A comparative study of radiometric corrections on multispectral and panchromatic images
Satellite images which are obtained by a
satellite which is not in direct contact with surface but
captures and stores the images in range of
electromagnetic spectrum. Satellite images consists of
numerous distortions or errors which are caused by
many external factors and internal factors. Radiometric
distortions (Spectral Anomalies) are due to errors in
digital number (DN) of image. Radiometric corrections
helps in improving the quality of image by correcting the
DN values which helps in comparative studies and this is
the major step in digital image processing. This study is
carried out using ERDAS imagine software. This study
mainly focused on haze reduction, noise reduction and
periodic noise removal on multispectral data and
panchromatic data. Histograms and accuracy assessment
was carried out to plot the difference between processed
and unprocessed image. Haze removal techniques
demonstrated success compared with noise removal and
periodic noise removal technique which might be due to
absence of noise in the satellite imagery.
corrections-revisited and improved,”
Photogramm. Eng. Remote Sens., vol. 62, no.
9, pp. 1025–1035, 1996.
 Y. Kawata, S. Ueno, and T. Kusaka,
“Radiometric correction for atmospheric and
topographic effects on Landsat MSS images,”
Remote Sens., vol. 9, no. 4, pp. 729–748, 1988.
 L. Paolini, F. Grings, J. A. Sobrino, J. C.
Jiménez Muñoz, and H. Karszenbaum,
“Radiometric correction effects in Landsat
multi-date/multi-sensor change detection
studies,” Int. J. Remote Sens., vol. 27, no. 4,
pp. 685–704, 2006.
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