The Integration of Image Segmentation Maps using Region and Edge Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
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This paper investigates the applicability and limitations of combining multi-sensor data through data fusion, to increase the usefulness of the datasets. This study focuses on merging daily mean aerosol optical thickness (AOT), as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, to increase spatial coverage and produce complete fields to facilitate comparison with models and station data. The fusion algorithm used the maximum likelihood (ML) technique to merge the pixel values where available, and then the optimal interpolation method to fill the remaining gaps. The algorithm was applied to a regional AOT subset. The results illustrate that the fusion algorithm can produce complete AOT fields with reasonably good data values and acceptable errors. The cumulative semivariogram (CSV) was found to be sensitive to the spatial distribution and fraction of gap areas and, thus, useful for assessing the sensitivity of the fused data to spatial gaps.