Lossless compression of map contours by context tree modeling of chain codes

We consider lossless compression of digital contours in map images. The problem is attacked by the use of context-based statistical modeling and entropy coding of the chain codes. We propose to generate an optimal n-ary incomplete context tree by first constructing a complete tree up to a predefined...

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Vydané v:Pattern recognition Ročník 40; číslo 3; s. 944 - 952
Hlavní autori: Akimov, Alexander, Kolesnikov, Alexander, Fränti, Pasi
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford Elsevier Ltd 01.03.2007
Elsevier Science
Predmet:
Applied sciences
Chain code encoding
Coding, codes
Context tree
Contour compression
Exact sciences and technology
Information, signal and communications theory
Signal and communications theory
Telecommunications and information theory
Context tree
Contour compression
Chain code encoding
Coding
Raster
Testing equipment
Entropy codes
Lossless compression
Information rate
Vector method
Modeling
Information transmission
ISSN:0031-3203, 1873-5142
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Shrnutí:We consider lossless compression of digital contours in map images. The problem is attacked by the use of context-based statistical modeling and entropy coding of the chain codes. We propose to generate an optimal n-ary incomplete context tree by first constructing a complete tree up to a predefined depth and creating the optimal tree by pruning out nodes that do not provide improvement in compression. We apply this method for both vector and raster maps. Experiments show that the proposed method gives lower bit rates than the existing methods of chain codes compression for the set of test data.
ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2006.08.005