Paper
1 August 2007 Polarization transformation as an algorithm for automatic generalization and quality assessment
Haizhong Qian, Liqiu Meng
Author Affiliations +
Abstract
Since decades it has been a dream of cartographers to computationally mimic the generalization processes in human brains for the derivation of various small-scale target maps or databases from a large-scale source map or database. This paper addresses in a systematic way the polarization transformation (PT) - a new algorithm that serves both the purpose of automatic generalization of discrete features and the quality assurance. By means of PT, two dimensional point clusters or line networks in the Cartesian system can be transformed into a polar coordinate system, which then can be unfolded as a single spectrum line r = f(α), where r and a stand for the polar radius and the polar angle respectively. After the transformation, the original features will correspond to nodes on the spectrum line delimited between 0° and 360° along the horizontal axis, and between the minimum and maximum polar radius along the vertical axis. Since PT is a lossless transformation, it allows a straighforward analysis and comparison of the original and generalized distributions, thus automatic generalization and quality assurance can be down in this way. Examples illustrate that PT algorithm meets with the requirement of generalization of discrete spatial features and is more scientific.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Haizhong Qian and Liqiu Meng "Polarization transformation as an algorithm for automatic generalization and quality assessment", Proc. SPIE 6751, Geoinformatics 2007: Cartographic Theory and Models, 67510Y (1 August 2007); https://doi.org/10.1117/12.759698
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Cited by 2 scholarly publications.
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KEYWORDS
Roads

Polarization

Image segmentation

Detection and tracking algorithms

Algorithm development

Brain mapping

Databases

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