On the darkest pixel atmospheric correction algorithm: a revised procedure applied over satellite remotely sensed images intended for environmental applications
Hadjimitsis, Diofantos G, Clayton, Christopher R. and Retalis, Adrianos (2004) On the darkest pixel atmospheric correction algorithm: a revised procedure applied over satellite remotely sensed images intended for environmental applications. In, Ehlers, Manfred, Kauffmann, Hermann J. and Michel, Ulrich (eds.) Remote Sensing for Environmental Monitoring, GIS Applications, and Geology III. Bellingham, USA, Society of Photo-Optical Instrumentation Engineers, 464-471. (Proceedings of SPIE, 5239). (doi:10.1117/12.511520).
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Atmospheric correction is an essential part of the pre-processing of satellite remote sensing data. Several atmospheric correction approaches can be found in the literature ranging from simple to sophisticated methods. The sophisticated methods require auxiliary data, however the simple methods are based only on the image itself and are served to be suitable for operational use. One of the most widely used and well-known simple atmospheric correction methods is the darkest pixel (DP). Despite of its simplicity, the user must be aware of several key points in order to avoid any erroneous results. Indeed, this paper addresses a new strategy for selecting the suitable dark object based on the proposed analysis of digital number histograms and image examination. Several case studies, in which satellite remotely sensed image data intended for environmental applications have been atmospherically corrected using the DP method, are presented in this article.
|Item Type:||Book Section|
|Digital Object Identifier (DOI):||doi:10.1117/12.511520|
|Subjects:||G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography
|Divisions :||University Structure - Pre August 2011 > School of Civil Engineering and the Environment
|Accepted Date and Publication Date:||
|Date Deposited:||11 Aug 2008|
|Last Modified:||31 Mar 2016 12:32|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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