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Evaluation of the Accuracy of an Inverse Image-Based Reconstruction Method for Chemical Weather Data

Victor Epitropou, Kostas D. Karatzas, Jaakko Kukkonen, Julius Vira


It is common practice to publish environmental information via the Internet. In the case of geographical coverage information such as pollutant concentration charts and maps in chemical weather forecasts, such data are published as web-resolution images. These forecasts are commonly presented with an associated value-range pseudocolor scale, which represents a simplified version of the original data obtained through, dispersion models and related post-processing methods. In this paper, the numerical and signal processing performance of a method to reconstruct numerical data from the published coverage images is evaluated by comparing the reconstructed data with the original forecast data.


numerical models, image processing, data reconstruction

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