Shape approximation through recursive scalable layer generation

G. Melnikov, A. Katsaggelos
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引用次数: 4

Abstract

This paper presents an efficient recursive algorithm for generating operationally optimal intra mode scalable layer decompositions of object contours. The problem is posed in terms of minimizing the shape distortion at full reconstruction subject to the total (for all scalable layers) bit budget constraint. Based on the chosen vertex-based representation, we solve the problem of determining the number and locations of approximating vertices for all scalable layers jointly and optimally. The number of scalable layers is not constrained, but, rather, is a by-product of the proposed optimization. The algorithm employs two different coding strategies: one for the base layer and one for the enhancement layers. By carefully defining scalable layer recursion and base layer segment costs the problem is solved by executing a directed acyclic graph (DAG) shortest path algorithm.
通过递归可扩展层生成形状逼近
本文提出了一种有效的递归算法,用于生成可操作的最优模式内可扩展的目标轮廓层分解。该问题是在受总(所有可扩展层)比特预算约束的情况下,在完全重建时最小化形状失真。基于所选择的基于顶点的表示,我们联合并最优地解决了确定所有可扩展层的近似顶点的数量和位置的问题。可伸缩层的数量不受限制,而是所提出的优化的副产品。该算法采用两种不同的编码策略:一种用于基础层,一种用于增强层。通过仔细定义可扩展层递归和基础层段代价,通过执行有向无环图(DAG)最短路径算法来解决问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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