Appearance-space texture synthesis.

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Analysis of Appearance Space Attributes for Texture ..

27/12/2007 · Title: Texture synthesis using dimensionality-reduced appearance space

Appearance-space texture synthesis

For our first step we implemented Efros and Leung's texture synthesis algorithm. Basically, this algorithm generates texture by looking through the original image and finding regions that match the pixel about to be generated. It does this by comparing a "window" of pixels around the new pixel to every possible window in the original texture and measuring the distance with a gaussian version of sum of square distances weighted toward central pixels in the window. Then, to ensure randomness, it picks a random pixel from those that match within a given error bound. For more details, we recommend reading their paper at Additionally, the code base is online at: . However, if you are interested in exploring the texture-picture blending described below, we found that this version of the code would not handle the changes we needed and ended up coding our own version from scratch. You will probably want to do the same thing.

Hugues Hoppe, Appearance-space texture synthesis, ACM ..

This function is acquired by large number of measurements for all possible combinations of illumination and viewing positions hence some compressed representation of these huge BTF texture data spaces is obviously inevitable.

―Appearance-Space Texture Synthesis…
Appearance Space Texture Synthesis (ASTS) provides fast texture synthesis by example

Texture synthesis using dimensionality-reduced appearance space…

In addition, the aggressively pruned search space results in strong artifacts when synthesizing multiple textures under user guidance (Texture-By-Numbers, TBN).

Sylvain Lefebvre , Hugues Hoppe, Appearance-space texture synthesis, ..

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It synthesizes the noise image using fixedneighborhood searching, and generates a new image of arbitrary size with appearancesimilar to the sample texture.

14/02/2012 · This paper presents an efficient texture synthesis based on ..

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Texture synthesis and morphing are important techniques for efficiently creating realistic and visually attractive textures. A popular class of synthesis algorithm are pixel-based techniques, which search in a given 2D exemplar for a pixel with a similar neighbourhood to the pixel currently being generated. The methods have the advantage that they are fast, they can be easily generalised to higher dimensions, and synthesised textures can be represented as references to the exemplar which allows definition of additional channels, such as displacement maps, at no additional cost. The quality of pixel-based techniques depends on the metric used to compare pixel neighbourhoods. Lefebvre and Hoppe introduced the term appearance space for measures describing pixel neighbourhood similarity. In this paper we introduce new appearance space attributes and evaluate them and existing attributes for texture synthesis and morphing. Our results show that our proposed gradient estimate significantly improves synthesis and morphing quality with little additional cost.