基于约束的多样图纹理合成方法

基于已有的约束的多样图纹理合成算法,提出采用图像金字塔的方法来实现,并在其中利用了纹理的相关性原理,不仅可以合成自然纹理,而且对结构性较强的纹理也取得了较好的效果,合成速度也得到了提高。实验结果表明,该算法在合成质量和合成速度上都有较大的提高,对于控制某种纹理在合成结果图中的位置的纹理合成有广泛的适用性。     

一种基于概周期性的纹理图象分析及合成方法

文章对纹理合成中存在的合成时间过长、合成质量不理想的情况进行分析,发现了对一类具有视觉重复性的纹理,可以利用其本身的性质,加快纹理合成的速度,提高纹理合成的质量。通过对这类纹理特征的研究,引入了概周期纹理的概念,利用固定尺度滑动窗口的灰度距离对其概周期性进行度量,继而采用零搜索技术进行合成。实验证明,对于概周期性纹理,该文提出的算法使得纹理合成速度大大提高,合成质量同于甚至优于传统方法。     

图像的纹理标准性度量及其应用

通过分析纹理合成中子块参数对合成速度及质量的影响,发现对于一类纹理图像,不依赖于参数的选择即可快速高效地进行纹理合成。选择子块灰度平均值作为度量指标,根据纹理标准性强的图像应具有的特征,提出了一种新的计算图像纹理标准性系数的算法。结合大量计算结果,界定了一般图像、强标准性纹理以及弱标准性纹理的分类标准。并将其应用到纹理合成当中,对强标准性纹理图像的合成采用大尺度子块及零搜索的合成方法,提高了合成速度的同时保持合成质量不变。     

基于纹理延伸和三角块拼接的快速曲面纹理合成

对相邻的已合成三角形个数为1的待合成三角形使用"纹理延伸"的方法进行纹理合成;对相邻的已合成三角形个数大于1的待合成三角形采用梯形模板匹配的三角块拼接方法进行纹理合成.实验结果与理论分析表明,该算法合成质量较高,合成速度较现有方法提高了1/3.     

块纹理合成中纹理块尺寸自适应算法

分析了块纹理合成方法中纹理块尺寸对合成结果的影响,经过对大量不同类型纹理图像采样,归纳并验证了纹理相关性特征值与纹理块尺寸之间的关系,得出纹理相关性特征值自适应调整纹理块尺寸的算法.采用该算法可避免因纹理块尺寸选取不当而引起的合成时间的增加和合成质量的降低.     

应用PSO的快速纹理合成算法

应用PSO的快速纹理合成算法是一种高效的纹理合成算法,应用粒子群优化(PSO)算法对基于块采样的纹理合成算法的搜索匹配过程进行了改进,改变了原算法的全遍历搜索过程,在不影响合成质量的前提下加快了合成速度．本算法对于按序和随机的各种应用都能在一台中等的PC机上几秒内合成高质量的纹理．并对算法执行中的粒子数、迭代次数对合成速度和合成效果的影响进行了详细的分析．     

运用局部纹理映射加速曲面纹理合成

基于样图的纹理合成方法能够在网格曲面上合成高质量纹理,但合成速度有待进一步提高,对此提出一种运用局部纹理映射加速曲面纹理合成的算法.首先以三角形法向量、切向矢量与纹理尺度为约束,将三角网格曲面分割为一系列映射区与合成区;然后用基于块的平面纹理合成方法生成大面积样图,用调和映射方法对映射区进行纹理映射;最后采用基于三角块的合成方法生成合成区纹理.实验结果表明,该算法对一般的随机性纹理与半结构性纹理具有很高的合成质量,能够控制纹理方向与尺度的变化.由于大部分三角形的纹理通过局部纹理映射得到,仅需要合成少数三角形的纹理,纹理合成过程得到大幅度地加速.     

螺旋状匹配搜索的块拼贴纹理合成

基于样图的纹理合成方法是继纹理映射、过程纹理合成等方法后发展起来的一种纹理拼贴方法。该文在Efros块拼贴算法和徐晓刚的螺旋状点匹配搜索算法基础上,提出了一种螺旋状匹配搜索的块拼贴算法。该算法利用纹理块的连惯性,在搜索待合成纹理块时,在已合成纹理块在样本图像中位置的邻域进行搜索,找到匹配纹理块后进行输出。该方法大大加快了纹理合成的速度,与Efros块拼贴算法相比,在合成质量不变的基础上,合成速度平均提高了10倍。对于不同的纹理进行实验,其结果也令人满意。     

使用可变大小的邻域进行纹理合成

在许多采用马尔可夫随机场模型的基于样图的纹理合成算法中,邻域的大小决定着这些合成算法的纹理合成质量和合成速度。目前很多纹理合成算法都是在合成前人为选择或通过一定算法来选择邻域尺寸,在合成过程中就使用这个固定大小的邻域来合成纹理,但是固定大小的邻域通常会造成纹理特征混乱。本文提出一种新的纹理合成算法,该算法在合成过程中动态改变邻域大小来避免这个问题。针对每一个输出像素,它的邻域尺寸与这个邻域结构所有像素都相关,是动态改变的。实验表明,在一个较宽的纹理范围内,该算法能够自动为每一输出点自动地识别出理想的邻域大小,生成令人满意的纹理合成效果。     

结合图像细节特征的全局优化纹理合成

提出了一种结合图像细节特征的全局优化纹理合成算法.作者利用非线性分解方法获取纹理细节作为特征图,将其作为纹理图像一个新的信息通道来引导纹理合成.联合图像细节信息通道和颜色通道,在图像上建立了一个全局的纹理合成能量方程,采用最大期望值算法迭代优化求解出一个全局的能量最小值.在全局优化算法中,构建样本纹理和待合成纹理之间的各个信息通道直方图匹配算法,进一步提高纹理合成的质量.文中同时给出了结合细节特征的图像和视频纹理合成算法,实验结果表明,文中的方法较好地解决了纹理合成中合成的纹理图像结构不连续或特征结构容易断裂等问题.     

Modeling and rendering of realistic waterfall scenes with dynamic texture sprites

We propose an efficient approach for authoring dynamic and realistic waterfall scenes based on an acquired video sequence. Traditional video based techniques generate new images by synthesizing 2D samples, i.e., texture sprites chosen from a video sequence. However, they are limited to one fixed viewpoint and cannot provide arbitrary walkthrough into 3D scenes. Our approach extends this scheme by synthesizing dynamic 2D texture sprites and projecting them into 3D space. We first generate a set of basis texture sprites, which capture the representative appearance and motions of waterfall scenes contained in the video sequence. To model the shape and motion of a new waterfall scene, we interactively construct a set of flow lines taking account of physical principles. Along each flow line, the basis texture sprites are manipulated and animated dynamically, yielding a sequence of dynamic texture sprites in 3D space. These texture sprites are displayed using the point splatting technique, which can be accelerated efficiently by graphics hardware. By choosing varied basis texture sprites, waterfall scenes with different appearance and shapes can be conveniently simulated. The experimental results demonstrate that our approach achieves realistic effects and real‐time frame rates on consumer PC platforms. Copyright © 2006 John Wiley & Sons, Ltd.     

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.     

Analysis and Controlled Synthesis of Inhomogeneous Textures

Many interesting real‐world textures are inhomogeneous and/or anisotropic. An inhomogeneous texture is one where various visual properties exhibit significant changes across the texture's spatial domain. Examples include perceptible changes in surface color, lighting, local texture pattern and/or its apparent scale, and weathering effects, which may vary abruptly, or in a continuous fashion. An anisotropic texture is one where the local patterns exhibit a preferred orientation, which also may vary across the spatial domain. While many example‐based texture synthesis methods can be highly effective when synthesizing uniform (stationary) isotropic textures, synthesizing highly non‐uniform textures, or ones with spatially varying orientation, is a considerably more challenging task, which so far has remained underexplored. In this paper, we propose a new method for automatic analysis and controlled synthesis of such textures. Given an input texture exemplar, our method generates a source guidance map comprising: (i) a scalar progression channel that attempts to capture the low frequency spatial changes in color, lighting, and local pattern combined, and (ii) a direction field that captures the local dominant orientation of the texture. Having augmented the texture exemplar with this guidance map, users can exercise better control over the synthesized result by providing easily specified target guidance maps, which are used to constrain the synthesis process.     

Transition Texture Synthesis

Synthesis of transition textures is essential for displaying visually acceptable appearances on a terrain. This investigation presents a modified method for synthesizing the transition texture to be tiled on a terrain. All transition pattern types are recognized for a number of input textures. The proposed modified patch-based sampling texture synthesis approach, using the extra feature map of the input source and target textures for patch matching, can synthesize any transition texture on a succession pattern by initializing the output texture using a portion of the source texture enclosed in a transition cut. The transition boundary is further enhanced to improve the visual effect by tracing out the integral texture elements. Either the Game of Life model or Wang tiles method are exploited to present a good-looking profile of successions on a terrain for tiling transition textures. Experimental results indicate that the proposed method requires few input textures, yet synthesizes numerous tileable transition textures, which are useful for obtaining a vivid appearance of a terrain.     

基于三角块的曲面纹理合成

根据曲面网格上的切向矢量场,采用广度优先搜索策略从样本纹理空间中为每个三角面片映射纹理面片,直至完全覆盖整个网格．在搜索和映射过程中,首先使网格上相邻三角面片的纹理有最小的匹配误差;然后对相邻的三角面片纹理使用图的分割方法拼接纹理,得到曲面上连续的合成纹理;最后压缩存储合成的三角面片纹理．该算法适用于多种类型的样本纹理和任意的三角化曲面．     

Novel approaches for synthesizing video textures

Video texture, a novel type of medium, can produce a new video with a continuously varying stream of images from a recorded video. A classic approach to generate video textures is to apply principal components analysis (PCA) for dimensionality reduction (i.e. extraction of frame signatures) and autoregressive (AR) process for prediction purposes. In this paper we investigate the use of other dimensionality reduction techniques to generate accurate video textures. Based on our experiments, the quality of video textures can be improved further. We also propose a new approach for generating video textures using probabilistic principal components analysis (PPCA) and Gaussian process dynamical model (GPDM) to synthesize video textures which contain frames that never appeared before and with similar motions as original videos. Furthermore, we propose two ways of generating online video textures by applying the incremental Isomap and incremental Spatio-temporal Isomap (IST-Isomap). Both approaches can produce good online video texture results. In particular, IST-Isomap, that we propose, is more suitable for sparse video data (e.g. cartoon).     

基于纹理合成的向量场可视化

在纹理合成过程中利用向量场作为指导,生成反映向量场大小和方向变化的合成结果.采用块纹理合成的流程,在对向量场合成块均匀划分的基础上,通过进一步的自适应分割,将向量场划分成为不同大小和不同形状的最终合成块,使之与向量场的变化趋势相吻合.对向量变化过于剧烈的区域,则采用点合成的方式进行纹理合成,以保证合成效果的平滑.实验表明,文中的方法可以实现快速而高质量的向量场可视化.     

Texture synthesis via the matching compatibility between patches

A new patch-based texture synthesis method is presented in this paper. By the method, a set of patches that can be matched with a sampled patch for growing textures effectively, called the matching compatibility between patches, is generated first for each patch, and the set is further optimized by culling the patches that may cause synthesis conflicts. In this way, similarity measurement calculation for selecting suitable patches in texture synthesis can be greatly saved, and synthesis conflicts between neighbouring patches are substantially reduced. Furthermore, retrace computation is integrated in the synthesis process to improve the texture quality. As a result, the new method can produce high quality textures as texture optimization, the best method to date for producing good textures, and run in a time complexity linear to the size of the output texture. Experimental results show that the new method can interactively generate a large texture in 1024 × 1024 pixels, which is very difficult to achieve by existing methods. Supported by the National Basic Research Program of China (Grant No. 2009CB320802), the National Natural Science Foundation of China (Grant Nos. 60773026, 60833007), the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z306, 2008AA01Z301), and the Research Grant of University of Macau     

基于混洗蛙跳和粒子群优化算法的块自增纹理合成

针对基于样图的纹理合成技术,提出了一种基于混洗蛙跳和粒子群优化算法的块自增纹理合成方法。该方法在纹理合成过程中,通过选取尺寸按2的倍数不断增大的纹理块来提高纹理合成的速度,将混洗蛙跳算法和粒子群算法相结合,作为纹理块匹配的寻优策略,以提高纹理块的查找速度和全局搜索性能。实验结果表明,该方法在保证纹理合成质量的前提下,能够显著地提高基于样图的纹理合成速度,并能克服粒子群算法易陷入局部最优解的缺陷。