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Optimization-Based Multi-scale Texture Synthesis

Authors: Fan Xulong; Chen Zhaojiong;

Optimization-Based Multi-scale Texture Synthesis

Abstract

Multi-scale texture synthesis is a rising research in recent years. There are two shortcomings: First, the exemplar design is very difficult, Second, Multi-scale texture synthesis uses pixel matching. Pixel matching can not capture the big structure information of the texture and it requires significant resources. A new multi-scale texture synthesis algorithm based optimization was proposed. The algorithm designs input exemplar textures using graph structure, constructs an exemplar-relation graph, adopts patch matching synthesis, introduces optimization to keep patch matching properly, and the size of the block can be adjusted and a jitter function was proposed. The algorithm absorbed the random characteristic of the pixel matching, and enhanced synthesis efficiency. Experimental results show that the method is effective.

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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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Average
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