26 #ifndef __TERRALIB_INTERNAL_RP_H 27 #define __TERRALIB_INTERNAL_RP_H 43 #include "rp/ClassifierEDStrategy.h
" 44 #include "rp/ClassifierSAMStrategy.h
" 45 #include "rp/ClassifierStrategyFactory.h
" 46 #include "rp/ClassifierStrategy.h
" 48 #include "rp/Contrast.h
" 49 #include "rp/Exception.h
" 50 #include "rp/FeedersRaster.h
" 51 #include "rp/Filter.h
" 52 #include "rp/Functions.h
" 53 #include "rp/GeoMosaic.h
" 54 #include "rp/IHSFusion.h
" 55 #include "rp/Macros.h
" 56 #include "rp/Matrix.h
" 57 #include "rp/MixtureModel.h
" 58 #include "rp/MixtureModelLinearStrategy.h
" 59 #include "rp/MixtureModelPCAStrategy.h
" 60 #include "rp/MixtureModelStrategyFactory.h
" 61 #include "rp/MixtureModelStrategy.h
" 62 #include "rp/Module.h
" 63 #include "rp/PCAFusion.h
" 64 #include "rp/RasterAttributes.h
" 65 #include "rp/RasterHandler.h
" 66 #include "rp/Register.h
" 67 #include "rp/SegmenterDummyStrategy.h
" 68 #include "rp/Segmenter.h
" 69 #include "rp/SegmenterIdsManager.h
" 70 #include "rp/SegmenterRegionGrowingSegment.h
" 71 #include "rp/SegmenterRegionGrowingSegmentsPool.h
" 72 #include "rp/SegmenterRegionGrowingBaatzStrategy.h
" 73 #include "rp/SegmenterRegionGrowingMeanStrategy.h
" 74 #include "rp/SegmenterSegmentsBlock.h
" 75 #include "rp/SegmenterStrategyFactory.h
" 76 #include "rp/SegmenterStrategy.h
" 77 #include "rp/SegmenterStrategyParameters.h
" 78 #include "rp/SequenceMosaic.h
" 79 #include "rp/Skeleton.h
" 80 #include "rp/SpectralResponseFunctions.h
" 81 #include "rp/StrategyParameters.h
" 82 #include "rp/Texture.h
" 83 #include "rp/TiePointsLocator.h
" 84 #include "rp/TiePointsLocatorInputParameters.h
" 85 #include "rp/TiePointsLocatorMoravecStrategy.h
" 86 #include "rp/TiePointsLocatorStrategy.h
" 87 #include "rp/TiePointsLocatorSURFStrategy.h
" 88 #include "rp/TiePointsMosaic.h
" 89 #include "rp/WisperFusion.h
" 90 #include "rp/radar/RadarFunctions.h
" 114 } // end namespace radar
115 } // end namespace rp
116 } // end namespace te
118 #endif // __TERRALIB_INTERNAL_RP_H
Maximum a posteriori probability strategy.
KMeans strategy for image classification.
Blended pixel value calculation for two overlaped rasters.
EM (Expectation-Maximization) strategy for pixel-based classification.
Raster Processing algorithm base interface class.
Performs arithmetic operation over raster data.
Raster Processing algorithm output parameters base interface.
A maximum likelihood estimation strategy for classification (a.k.a. MaxVer in portuguese).
ISOSeg strategy for segmentation-based classification.
Dummy strategy (just for testing purposes).