Patch‐based Texture Interpolation

In this paper, we present a novel exemplar‐based technique for the interpolation between two textures that combines patch‐based and statistical approaches. Motivated by the notion of texture as a largely local phenomenon, we warp and blend small image neighborhoods prior to patch‐based texture synthesis. In addition, interpolating and enforcing characteristic image statistics faithfully handles high frequency detail. We are able to create both intermediate textures as well as continuous transitions. In contrast to previous techniques computing a global morphing transformation on the entire input exemplar images, our localized and patch‐based approach allows us to successfully interpolate between textures with considerable differences in feature topology for which no smooth global warping field exists.     

Semi‐Stochastic Tilings for Example‐Based Texture Synthesis

We investigate semi‐stochastic tilings based on Wang or corner tiles for the real‐time synthesis of example‐based textures. In particular, we propose two new tiling approaches: (1) to replace stochastic tilings with pseudo‐random tilings based on the Halton low‐discrepancy sequence, and (2) to allow the controllable generation of tilings based on a user‐provided probability distribution. Our first method prevents local repetition of texture content as common with stochastic approaches and yields better results with smaller sets of utilized tiles. Our second method allows to directly influence the synthesis result which—in combination with an enhanced tile construction method that merges multiple source textures—extends synthesis tasks to globally‐varying textures. We show that both methods can be implemented very efficiently in connection with tile‐based texture mapping and also present a general rule that allows to significantly reduce resulting tile sets.     

Texture Stationarization: Turning Photos into Tileable Textures

Texture synthesis has grown into a mature field in computer graphics, allowing the synthesis of naturalistic textures and images from photographic exemplars. Surprisingly little work, however, has been dedicated to synthesizing tileable textures, that is, textures that when laid out in a regular grid of tiles form a homogeneous appearance suitable for use in memory‐sensitive real‐time graphics applications. One of the key challenges in doing so is that most natural input exemplars exhibit uneven spatial variations that, when tiled, show as repetitive patterns. We propose an approach to synthesize tileable textures while enforcing stationarity properties that effectively mask repetitions while maintaining the unique characteristics of the exemplar. We explore a number of alternative measures for texture stationarity and show how each measure can be integrated into a standard texture synthesis method (PatchMatch) to enforce stationarity at user‐controlled scales. We demonstrate the efficacy of our approach using a database of 118 exemplar images, both from publicly available sources as well as new ones captured under uncontrolled conditions, and we quantitatively analyze alternative stationarity measures for their robustness across many test runs using different random seeds. In conclusion, we suggest a novel synthesis approach that employs local histogram matching to reliably turn input photographs of natural surfaces into tiles well suited for artifact‐free tiling.     

Self Tuning Texture Optimization

The goal of example‐based texture synthesis methods is to generate arbitrarily large textures from limited exemplars in order to fit the exact dimensions and resolution required for a specific modeling task. The challenge is to faithfully capture all of the visual characteristics of the exemplar texture, without introducing obvious repetitions or unnatural looking visual elements. While existing non‐parametric synthesis methods have made remarkable progress towards this goal, most such methods have been demonstrated only on relatively low‐resolution exemplars. Real‐world high resolution textures often contain texture details at multiple scales, which these methods have difficulty reproducing faithfully. In this work, we present a new general‐purpose and fully automatic self‐tuning non‐parametric texture synthesis method that extends Texture Optimization by introducing several key improvements that result in superior synthesis ability. Our method is able to self‐tune its various parameters and weights and focuses on addressing three challenging aspects of texture synthesis: (i) irregular large scale structures are faithfully reproduced through the use of automatically generated and weighted guidance channels; (ii) repetition and smoothing of texture patches is avoided by new spatial uniformity constraints; (iii) a smart initialization strategy is used in order to improve the synthesis of regular and near‐regular textures, without affecting textures that do not exhibit regularities. We demonstrate the versatility and robustness of our completely automatic approach on a variety of challenging high‐resolution texture exemplars.     

Lazy Solid Texture Synthesis

Existing solid texture synthesis algorithms generate a full volume of color content from a set of 2D example images. We introduce a new algorithm with the unique ability to restrict synthesis to a subset of the voxels, while enforcing spatial determinism. This is especially useful when texturing objects, since only a thick layer around the surface needs to be synthesized. A major difficulty lies in reducing the dependency chain of neighborhood matching, so that each voxel only depends on a small number of other voxels. Our key idea is to synthesize a volume from a set of pre‐computed 3D candidates, each being a triple of interleaved 2D neighborhoods. We present an efficient algorithm to carefully select in a pre‐process only those candidates forming consistent triples. This significantly reduces the search space during subsequent synthesis. The result is a new parallel, spatially deterministic solid texture synthesis algorithm which runs efficiently on the GPU. Our approach generates high resolution solid textures on surfaces within seconds. Memory usage and synthesis time only depend on the output textured surface area. The GPU implementation of our method rapidly synthesizes new textures for the surfaces appearing when interactively breaking or cutting objects.     

EnvyDepth: An Interface for Recovering Local Natural Illumination from Environment Maps

In this paper, we present EnvyDepth, an interface for recovering local illumination from a single HDR environment map. In EnvyDepth, the user quickly indicates strokes to mark regions of the environment map that should be grouped together in a single geometric primitive. From these annotated strokes, EnvyDepth uses edit propagation to create a detailed collection of virtual point lights that reproduce both the local and the distant lighting effects in the original scene. When compared to the sole use of the distant illumination, the added spatial information better reproduces a variety of local effects such as shadows, highlights and caustics. Without the effort needed to create precise scene reconstructions, EnvyDepth annotations take only tens of seconds to produce a plausible lighting without visible artifacts. This is easy to obtain even in the case of complex scenes, both indoors and outdoors. The generated lighting environments work well in a production pipeline since they are efficient to use and able to produce accurate renderings.     

Adaptive Compression of Texture Pyramids

High‐quality texture minification techniques, including trilinear and anisotropic filtering, require texture data to be arranged into a collection of pre‐filtered texture maps called mipmaps. In this paper, we present a compression scheme for mipmapped textures which achieves much higher quality than current native schemes by exploiting image coherence across mipmap levels. The basic idea is to use a high‐quality native compressed format for the upper levels of the mipmap pyramid (to retain efficient minification filtering) together with a novel compact representation of the detail provided by the highest‐resolution mipmap. Key elements of our approach include delta‐encoding of the luminance signal, efficient encoding of coherent regions through texel runs following a Hilbert scan, a scheme for run encoding supporting fast random‐access, and a predictive approach for encoding indices of variable‐length blocks. We show that our scheme clearly outperforms native 6:1 compressed texture formats in terms of image quality while still providing real‐time rendering of trilinearly filtered textures.     

Gamut Mapping Spatially Varying Reflectance with an Improved BRDF Similarity Metric

Recent spatially varying reflectance (svBRDF) printing systems can reproduce an input document as a combination of matte, glossy and metallic inks. Due to the limited number of inks, this reproduction process incurs some distortion. In this work, we present an svBRDF gamut mapping algorithm that minimizes distortions in the angular and spatial domains. To preserve a material's perceived variation with lighting and view, we introduce an improved BRDF similarity metric that builds on both experimental results on reflectance perception and on the statistics of natural lighting environments. Our experiments show better preservation of object color and highlights, as validated quantitatively as well as through a perceptual study. As for the spatial domain, we show how to adapt traditional color gamut mapping methods to svBRDFs. Our solution takes into account the contrast between regions, achieving better preservation of textures and edges.     

An Example-based Procedural System for Element Arrangement

We present a method for synthesizing two dimensional (2D) element arrangements from an example. The main idea is to combine texture synthesis techniques based‐on a local neighborhood comparison and procedural modeling systems based‐on local growth. Given a user‐specified reference pattern, our system analyzes neigh‐borhood information of each element by constructing connectivity. Our synthesis process starts with a single seed and progressively places elements one by one by searching a reference element which has local features that are the most similar to the target place of the synthesized pattern. To support creative design activities, we introduce three types of interaction for controlling global features of the resulting pattern, namely a spray tool, a flow field tool, and a boundary tool. We also introduce a global optimization process that helps to avoid local error concentrations. We illustrate the feasibility of our method by creating several types of 2D patterns.     

Seamless Montage for Texturing Models

We present an automatic method to recover high‐resolution texture over an object by mapping detailed photographs onto its surface. Such high‐resolution detail often reveals inaccuracies in geometry and registration, as well as lighting variations and surface reflections. Simple image projection results in visible seams on the surface. We minimize such seams using a global optimization that assigns compatible texture to adjacent triangles. The key idea is to search not only combinatorially over the source images, but also over a set of local image transformations that compensate for geometric misalignment. This broad search space is traversed using a discrete labeling algorithm, aided by a coarse‐to‐fine strategy. Our approach significantly improves resilience to acquisition errors, thereby allowing simple and easy creation of textured models for use in computer graphics.     

Texture Compression using Wavelet Decomposition

In this paper we introduce a new fixed‐rate texture compression scheme based on the energy compaction properties of a modified Haar transform. The coefficients of this transform are quantized and stored using standard block compression methods, such as DXTC and BC7, ensuring simple implementation and very fast decoding speeds. Furthermore, coefficients with the highest contribution to the final image are quantized with higher accuracy, improving the overall compression quality. The proposed modifications to the standard Haar transform, along with a number of additional optimizations, improve the coefficient quantization and reduce the compression error. The resulting method offers more flexibility than the currently available texture compression formats, providing a variety of additional low bitrate encoding modes for the compression of grayscale and color textures.     

On Neighbourhood Matching for Texture‐by‐Numbers

Texture‐by‐Numbers is an attractive texture synthesis framework, because it is able to cope with non‐homogeneous texture exemplars, and provides the user with intuitive creative control over the outcome of the synthesis process. Like many other exemplar‐based texture synthesis methods, its basic underlying mechanism is neighbourhood matching. In this paper we review a number of commonly used neighbourhood matching acceleration techniques, compare and analyse their performance in the specific context of Texture‐by‐Numbers (as opposed to ordinary unconstrained texture synthesis). Our study indicates that the standard approaches are not optimally suited for the Texture‐by‐Numbers framework, often producing visually inferior results compared to searching for the exact L² nearest neighbour. We then show that performing Texture‐by‐Number using the Texture Optimization framework in conjunction with an efficient FFT‐based search is able to produce good results in reasonable running times and with a minimal memory overhead.     

An Optimal Control Approach for Texture Metamorphosis

In this paper, we introduce a new texture metamorphosis approach for interpolating texture samples from a source texture into a target texture. We use a new energy optimization scheme derived from optimal control principles which exploits the structure of the metamorphosis optimality conditions. Our approach considers the change in pixel position and pixel appearance in a single framework. In contrast to previous techniques that compute a global warping based on feature masks of textures, our approach allows to transform one texture into another by considering both intensity values and structural features of textures simultaneously. We demonstrate the usefulness of our approach for different textures, such as stochastic, semi‐structural and regular textures, with different levels of complexities. Our method produces visually appealing transformation sequences with no user interaction.     

Real‐time Texture Synthesis and Concurrent Random‐access Rendering for Low‐cost GPU Chip Design

Numerous algorithms have been researched in the area of texture synthesis. However, it remains difficult to design a low‐cost synthesis scheme capable of generating high quality results while simultaneously achieving real‐time performance. Additional challenges include making a scheme parallel and being able to partially render/synthesize high‐resolution textures. Furthermore, it would be beneficial for a synthesis scheme to be able to incorporate Texture Compression and minimize the bandwidth usage, especially on mobile devices. In this paper, we propose a practical method which has low computational complexity and produces textures with small storage requirements. Through use of an index table, random access of the texture is another essential advantage, with which parallel rendering becomes feasible including generation of mip‐map sequences. Integrating the index table with existing compression algorithms, for example ETC or PVRTC, the bandwidth is further reduced and avoids the need for a separate, computationally expensive pass to compress the synthesized output. It should be noted that our texture synthesis achieves real‐time performance and low power consumption even on mobile devices, for which texture synthesis has been traditionally considered too expensive.     

Scalable Height Field Self‐Shadowing

We present a new method suitable for general purpose graphics processing units to render self‐shadows on dynamic height fields under dynamic light environments in real‐time. Visibility for each point in the height field is determined as the exact horizon for a set of azimuthal directions in time linear in height field size and the number of directions. The surface is shaded using the horizon information and a high‐resolution light environment extracted on‐line from a high dynamic range cube map, allowing for detailed extended shadows. The desired accuracy for any geometric content and lighting complexity can be matched by choosing a suitable number of azimuthal directions. Our method is able to represent arbitrary features of both high‐ and low‐frequency, unifying hard and soft shadowing. We achieve 23 fps on 1024×1024 height fields with 64 azimuthal directions under a 256×64 environment lighting on an Nvidia GTX 280 GPU.     

Textures on Rank‐1 Lattices

Storing textures on orthogonal tensor product lattices is predominant in computer graphics, although it is known that their sampling efficiency is not optimal. In two dimensions, the hexagonal lattice provides the maximum sampling efficiency. However, handling these lattices is difficult, because they are not able to tile an arbitrary rectangular region and have an irrational basis. By storing textures on rank‐1 lattices, we resolve both problems: Rank‐1 lattices can closely approximate hexagonal lattices, while all coordinates of the lattice points remain integer. At identical memory footprint texture quality is improved as compared to traditional orthogonal tensor product lattices due to the higher sampling efficiency. We introduce the basic theory of rank‐1 lattice textures and present an algorithmic framework which easily can be integrated into existing off‐line and real‐time rendering systems.     

Dominant Texture and Diffusion Distance Manifolds

Texture synthesis techniques require nearly uniform texture samples, however identifying suitable texture samples in an image requires significant data preprocessing. To eliminate this work, we introduce a fully automatic pipeline to detect dominant texture samples based on a manifold generated using the diffusion distance. We define the characteristics of dominant texture and three different types of outliers that allow us to efficiently identify dominant texture in feature space. We demonstrate how this method enables the analysis/synthesis of a wide range of natural textures. We compare textures synthesized from a sample image, with and without dominant texture detection. We also compare our approach to that of using a texture segmentation technique alone, and to using Euclidean, rather than diffusion, distances between texture features.     

Example‐Based Fractured Appearance

A common weathering effect is the appearance of cracks due to material fractures. Previous exemplar‐based aging and weathering methods have either reused images or sought to replicate observed patterns exactly. We introduce a new approach to exemplar‐based modeling that creates weathered patterns on synthetic objects by matching the statistics of fracture patterns in a photograph. We present a user study to determine which statistics are correlated to visual similarity and how they are perceived by the user. We then describe a revised physically‐based fracture model capable of producing a wide range of crack patterns at interactive rates. We demonstrate how a Bayesian optimization method can determine the parameters of this model so it can produce a pattern with the same key statistics as an exemplar. Finally, we present results using our approach and various exemplars to produce a variety of fracture effects in synthetic renderings of complex environments. The speed of the fracture simulation allows interactive previews of the fractured results and its application on large scale environments.     

Topographic Map Visualization from Adaptively Compressed Textures

Raster‐based topographic maps are commonly used in geoinformation systems to overlay geographic entities on top of digital terrain models. Using compressed texture formats for encoding topographic maps allows reducing latency times while visualizing large geographic datasets. Topographic maps encompass high‐frequency content with large uniform regions, making current compressed texture formats inappropriate for encoding them. In this paper we present a method for locally‐adaptive compression of topographic maps. Key elements include a Hilbert scan to maximize spatial coherence, efficient encoding of homogeneous image regions through arbitrarily‐sized texel runs, a cumulative run‐length encoding supporting fast random‐access, and a compression algorithm supporting lossless and lossy compression. Our scheme can be easily implemented on current programmable graphics hardware allowing real‐time GPU decompression and rendering of bilinear‐filtered topographic maps.