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An edge-list compression scheme for 2-D graphic system

Authors: Yun-Nan Chang; Ting-Chi Tong;

An edge-list compression scheme for 2-D graphic system

Abstract

This paper presents an edge-list compression scheme for the two-dimensional (2D) graphic systems. To fill a 2D graphic object described by complex curve paths, either enormous global edge-table has to be created, or a more economic line-based edge-list can be utilized. The latter approach, however, will sacrifice the rendering quality by approximating the curve using straight-lines. Therefore, this paper proposes a new edge-list structure, which first divides each path of the object into several upward and downward segments. Each segment will then be coded based on the difference vector of neighboring pixels, and the quadrant this vector belongs to. The entire path can be converted into a compact bit-stream. To decode the bit-stream, an additional link-list structure has to be built, which contains the direct access links to the entry points in the bit-stream in order to fetch the local lowest points to produce an active edge-list for each scan line. Our preliminary results show that the proposed scheme can reduce the overall edge-table size by an average factor of 15.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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