Synthesizing natural textures

Abstract

We present a simple texture synthesis algorithm that is well-suited for a specific class of naturally occurring textures. This class includes quasi-repeating patterns consisting of small objects of familiar but irregular size, such as flower fields, pebbles, forest undergrowth, bushes and tree branches. The algorithm starts from a sample image and generates a new image of arbitrary size the appearance of which is similar to that of the original image. This new image does not change the basic spatial frequencies the original image; instead it creates an image that is a visually similar, and is of a size set by the user. This method is fast and its implementation is straightforward. We extend the algorithm to allow direct user input for interactive control over the texture synthesis process. This allows the user to indicate large-scale properties of the texture appearance using a standard painting-style interface, and to choose among various candidate textures the algorithm can create by performing different number of iterations.

Perceptually inspired real-time artistic style transfer for video stream

“…Ashikhmin [3] proposed a fast texture transfer method, which is an extended version of the local texture synthesis technique [2]. His method effectively transfers the artistic style of the source to the target, requiring only one source image instead of a pair of source images.…”

Texture Deviation Mapping Based on Detail Enhancement

“…From the texture background image's intensity, the deviation map of deviation angles can be generated. Different with the method of Liu [4], this paper advocate the filter operator to preserve the image's detail, such as edge and tone. This method has the exact computational complexity O(N).…”

“…In addition, this technique is easily to implement and the rendering speed is fast. Compared with the other NPR artistic generating methods [4,5], the main advantages of this paper can be summarized as follows: (1)Some details information such as edge and tone can be preserve and appear in the final artistic appearance images. (2)Compared with the deviation mapping generation and bump map, the computation complexity is much cheaper.…”

The Promise and Perils of Near-Regular Texture

“…Existing work on texture synthesis has achieved impressive results for a variety of different types of textures (e.g., De Bonet, 1997;Efros and Leung, 1999;Ashikhmin, 2001;Efros and Freeman, 2001;Hsu and Wilson, 1998;Wei and Levoy, 2000;Hertzmann et al, 2001;Xu et al, 2001;Liang et al, 2001;Zhu et al, 2000;Kwatra et al, 2003;Cohen et al, 2003). These texture synthesis algorithms share a common theme of local neighborhood-based statistical approaches.…”