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Proceedings Paper

A relative radiometric correction method for linear array push-broom imagery
Author(s): Hai-chao Li; Hai-feng Song
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Paper Abstract

The linear array CCD camera is the main sensor on the push-broom satellite. Because of the difference response among the CCD detectors, the striping noise is an obvious phenomenon in the remote sensing image along the scanning direction, which can seriously affect the image quality and quantitative application. The object of relative radiometric calibration is to eliminate them. As the state of satellite electronics varies from orbit to orbit, an automatic de-striping algorithm is needed that depends only on information that can be attained from the image data. There are many published techniques that are used to remove striping from images such as the histogram matching, histogram equalization, and Fourier transform filter methods. In order to decrease the effect we try to remove these stripes in CCD images using a relative radiometric correction algorithm based on the adaptive filtering pattern in this paper. Firstly, aiming at the characteristics of strip noise in push-broom scanner, the cause of strip noise formation is described. The suitable 1-D nonlinear filter is chosen to remove the obvious stripping based on the stripping distribution. Then, 1-D smoothing filtering is used to calculate the gain and offset coefficients. At last, the thin stripping is de-striped with the obtained coefficients. The final results indicate that the proposed method can effectively remove the stripping noise along the scanning direction effectively. Comparison of mean value and standard deviations obtained from the strip noise removed image by the proposed method and histogram equalization method suggested that the proposed method is evidently superior to the traditional histogram equalization method in preserving the image detail very well. The result of this study is applicable in striping removal of push-broom satellite's remote sensing data.

Paper Details

Date Published: 18 August 2011
PDF: 8 pages
Proc. SPIE 8194, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, 81941L (18 August 2011); doi: 10.1117/12.900195
Show Author Affiliations
Hai-chao Li, Beijing Institute of Satellite Information Engineering (China)
Hai-feng Song, Beijing Institute of Satellite Information Engineering (China)

Published in SPIE Proceedings Vol. 8194:
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications
Makoto Ikeda; Nanjian Wu; Guangjun Zhang; Kecong Ai, Editor(s)

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