Fast texture synthesis using tree-structured vector quantization

Fast texture synthesis using tree-structured vector quantization (2000)

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by Li-yi Wei , Marc Levoy

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Datum	Value	Source
TITLE	Fast texture synthesis using tree-structured vector quantization	INFERENCE
AUTHOR NAME	Li-yi Wei	SVM HeaderParse 0.2
AUTHOR AFFIL	Stanford University	SVM HeaderParse 0.2
AUTHOR NAME	Marc Levoy	SVM HeaderParse 0.2
AUTHOR AFFIL	Stanford University	SVM HeaderParse 0.2
ABSTRACT	Figure 1: Our texture generation process takes an example texture patch (left) and a random noise (middle) as input, and modifies this random noise to make it look like the given example texture. The synthesized texture (right) can be of arbitrary size, and is perceived as very similar to the given example. Using our algorithm, textures can be generated within seconds, and the synthesized results are always tileable. Texture synthesis is important for many applications in computer graphics, vision, and image processing. However, it remains difficult to design an algorithm that is both efficient and capable of generating high quality results. In this paper, we present an efficient algorithm for realistic texture synthesis. The algorithm is easy to use and requires only a sample texture as input. It generates textures with perceived quality equal to or better than those produced by previous techniques, but runs two orders of magnitude faster. This permits us to apply texture synthesis to problems where it has traditionally been considered impractical. In particular, we have applied it to constrained synthesis for image editing and temporal texture generation. Our algorithm is derived from Markov Random Field texture models and generates textures through a deterministic searching process. We accelerate this synthesis process using tree-structured vector quantization.	SVM HeaderParse 0.2
YEAR	2000	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	479--488	INFERENCE
CITATIONS	28 found	ParsCit 1.0