Presentation + Paper
19 October 2016 Accurate and efficient correction of adjacency effects for high resolution imagery: comparison to the Lambertian correction for Landsat
Author Affiliations +
Proceedings Volume 10001, Remote Sensing of Clouds and the Atmosphere XXI; 100010F (2016) https://doi.org/10.1117/12.2240625
Event: SPIE Remote Sensing, 2016, Edinburgh, United Kingdom
Abstract
The state of the art of atmospheric correction for moderate resolution and high resolution sensors is based on assuming that the surface reflectance at the bottom of the atmosphere is uniform. This assumption accounts for multiple scattering but ignores the contribution of neighboring pixels, that is it ignores adjacency effects. Its great advantage however is to substantially reduce the computational cost of performing atmospheric correction and make the problem computationally tractable. In a recent paper, (Sei, 2015) a computationally efficient method was introduced for the correction of adjacency effects through the use of fast FFT-based evaluations of singular integrals and the use of analytic continuation. It was shown that divergent Neumann series can be avoided and accurate results be obtained for clear and turbid atmospheres. We analyze in this paper the error of the standard state of the art Lambertian atmospheric correction method on Landsat imagery and compare it to our newly introduced method. We show that for high contrast scenes the state of the art atmospheric correction yields much larger errors than our method.
Conference Presentation
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alain Sei "Accurate and efficient correction of adjacency effects for high resolution imagery: comparison to the Lambertian correction for Landsat", Proc. SPIE 10001, Remote Sensing of Clouds and the Atmosphere XXI, 100010F (19 October 2016); https://doi.org/10.1117/12.2240625
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Reflectivity

Atmospheric corrections

Earth observing sensors

Landsat

Image resolution

Transmittance

Visibility

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