用于互联网成像的SVG渲染

Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05) Pub Date : 2005-07-04 DOI:10.1109/CAMP.2005.51

S. Battiato, G. D. Blasi, G. Gallo, G. Messina, Salvatore Nicotra

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引用次数: 14

摘要

SVG(可缩放矢量图形)标准允许通过一组基于图形矢量的原语来表示复杂的图形场景，与经典栅格图像相比，它提供了几个优势，例如:可伸缩性、分辨率无关性等。在本文中，我们对一些先进的光栅到SVG算法:SWaterG, SVGenie, SVGWave和一些商业工具进行了全面的比较。SWaterG的工作原理是分水岭分解和一些特别的启发式算法，SVGenie和SVGWave分别使用基于数据依赖和小波三角剖分的多面化。SWaterG、SVGenie和SVGWave在感知测量质量和压缩比方面都取得了令人满意的结果。

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SVG rendering for Internet imaging

The SVG (scalable vector graphics) standard allows representing complex graphical scenes by a collection of graphic vectorial-based primitives, offering several advantages with respect to classical raster images such as: scalability, resolution independence, etc. In this paper we present a full comparison between some advanced raster to SVG algorithms: SWaterG, SVGenie, SVGWave and some commercial tools. SWaterG works by a watershed decomposition coupled with some ad-hoc heuristics, SVGenie and SVGWave use a polygonalization based respectively on data dependent and wavelet triangulation. The results obtained by SWaterG, SVGenie and SVGWave are satisfactory both in terms of perceptual measured quality and compression ratio.

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Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)

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