Best Fit Edge Detection For Meteorological Data

Douglas DeMasters; Michael Andrews

doi:10.1117/12.956725

9 January 1979 Best Fit Edge Detection For Meteorological Data

Douglas DeMasters, Michael Andrews

Proceedings Volume 0155, Image Understanding Systems and Industrial Applications I; (1979) https://doi.org/10.1117/12.956725
Event: 22nd Annual Technical Symposium, 1978, San Diego, United States

Abstract

The texture, contrast and "noisiness" of meteorological data belongs to the class of visual images that requires unconventional and non-classical processing techniques. For instance, the digital Laplacian operator cannot be directly applied to these images without further modification. This is vividly portrayed in the application of classical edge, detection techniques to visual images that are very "busy", which tends to amplify the granularity of an image rather than generate useful edge detection. In this paper, a comparative study of classical edge detection techniques is described with actual atmospheric data obtained from geostationary satellite data. These results are compared to novel techniques developed at the Image Processing Center for Atmospheric Studies at Colorado State University.

Citation Download Citation

Douglas DeMasters and Michael Andrews "Best Fit Edge Detection For Meteorological Data", Proc. SPIE 0155, Image Understanding Systems and Industrial Applications I, (9 January 1979); https://doi.org/10.1117/12.956725

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