The performance of image classification techniques as applied to color cartographic maps is compared. These color maps have a lot of graininess due to imperfections in the printing process. This graininess decreases the efficiency of compression techniques. The color maps are classified using the K-means clustering algorithm and vector quantization with neighborhood classification to improve the visual quality and compression ratio. The classification is performed in various image representation schemes. ...
The efficiencies of various data compression techniques as applied to color maps are compared. These color maps have certain special characteristics such as large homogeneous regions and fine detail such as lines and lettering. The color maps are first classified using the K means clustering algorithm with neighborhood classification. Three techniques are investigated - contour, quadtree and run-length coding. The run-length coding algorithm is modified to allow wrap around of ...
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