Texture Synthesis Efros & Leung's Algorithm
Exemplar-based Texture Synthesis: the Efros-Leung Algorithm
However, as I will demonstrate, it is impractical to use so small window, whichmay not find the undergoing stochastic property (This is also discussed inEfros’s paper).Figure 2To have an idea about howlarge the matching window should be, we test our algorithm for synthesizingbrick texture.
Alexei A. Efros homepage - EECS at UC Berkeley
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.