Brushables: Example‐based Edge‐aware Directional Texture Painting

In this paper we present Brushables—a novel approach to example‐based painting that respects user‐specified shapes at the global level and preserves textural details of the source image at the local level. We formulate the synthesis as a joint optimization problem that simultaneously synthesizes the interior and the boundaries of the region, transferring relevant content from the source to meaningful locations in the target. We also provide an intuitive interface to control both local and global direction of textural details in the synthesized image. A key advantage of our approach is that it enables a “combing” metaphor in which the user can incrementally modify the target direction field to achieve the desired look. Based on this, we implement an interactive texture painting tool capable of handling more complex textures than ever before, and demonstrate its versatility on difficult inputs including vegetation, textiles, hair and painting media.     

基于PSO的Wang Tiles纹理合成

如何在纹理样图中选择组成Wang Tiles的图像块决定着纹理的合成质量。基于PSO的Wang Tiles纹理合成通过粒子群优化算法在纹理样图中快速搜索边界差异最小的图像块,并用选取的图像块构建Wang Tiles,最后用Wang Tiles纹理合成算法合成纹理。实验表明,该算法合成的纹理具有较少的接缝,比随机选择图像块具有更好的合成效果。     

Image-based synthesis of Chinese landscape painting

This paper describes a new framework for synthesizing chinese landscape painting using an image-ased approach.The framework involves two stages:a preprocessing phase,in which a few brush stroke texture primitivities(BSTP) are collected from samples of hand-made Chinese paintings,and the control picture is constructed to provide color IDs of mountains,and the on-line phases,in which the fog image is synthesized and mountains are “drawn“ by mapping multiple layers of BSTP guided by the control picture.When more complex shading is needed,the shading picture is constructed and used during the BSTP mapping phase.Finally,the synthesized Chinese landscape paintings of a variety of styles are given and they look more close to the hand-made work than those produced with previous modeling methods.     

基于纹理和草图的图像铅笔画绘制

针对目前铅笔画生成方法中的线条不够灵活、纹理缺少方向感的问题,提出了一种基于带方向的纹理和线条草图将一幅图像转换为铅笔画风格的方法。首先,对输入图像进行直方图匹配得到图像的色调图,并将图像分割为多个区域,对每个区域,根据其颜色和形状计算其色调和方向,以此决定铅笔纹理的色调和方向;然后,通过可调整的线性卷积方法得到铅笔画的线条草图;最后,将纹理和草图结合得到铅笔画效果。运用提出的方法对不同类型的自然图像进行了铅笔画的转换,并与已有的线卷积积分方法和基于色调的方法进行了对比。实验结果表明带方向的区域纹理能更好地模拟手工铅笔画纹理的方向,可调整的线条能够更好地模拟手工铅笔画的线条的随意性和灵活性。     

基于多尺度笔刷的分层油画风格化

基于图像的油画风格化绘制是计算机图形学领域非真实感绘制研究的热点之一.为了进一步提高图像油画风格化的质量,提出了一种基于多尺度笔刷的分层图像油画风格化绘制算法.该算法模拟艺术家的油画绘制过程,采用不同尺度的笔刷按照从粗到细的顺序逐层绘制.在每层笔刷绘制中,首先使用增量Voronoi序列采样点和图像切线方向场确定笔刷流线,然后结合笔刷形状与笔刷高度场进行纹理贴图,得到最终的图像油画风格化绘制结果.通过与现有算法比较,文中算法不仅能模拟真实的油画绘制过程,而且生成的油画效果层次感更强,充分体现了图像的结构特征和油画细节.     

Radon transform orientation estimation for rotation invariant texture analysis

This paper presents a new approach to rotation invariant texture classification. The proposed approach benefits from the fact that most of the texture patterns either have directionality (anisotropic textures) or are not with a specific direction (isotropic textures). The wavelet energy features of the directional textures change significantly when the image is rotated. However, for the isotropic images, the wavelet features are not sensitive to rotation. Therefore, for the directional textures, it is essential to calculate the wavelet features along a specific direction. In the proposed approach, the Radon transform is first employed to detect the principal direction of the texture. Then, the texture is rotated to place its principal direction at 0 degrees. A wavelet transform is applied to the rotated image to extract texture features. This approach provides a features space with small intraclass variability and, therefore, good separation between different classes. The performance of the method is evaluated using three texture sets. Experimental results show the superiority of the proposed approach compared with some existing methods.     

Stroke Style Analysis for Painterly Rendering

We propose a novel method that automatically analyzes stroke-related artistic styles of paintings.A set of adaptive interfaces are also developed to connect the style analysis with existing painterly rendering systems, so that the specific artistic style of a template painting can be effectively transferred to the input photo with minimal effort.Different from conventional texture-synthesis based rendering techniques that focus mainly on texture features, this work extracts, analyzes and simulates high-level style features expressed by artists’ brush stroke techniques.Through experiments, user studies and comparisons with ground truth, we demonstrate that the proposed style-orientated painting framework can significantly reduce tedious parameter adjustment, and it allows amateur users to efficiently create desired artistic styles simply by specifying a template painting.     

二元树复小波变换及其在图象方向滤波中的应用

复小波变换虽然具有良好的方向选择性和平移不变性 ,但不具备完全重构性条件 ,而二元树复小波变换(DTCWT)正好解决了这一难题 .在分析二元树复小波分解后的 12个高频子带方向性的基础上 ,利用其良好的方向选择性提出了一种对线形纹理图象进行增强滤波的方法 .该方法借助于小波变换域的方向解析性 ,在各子带中保留图象中各局部主方向的信息而滤除其他方向的噪声 .利用该方法进行滤波还可以避免对信号和噪声频率特性和统计特性进行估计 ,从而大大减小了滤波的复杂程度 .以指纹图象为例的实验结果表明 ,该方法效果较好 ,便于实现 ,尤其适用于噪声特性复杂的纹理图象的滤波 .     

基于GPU加速的保结构纹理合成

提出一种基于Chamfer距离的保结构纹理合成方法。使用Chamfer距离度量纹理结构特征的相似度,在查找匹配块的同时计算纹理在颜色空间和结构特征空间的匹配度,从而解决以往纹理合成中有显著结构特征的纹理容易出现不连续的问题。但是Chamfer距离的计算量很大,而且随着纹理合成图分辨率的提高,计算成本会变得相当高昂以至于难以负担。因此,提出了基于GPU加速的保结构纹理合成方法,通过并行查找匹配块提高合成效率。实验证明本方法既提高了结构纹理的合成质量,又使得保结构纹理方法的合成速度大大提高,且与纹理合成图的分辨率无关。     

Interactive texture design and synthesis from mesh sketches

Geometry mesh introduces user control into texture synthesis and editing, and brings more variations in the synthesized results. But still two problems related remain in need of better solutions. One problem is generating the meshes with desired size and pattern efficiently from easier user inputs. The other problem is improving the quality of synthesized results with mesh information. We present a new two-step texture design and synthesis method that addresses these two problems. Besides example texture, a small piece of mesh sketch drawn by hand or detected from example texture is input to our algorithm. And then a mesh synthesis method of geometry space is provided to avoid optimizations cell by cell. Distance and orientation features are introduced to improve the quality of mesh rasterization. Results show that with our method, users can design and synthesize textures from mesh sketches easily and interactively.     

Image palette: painting style transfer via brushstroke control synthesis

As one kind of technology of style transfer, painting style transfer can be used to render the sample images with a specific art style. With this technology, we can render the target images in the same style as the samples after some computation. We present a new approach of painting style transfer in which such a style transfer artwork is done by simulating the process of creation. We take the sample as a palette where users can select arbitrary contours or textures as the input brush strokes. We then analyze the style feature of the brush strokes and use this feature for synthesis and style transfer along the stroke curves learned from the specified area in target images or target 3D models to get the same painting style as the samples. Based on this approach, we also design and realize the corresponding painting system. The results show that the users can get a style-transferred personalized target image just by using the given sample images with the least interactions.     

毛发的结构造型方法

人物的绘制是当今计算机图形学中的一项重要任务,特别吸引人的是头发的生成技术.头发生成技术的难点在于其精细的形状和庞大的数量.文章针对头发提出了弯曲纹元和三维纹理体的概念,并给出了它们的数学表达式以及对不同发型的描述方法.弯曲纹元和三维纹理体是一般三维纹理的结构.带三维纹理的景物是由弯曲纹元和三维纹理体构成的,三维纹理体可再分成多个弯曲纹元,因而指明了三维纹理空间的结构,并解决了三维纹理曲面的造型问题.文章通过不同例子表明了结构造型方法在描述头发中的应用价值.     

Perspective-aware texture analysis and synthesis

This paper presents a novel texture synthesis scheme for anisotropic 2D textures based on perspective feature analysis and energy optimization. Given an example texture, the synthesis process starts with analyzing the texel (TEXture ELement) scale variations to obtain the perspective map (scale map). Feature mask and simple user-assisted scale extraction operations including slant and tilt angles assignment and scale value editing are applied. The scale map represents the global variations of the texel scales in the sample texture. Then, we extend 2D texture optimization techniques to synthesize these kinds of perspectively featured textures. The non-parametric texture optimization approach is integrated with histogram matching, which forces the global statics of the texel scale variations of the synthesized texture to match those of the example. We also demonstrate that our method is well-suited for image completion of a perspectively featured texture region in a digital photo.     

The Synthesis of Rock Textures in Chinese Landscape Painting

In Chinese landscape painting, rock textures portray the orientation of mountains and contribute to the atmosphere. Many landscape-painting skills are required according to the type of rock. Landscape painting is the major theme of Chinese painting. Over the centuries, masters of Chinese landscape painting developed various texture strokes. Hemp-fiber and axe-cut are two major types of texture strokes. A slightly sinuous and seemingly broken line, the hemp-fiber stroke is used for describing the gentle slopes of rock formations whereas the axe-cut stroke best depicts hard, rocky surfaces. This paper presents a novel method of synthesizing rock textures in Chinese landscape painting, useful not only to artists who want to paint interactively, but also in automated rendering of natural scenes. The method proposed underwrites the complete painting process after users have specified only the contour and parameters.     

艺术风格学习

提出一种基于实例的非真实感图像绘制算法，该算法利用两种纹理合成的基本方法，通过参数调整控制匹配点在结构与细节间的倾向性，把输入样图中的绘画风格传输到目标图片中，实现了自动绘画功能，另外，还提出一种搜索算法，该算法可以在大地加快纹理合成速度，实验证明文中算法十分有效。     

Painterly rendering with content-dependent natural paint strokes

We present a new painterly rendering method that simulates artists’ content-dependent painting process and the natural variation of hand-painted strokes. First, a new stroke layout strategy is proposed to enhance the contrast between large and small paint strokes, which is an important characteristic of hand-painted paintings. Specifically, the input image is partitioned into nonuniform grids according to its importance map, and determined by the grid size, an individually constructed paint stroke is applied in each grid. Second, an anisotropic digital brush is designed to simulate a real paint brush. In particular, each bristle of the digital brush has an individual color, so that strokes rendered by the new brush can have multiple colors and naturally varied textures. Finally, we present a novel method to add lighting effects to the canvas. This lighting imitation method is robust and very easy to implement, and it can significantly improve the quality of rendering. Comparing with traditional painterly rendering approaches, the new method simulates more closely the real painting procedure, and our experimental results show that it can produce vivid paintings with fewer artifacts.     

Synthesis of Color Textures for Multimedia Applications

An algorithm for synthesizing color textures from a small set of parameters is presented in this paper. The synthesis algorithm is based on the 2-D moving average model, and realistic textures resembling many real textures can be synthesized using this algorithm. A maximum likelihood estimation algorithm to estimate parameters from a sample texture is also presented. By combining the estimation and synthesis algorithms, a color texture can be synthesized from a sample texture without human intervention. Using the estimated parameters, a texture larger than the original image can be synthesized from a small texture sample. The synthesis algorithm does not require an expensive iterative algorithm, and the quality of synthesized textures may be acceptable for many multimedia applications. In the experiment, various textures suitable for multimedia applications are synthesized from parameters estimated from real textures.     

Contour-driven Sumi-e rendering of real photos

We propose a sketch-based system for rendering oriental brush strokes on complex shapes. While previous research has focused on methods for converting user-specified trajectories into oriental ink painting (Sumi-e) strokes, we propose an approach that takes as input the contours of complex shapes, estimates automatically the sizes of the brush footprints, their orientations, and the brush trajectory. Then, it renders them into oriental ink paintings. The approach performs in three steps; first complex shapes are decomposed into elementary shapes that can be rendered with a single brush stroke. Second, the brush trajectory estimation is formulated as the minimization of an energy function that measures the quality of the trajectory. Finally, the estimated trajectories are rendered into brush strokes by mapping on them footprint textures scanned from real images. We demonstrate that the proposed contour-driven approach is particularly suitable for converting real images into Sumi-e paintings with minimum interaction. To this end we develop a system where images are either interactively or automatically segmented into elementary shapes and converted into Sumi-e paintings. For the automatic segmentation, we observe that the strokes in Sumi-e paintings are nearly parallel to the edge tangent flow (ETF). We propose a segmentation procedure that is based on clustering the curves obtained by integrating the ETF of real images. Experiments on complex shapes show that the proposed contour-based approach produces a large variety of complex strokes compared to trajectory-based approaches.     

An evolutionary system for near-regular texture synthesis

Near-regular texture is probably among the most difficult to handle in the texture synthesis area, because the synthesis must preserve the holistic structural property and the local randomness simultaneously. In this paper, motivated by the relationship between a near-regular texture image and an evolutionary system, we propose a novel texture synthesis algorithm. By defining individuals with appropriate attributes and behaviors, we convert the texture synthesis problem to an evolution process of an evolutionary system. It can achieve high-quality synthesized results on a large variety of near-regular textures without any extra overhead for memory and pretreatment, and the speed approaches real-time. Moreover, it can be easily generalized to deal with other kinds of textures.