Abstract
An algorithm for lossy compression of vector data (vector maps, vector graphics, contours of shapes) was developed. The algorithm is based on optimal polygonal approximation for error measure L 2 and dynamic quantization of the vector data. The algorithm includes optimal distribution of the approximation line segments among the vector objects, optimal polygonal approximation of the objects with dynamic quantization and construction of the optimal variable-rate vector quantizer. The developed algorithm can be used for lossy compression of one-dimensional signals and multidimensional vector data.
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Kolesnikov, A. (2007). Optimal Algorithm for Lossy Vector Data Compression. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2007. Lecture Notes in Computer Science, vol 4633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74260-9_68
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DOI: https://doi.org/10.1007/978-3-540-74260-9_68
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74258-6
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