.png){kind=icon}
.png){kind=icon}
Return
Multiple kernels noise for improved procedural texturing
.png){kind=icon}
PRE
AI
DOI：10.1007/s00371-012-0711-2.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Procedural texturing is a well known method to synthesize details onto virtual surfaces directly during rendering. But the creation of such textures is often a long and painstaking task. This paper introduces a new noise function, called multiple kernels noise. It is characterized by an arbitrary energy distribution in spectral domain. Multiple kernels noise is obtained by adaptively decomposing a user-defined power spectral density (PSD) into rectangular regions. These are then associated to kernel functions used to compute noise values by sparse convolution. We show how multiple kernels noise (1) increases the variety of noisy procedural textures that can be modeled and (2) helps creating structured procedural textures by automatic extraction of noise characteristics from user-supplied samples.
Keywords:
Procedural textures
Rendering
Noise-based texturing
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
2.9
Papers:
4.5K
Citations:
6.5K