TY - GEN
T1 - Comparison of absolute and relative radiometric normalization use landsat time series images
AU - Hu, Yong
AU - Liu, Liangyun
AU - Liu, Lingling
AU - Jiao, Quanjun
PY - 2011
Y1 - 2011
N2 - For most remote sense image applications, variations in solar illumination conditions, atmospheric scattering and absorption, and detector performance need to be normalized, especially in time series analysis such as change detection. For the purpose of radiometric correction, two levels of radiometric correction, absolute and relative, have been developed for remote sense imagery. In this paper, we select the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm as the Atmospheric correction method, and compare it with an automatic method for relative radiometric normalization based on a linear scale invariance of the multivariate alteration detection (MAD) transformation. The performances of both methods are compared using a landsat TM image pairs, the results from the two techniques have been compared both visually and using a measure of the fit based on standard error statistic.
AB - For most remote sense image applications, variations in solar illumination conditions, atmospheric scattering and absorption, and detector performance need to be normalized, especially in time series analysis such as change detection. For the purpose of radiometric correction, two levels of radiometric correction, absolute and relative, have been developed for remote sense imagery. In this paper, we select the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm as the Atmospheric correction method, and compare it with an automatic method for relative radiometric normalization based on a linear scale invariance of the multivariate alteration detection (MAD) transformation. The performances of both methods are compared using a landsat TM image pairs, the results from the two techniques have been compared both visually and using a measure of the fit based on standard error statistic.
KW - Atmospheric correction
KW - Landsat TM
KW - Relative radiometric normalization
KW - Time series
UR - http://www.scopus.com/inward/record.url?scp=84255199627&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84255199627&partnerID=8YFLogxK
U2 - 10.1117/12.902076
DO - 10.1117/12.902076
M3 - Conference contribution
AN - SCOPUS:84255199627
SN - 9780819485809
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - MIPPR 2011
T2 - MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Y2 - 4 November 2011 through 6 November 2011
ER -