Paper
28 December 2000 Comparison of different classification algorithms for NOAA AVHRR images
Enrico Piazza
Author Affiliations +
Abstract
In this work four different algorithms for image classification have been applied to AHVRR images coming from the NOAA-14 polar orbiter satellite. The goal is to assign each pixel to one of the following classes: Sea, Land, Cloud, Cloud Edge or Out of the scene. The last class are needed since the images are resampled with always the same geographical limit, thus, sometime, due to satellite being low on the horizon, some pixel can be out of the radiometer view. The first method is based on thresholds on the value of the NDVI (Normalized Differential Vegetation Index) alone. The second method is based on thresholds on 4 of the 5 bands of the AVHRR. The third method is a simple Isodata algorithm on the same 4 bands of the second method and on the same 2 bands of the first method, the ones used to extract the NDVI value. The fourth method is a fuzzy C-Means algorithm on the same set of bands of first and second method. Finally some improvement are proposed and discussed with focus and the actual NOAA-14 images. The results, in terms of computational time, and classification behavior are also discussed. For comparison purposes, the second method, thresholds on 4 of the 5 bands of the AVHRR, is assumed to be the truth and all the results are given with reference to it.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Enrico Piazza "Comparison of different classification algorithms for NOAA AVHRR images", Proc. SPIE 4115, Applications of Digital Image Processing XXIII, (28 December 2000); https://doi.org/10.1117/12.411579
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Cited by 4 scholarly publications.
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KEYWORDS
Clouds

Fuzzy logic

Satellites

Image classification

Radiometry

Satellite imaging

Image segmentation

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