  Perspective texture synthesis has great significance in many fields like
video editing, scene capturing etc., due to its ability to read and control
global feature information. In this paper, we present a novel example-based,
specifically energy optimization-based algorithm, to synthesize perspective
textures. Energy optimization technique is a pixel-based approach, so it is
time-consuming. We improve it from two aspects with the purpose of achieving
faster synthesis and high quality. Firstly, we change this pixel-based
technique by replacing the pixel computation with a little patch. Secondly, we
present a novel technique to accelerate searching nearest neighborhoods in
energy optimization. Using k- means clustering technique to build a search tree
to accelerate the search. Hence, we make use of principal component analysis
(PCA) technique to reduce dimensions of input vectors. The high quality results
prove that our approach is feasible. Besides, our proposed algorithm needs
shorter time relative to other similar methods.
