Abstract: A procedural texture relates texel coordinates to color values through an arbitrary function, herein called a texel shader. The procedural texture is defined by a dimension, size, texel format and the texel shader. Texel coordinates are an input to the texel shader, which generates a color value for those texel coordinates. A renderer can be implemented either in hardware, such as part of a graphics processor, or in software as a computer program executed by a processor. The renderer samples from the procedural texture in response to texel coordinates, and evaluates the texel shader on demand. Filtering also can be applied automatically to results. The results of the texel shader invocations are stored in a texture cache to take advantage of spatial and temporal locality. Results are shared among threads, processes and the like through the texture cache.

Abstract: This paper presents a novel dynamic terrain multiresolution rendering method by utilizing the capabilities of current generation GPUs. Firstly, the terrain depth offset map texture that represents the appropriate offset values is generated through rendering to texture, which is used to deform terrain in vertex shader. Then in order to accurately represent the fine terrain detail created by deformation, an adaptive geometry tessellation technique is implemented in geometry shader. Moreover, to update deformation area texture, we apply procedural texturing based on constraint conditions in fragment shader. In the end, the experiments prove that our method is feasible and efficient.

Abstract: The choice of parameters for procedural textures to achieve a desired appearance poses a challenging problem even for experienced artists. We propose a method to automatically determine such parameters to reproduce the appearance of input images. Addressing two-tone textures, we separate the estimation of color and structure information and interpret the problem as image retrieval task from the space of procedural outputs. Applying a perceptually motivated image metric based on a texture descriptor enables us to precompute a comprehensive collection of possible parameter sets and yet achieve interactive retrieval performance. Our method supports a large variety of procedural texture models with a unified approach.

Abstract: Applying non-linear transfer functions and look-up tables to procedural functions (such as noise), surface attributes, or even surface geometry are common strategies used to enhance visual detail. Their simplicity and ability to mimic a wide range of realistic appearances have led to their adoption in many rendering problems. As with any textured or geometric detail, proper filtering is needed to reduce aliasing when viewed across a range of distances, but accurate and efficient transfer function filtering remains an open problem for several reasons: transfer functions are complex and non-linear, especially when mapped through procedural noise and/or geometry-dependent functions, and the effects of perspective and masking further complicate the filtering over a pixel’s footprint. We accurately solve this problem by computing and sampling from specialized filtering distributions on the fly, yielding very fast performance. We investigate the case where the transfer function to filter is a color map applied to (macroscale) surface textures (like noise), as well as color maps applied according to (microscale) geometric details. We introduce a novel representation of a (potentially modulated) color map’s distribution over pixel footprints using Gaussian statistics and, in the more complex case of high-resolution color mapped microsurface details, our filtering is view- and light-dependent, and capable of correctly handling masking and occlusion effects. Our approach can be generalized to filter other physical-based rendering quantities. We propose an application to shading with irradiance environment maps over large terrains. Our framework is also compatible with the case of transfer functions used to warp surface geometry, as long as the transformations can be represented with Gaussian statistics, leading to proper view- and light-dependent filtering results. Our results match ground truth and our solution is well suited to real-time applications, requires only a few lines of shader code (provided in supplemental material, which can be found on the Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/TVCG.2013.102), is high performance, and has a negligible memory footprint.

Abstract: Gabor noise is a powerful technique for procedural texture generation. Contrary to other types of procedural noise, its sparse convolution aspect makes it easily controllable locally. In this paper, we demonstrate this property by explicitly introducing spatial variations. We do so by linking the sparse convolution process to the parameterization of the underlying surface. Using this approach, it is possible to provide control maps for the parameters in a natural and convenient way. In order to derive intuitive control of the resulting textures, we accomplish a small study of the influence of the parameters of the Gabor kernel with respect to the outcome and we introduce a solution where we bind values such as the frequency or the orientation of the Gabor kernel to a user-provided control map in order to produce novel visual effects.

Abstract: Local random-phase noise is a noise model for procedural texturing. It is defined on a regular spatial grid by local noises, which are sums of cosines with random phase. Our model is versatile thanks to separate sampling in the spatial and spectral domains. Therefore, it encompasses Gabor noise and noise by Fourier series. A stratified spectral sampling allows for a faithful yet compact and efficient reproduction of an arbitrary power spectrum. Noise by example is therefore obtained faster than state-of-the-art techniques. As a second contribution we address texture by example and generate not only Gaussian patterns but also structured features present in the input. This is achieved by fixing the phase on some part of the spectrum. Generated textures are continuous and non-repetitive. Results show unprecedented framerates and a flexible visual result: users can control with one parameter the blending between noise by example and structured texture synthesis.