Imperfection for realistic image synthesis

Creating objects with surface imperfections is accomplished through texture specification and generation techniques. Based on fractal subdivision techniques and relatively simple distribution models, a wide class of surface imperfections may be generated, combined and rendered. The surface effects include scratches, splotches, smudges, corrosion, mould, stains and rust. A rule-based system is used to position the various surface imperfections on the texture map, and a simple natural language interface is used to specify the kinds of imperfections and their generative parameters through adverbs and prepositional phrases. Results along some of the imperfection dimensions are illustrated.     

A spectrally based framework for realistic image synthesis

Published online: 2 October 2001     

PERIS: A programming environment for realistic image synthesis

A computer graphics system called PERIS is described. It offers two levels of user interfaces to serve both as a testbed to facilitate further research work and as a pragmatic system for CAD/CAM applications. Flexibility of the system is achieved by providing tools of solid modeling, surface modeling and procedural model representations for physical environment modeling and by including interfaces of immediate display, scan line rendering, ray tracing and two-way ray tracing for realistic image synthesis. A linear octree data structure is established to support the modeling and rendering processes, greatly reducing the computations involved. Meanwhile, we also introduce a new illumination model which unifies most of the existing models on a theoretical basis. An improved Cook-Torrance model is then derived. By examining the merits and limitations of the classic ray tracing methods, we propose a new rendering technique of two-way ray tracing that allows more accurate simulation of light propagation in the environment.     

Full-spectral color calculations in realistic image synthesis

The standard RGB color model manifests color errors when rendering or imaging metameric objects. In this article, we review some alternative color representation methods for accurate color image synthesis     

Colour volumetric compression for realistic view synthesis applications

Colour volumetric data, which is constructed from a set of multi-view images, is capable of providing realistic immersive experience. However it is not widely applicable due to its manifold increase in bandwidth. This paper presents a novel framework to achieve scalable volumetric compression. Based on wavelet transformation, data rearrangement algorithm is proposed to compact volumetric data leading to high efficiency of transformation. The colour data is rearranged using the characteristics of human visual system. A pre-processing scheme for adaptive resolution is also proposed in this paper. The low resolution overcomes the limitation of the data transmission at low bitrates, whilst the fine resolution improves the quality of the synthesised images. Results show significant improvement of the compression performance over the traditional 3D coding. Finally, effect of using residual coding is investigated in order to show a trade off between the compression and view synthesis performance.     

Algorithms for rendering realistic terrain image sequences and their parellel implementation

We present algorithms for rendering realistic images of large terrains and their implementation on a parallel computer for rapid production of terrain-animation sequences. “Large” means datasets too large for RAM. A hybrid ray-casting and projection technique incorporates quadtree subdivision techniques and filtering using precomputed bit masks. Hilbert space-filling curves determine the imagepixel rendering order. A parallel version of the algorithm is based on a Meiko parallel computer architecture, designed to relieve dataflow bottlenecks and exploit temporal image coherence. Our parallel system, incorporating 26 processors, can generate a full color-terrain image at video resolution (without noticable aliasing artifacts) every 2 s, including I/O and communication overheads.     

基于复用计算的大纹理实时合成

文中提出一种基于复用计算的纹理合成方法,逐步地利用已合成的部分纹理来生成更大的纹理块,以进行后续的纹理合成计算.由此,该方法可节省大量耗时的纹理块选择及缝合计算,提高了合成效率.实验表明,新方法可实时合成2048×2048像素的大纹理,而已有工作至多只能以交互的速度进行这样的合成.     

Testing of systems for illumination simulation and synthesis of realistic images

Testing technologies for software systems of optical simulation and realistic computer graphics developed at the Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, are described. The complexity of the products developed (which consist of about 500 software components) and the need to produce a large number of versions (from 50 to 70 versions a year) require the development of an own testing system that would allow one to effectively detect errors and correct them before product release. The testing of computer graphics products has its own specificity, which is the focus of the present study.     

Dynamic Textures

Dynamic textures are sequences of images of moving scenes that exhibit certain stationarity properties in time; these include sea-waves, smoke, foliage, whirlwind etc. We present a characterization of dynamic textures that poses the problems of modeling, learning, recognizing and synthesizing dynamic textures on a firm analytical footing. We borrow tools from system identification to capture the essence of dynamic textures; we do so by learning (i.e. identifying) models that are optimal in the sense of maximum likelihood or minimum prediction error variance. For the special case of second-order stationary processes, we identify the model sub-optimally in closed-form. Once learned, a model has predictive power and can be used for extrapolating synthetic sequences to infinite length with negligible computational cost. We present experimental evidence that, within our framework, even low-dimensional models can capture very complex visual phenomena.     

Textures revisited

We describe texture generation methods for complex objects. Recently developed 3D scanning devices and high-resolution cameras can capture the complex geometry of an object and yield high-resolution images. However, generating a textured model from this input data is still a difficult problem. This task is divided into three subproblems: parameterization, texture combination, and texture restoration. A low-distortion parameterization method is presented, which minimizes geometry stretch energy. Photographs of the object taken from multiple viewpoints under modestly uncontrolled illumination conditions are merged into a seamless texture using our new texture combination method. We also demonstrate a texture restoration method that can fill in missing pixel information when the input photographs do not provide sufficient information to cover the entire surface due to self-occlusion or registration errors. Our methods are fully automatic, except for the registration process between a 3D model and input photographs. We demonstrate the application of our method to human face models for evaluation. The techniques presented in this paper make a consistent and complete pipeline to generate the texture of a complex object.     

Analysis of traditional and modern image encryption algorithms under realistic ambience

Multimedia Tools and Applications - Cryptography (encryption/decryption) is one of the prevailing mechanisms for protection of information (data or image) in the growing era of computerized...     

Floating Textures

We present a novel multi‐view, projective texture mapping technique. While previous multi‐view texturing approaches lead to blurring and ghosting artefacts if 3D geometry and/or camera calibration are imprecise, we propose a texturing algorithm that warps (“floats”) projected textures during run‐time to preserve crisp, detailed texture appearance. Our GPU implementation achieves interactive to real‐time frame rates. The method is very generally applicable and can be used in combination with many image‐based rendering methods or projective texturing applications. By using Floating Textures in conjunction with, e.g., visual hull rendering, light field rendering, or free‐viewpoint video, improved rendering results are obtained from fewer input images, less accurately calibrated cameras, and coarser 3D geometry proxies.     

Automatic image matting and fusing for portrait synthesis

We propose an automatic image matting and fusing system for portrait synthesis in this study.We firstly use a face de-tection algorithm to determine if the inpu...     

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.     

Occlusion Textures for Plausible Soft Shadows*

This paper presents a new approach to compute plausible soft shadows for complex dynamic scenes and rectangular light sources. We estimate the occlusion at each point of the scene using prefiltered occlusion textures, which dynamically approximate the scene geometry. The algorithm is fast and its performance independent of the light's size. Being image‐based, it is mostly independent of the scene complexity and type. No a priori information is needed, and there is no caster/receiver separation. This makes the method appealing and easy to use.     

Level of Detail for Precomputed Procedural Textures

Programming and Computer Software - In this paper we address the problem of determining the detail level of precomputed procedural textures for photorealistic rendering. We propose an approach...     

Layered Dynamic Textures

A novel video representation, the layered dynamic texture (LDT), is proposed. The LDT is a generative model, which represents a video as a collection of stochastic layers of different appearance and dynamics. Each layer is modeled as a temporal texture sampled from a different linear dynamical system. The LDT model includes these systems, a collection of hidden layer assignment variables (which control the assignment of pixels to layers), and a Markov random field prior on these variables (which encourages smooth segmentations). An EM algorithm is derived for maximum-likelihood estimation of the model parameters from a training video. It is shown that exact inference is intractable, a problem which is addressed by the introduction of two approximate inference procedures: a Gibbs sampler and a computationally efficient variational approximation. The trade-off between the quality of the two approximations and their complexity is studied experimentally. The ability of the LDT to segment videos into layers of coherent appearance and dynamics is also evaluated, on both synthetic and natural videos. These experiments show that the model possesses an ability to group regions of globally homogeneous, but locally heterogeneous, stochastic dynamics currently unparalleled in the literature.     

Depth-guided asymmetric CycleGAN for rain synthesis and image deraining

Based on supervised learning, most of the existing single image deraining networks are trained on paired images including one clean image and one rain image. Since it is difficult to obtain a sufficient number of paired images, most of the rain images are manually synthesized from the clean ones. However, it costs huge time and effort, and requires professional experience to mimic the real rain images well. Moreover, the superior performance of these deraining networks trained on manually synthetic rain images is hard to be maintained when tested on real rain images. In this work, to obtain more realistic rain images for training supervised deraining networks, the depth-guided asymmetric CycleGAN (DA-CycleGAN) is proposed to translate clean images to their rainy counterparts automatically. Due to the cycle consistency strategy, DA-CycleGAN can also implement the single image deraining task unsupervised while synthesizing rain on clean images. Since rain streaks and rain mist vary with depth from the camera, DA-CycleGAN adopts depth information as an aid for rain synthesis and deraining. Furthermore, we design generators with different architectures for these two processes due to the information asymmetry in rain synthesis and deraining. Extensive experiments indicate that the DA-CycleGAN can synthesize more lifelike rain images and provide commensurate deraining performance compared with the state-of-the-art deraining methods.

     

一种基于纹理合成的高效图像填充方法

为了更好地解决图像填充与修复问题,提出了一种基于图像样本纹理合成的新方法。该方法提出了一种新的定义像素点优先级的思路,来确定待填充区域的填充顺序,以此来保证处理结果的质量。相较于其他图像填充算法,该算法无需复杂的数学模型和大量的计算过程,从而提高了运算速度。实验证明,该方法不仅在处理效率上取得了很大进步,而且输出图像的质量也取得了理想效果。     

A framework for holographic scene representation and image synthesis

We present a framework for the holographic representation and display of graphics objects. As opposed to traditional graphics representations, our approach reconstructs the light wave reflected or emitted by the original object directly from the underlying digital hologram. Our novel holographic graphics pipeline consists of several stages including the digital recording of a full-parallax hologram, the reconstruction and propagation of its wavefront, and rendering of the final image onto conventional, framebuffer-based displays. The required view-dependent depth image is computed from the phase information inherently represented in the complex-valued wavefront. Our model also comprises a correct physical modeling of the camera taking into account optical elements, such as lens and aperture. It thus allows for a variety of effects including depth of field, diffraction, interference, and features built-in anti-aliasing. A central feature of our framework is its seamless integration into conventional rendering and display technology which enables us to elegantly combine traditional 3D object or scene representations with holograms. The presented work includes the theoretical foundations and allows for high quality rendering of objects consisting of large numbers of elementary waves while keeping the hologram at a reasonable size