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Proceedings Paper

Spectrally consistent haze removal in multispectral data
Author(s): Aliaksei Makarau; Rudolf Richter; Rupert Müller; Peter Reinartz
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Paper Abstract

The presence of haze reduces the accuracy of optical data interpretation acquired from satellites. Medium and high spatial resolution multispectral data are often degraded by haze and haze detection and removal is still a challenging and important task. An empirical and automatic method for inhomogeneous haze removal is presented in this work. The dark object subtraction method is further developed to calculate a spatially varying haze thickness map. The subtraction of the haze thickness map from hazy images allows a spectrally consistent haze removal on calibrated and uncalibrated satellite multispectral data. The spectral consistency is evaluated using hazy and haze free remotely sensed medium resolution multispectral data.

Paper Details

Date Published: 23 October 2014
PDF: 7 pages
Proc. SPIE 9244, Image and Signal Processing for Remote Sensing XX, 924422 (23 October 2014); doi: 10.1117/12.2070025
Show Author Affiliations
Aliaksei Makarau, German Aerospace Ctr. (Germany)
Rudolf Richter, German Aerospace Ctr. (Germany)
Rupert Müller, German Aerospace Ctr. (Germany)
Peter Reinartz, German Aerospace Ctr. (Germany)

Published in SPIE Proceedings Vol. 9244:
Image and Signal Processing for Remote Sensing XX
Lorenzo Bruzzone, Editor(s)

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