methods perform comparably in unmixing data, MFCLS edges out FCLS in less computing time.
AB - Abundance fully constrained least squares (FLCS) method has been widely used for spectral unmixing. A modified FCLS (MFCLS) was previously proposed for the same purpose to derive two iterative equations for solving fully abundance-constrained spectral unmixing problems. Unfortunately, its advantages have not been recognized. This paper conducts a comparative study and analysis between FCLS and MFCLS via custom-designed synthetic images and real images to demonstrate that while both methods perform comparably in unmixing data, MFCLS edges out FCLS in less computing time.
UR - http://www.scopus.com/inward/record.url?scp=84875694423&partnerID=8YFLogxK
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U2 - 10.1117/12.979187
DO - 10.1117/12.979187
M3 - Conference contribution
AN - SCOPUS:84875694423
SN - 9780819492791
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - High-Performance Computing in Remote Sensing II
T2 - High-Performance Computing in Remote Sensing II
Y2 - 26 September 2012 through 27 September 2012
ER -