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The Sinusoidal Projection: A New Importance in Relation to Global Image Data
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2002
Year
New ImportanceEngineeringSinusoidal ProjectionGeophysical Signal ProcessingHigh Accuracy RatesMulti-resolution MethodSocial SciencesImage AnalysisData ScienceCalibrationGlobal Image DataComputational ImagingGeographic CoordinatesGeodesyCartographyImage FormationSynthetic Aperture RadarMultidimensional Signal ProcessingGeographyInverse ProblemsProjection SystemMedical Image ComputingComputer VisionSpatial VerificationImage CodingDigital PhotogrammetryRemote SensingImage Resolution
The reprojection of image data causes the loss or duplication of original pixel values. This research investigated the feasibility of using the sinusoidal projection for global image database construction. Specifically, reprojection accuracies were tested with geographic latitude and longitude coordinates, and the Hammer-Aitoff, Eckert IV, Mollweide, and sinusoidal projections. Reprojections between these five global projections and the Universal Transverse Mercator (UTM) projection and referencing system were performed using fifty-four sample datasets. A statistical analysis of categorical accuracy, a measure describing the omission of pixel values during reprojection, was conducted. Geographic coordinates and the sinusoidal projection both showed very high accuracy rates (100.0 percent and 99.5 percent respectively) when sample datasets were reprojected from UTM. The geographic coordinates, however, showed very low accuracy (65.3 percent) when sample datasets were reprojected to the UTM projection, while the sinusoidal projection showed the highest accuracy (98.4 percent). The results strongly suggest that the sinusoidal projection is very accurate and efficient for building global image databases.