Paper
14 December 2015 An improved dark-object subtraction technique for atmospheric correction of Landsat 8
Huimei Ding, Junsheng Shi, Yuanfangzhou Wang, Li Wei
Author Affiliations +
Proceedings Volume 9815, MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 98150K (2015) https://doi.org/10.1117/12.2205567
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China
Abstract
An improved Dark Object Subtraction (DOS) method was introduced for Landsat 8 multispectral satellite image in this paper. The main factors including Rayleigh scattering, Mie scattering in path radiance, as well as the other satellite image parameters (such as height modification, slope distance and azimuth), ware considered in the algorithm. The algorithm consists of three steps. First, starting band haze values are selected using histogram of a single image. Then predicted haze values were calculated using a known scattering model and the multispectral normalized gains and offset values. Finally, final predicted haze values are obtained by the predicted haze values and haze values. Compared with other improved Dark Object Subtraction methods, the result of this algorithm is more realistic on geographical object recognition on NDVI (Normalized Difference Vegetation Index) and NDWI (Normalized Difference Water Index) data.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Huimei Ding, Junsheng Shi, Yuanfangzhou Wang, and Li Wei "An improved dark-object subtraction technique for atmospheric correction of Landsat 8", Proc. SPIE 9815, MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 98150K (14 December 2015); https://doi.org/10.1117/12.2205567
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Cited by 8 scholarly publications.
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KEYWORDS
Scattering

Earth observing sensors

Air contamination

Landsat

Mie scattering

Atmospheric corrections

Atmospheric modeling

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