Comparison of absolute and relative radiometric normalization use Landsat time series images

Yong Hu; Liangyun Liu; Lingling Liu; Quanjun Jiao

doi:10.1117/12.902076

23 November 2011 Comparison of absolute and relative radiometric normalization use Landsat time series images

Yong Hu, Liangyun Liu, Lingling Liu, Quanjun Jiao

Proceedings Volume 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 800616 (2011) https://doi.org/10.1117/12.902076
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

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.

Citation Download Citation

Yong Hu, Liangyun Liu, Lingling Liu, and Quanjun Jiao "Comparison of absolute and relative radiometric normalization use Landsat time series images", Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 800616 (23 November 2011); https://doi.org/10.1117/12.902076

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