Fast texture synthesis using tree-structured vector quantization

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. AbstractTexture 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.

4. Rotation invariance in exemplar-based image inpainting

“…This concept was picked up and further analyzed Wei and Levoy [WL00] and justified in terms of probability theory by Levina and Bickel [LB06]. Criminisi et al applied the concept to inpainting problems like object removal in [CPT04].…”

“…6). The algorithms in [EL99,WL00] are greedy methods for the computation of a suitable correspondence map, since each pixel in the inpainting domain is visited only once. As it was shown in [CPT04] the quality of the result heavily depends on the order in which the pixels are processed.…”

“…The non-local exemplar-based approach of [EL99,WL00] has also found applications in other fields of mathematical image processing. In [AW05, KB08, KBC08] the concept has been applied to image denoising and in [GO08] it was used for the regularization of inverse problems in imaging.…”

Physically-Based Surface Texture Synthesis Using a Coupled Finite Element System

“…During the past decade, many example-based texture synthesis methods have been proposed, including parametric methods [12,19,6,7], non-parametric methods [13,14,20,27,28], optimization-based methods [15,10], and appearance-space texture synthesis [16]. In order to synthesize textures over surfaces based on a given texture example, parametric methods attempt to construct a parametric model of the texture.…”

“…Equation (14)(15) can be rewritten into a linear system in Equation (8). The mass matrix, the stiffness matrix and the force vector of Equation (14) are as follows, Similarly, the mass matrix, the stiffness matrix and the force vector of Equation (15) are as follows,…”