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In this paper, we present an efficient framework for editing the appearance of measured materials. First, we separate the material data into diffuse and specular parts, which is important for measured BRDFs since editing without distinguishing the two parts makes the results less predictive. Additionally, the albedo of each part is calculated for later color editing. Next, we use a novel method to cluster the materials by their gloss levels and select the representative material of every level. With this at hand, the roughness, i.e., shape of the specular highlights can be adjusted among different levels. Finally, we reconstruct the edited materials which can be directly used in both online and offline rendering. We test the framework on the MERL dataset to validate the effectiveness of our method.

In this paper, we propose a depth restoration method using a novel superpixel technique. Guided by a normal map reconstructed from the raw depth data, this technique over-segments RGB-D images into many small regions where their depth is assumed to be smooth. As the raw depth data is incomplete, we further introduce a depth confidence map to identify the regions which are more reliable. With the produced superpixels, we can restore the incomplete depth map using a per-superpixel linear regression. A multiresolution su-perpixel strategy is employed when some superpixels do not contain enough valid data. Experiments show that the proposed depth restoration method can effectively fill the wide gaps along depth discontinuities without blurring the object boundaries and the depth discontinuities.

Most traditional Chinese paintings are painted on hand-made paper that easily suffers from severe spectral changes caused by prolonged light exposure, resulting in color distortion and low contrast. To recover the original appearance of a Chinese painting, especially its background color, an automatic background adjustment framework is proposed. This framework is based on the insightful observation that the fading model of a painting image is analogue to the common hazy image formation model when the painting image is transformed into the K-M (Kubelka-Munk) space. We demonstrate that this fading model is quite useful in extracting pigment lines from any painting image. These pigment lines represent clusters of distinct color pigments used in a Chinese painting, which is the key to density map estimation and background restoration. Experimental results prove that our approach is able to restore a variety of deteriorated Chinese paintings without any user intervention or training.

This paper presents an efficient approach to render refracting transmissive objects with multi-scale surface roughness, under distant illumination. To correctly capture both fine-scale surface details and large-scale appearances, and enable real-time processing at various viewing resolutions, we first divide the surface roughness into three levels, namely, micro-scale, meso-scale and macro-scale. Each scale of roughness is modeled and evaluated using different strategies, and the overall roughness is approximated by their spherical convolution. Then, this representation is incorporated into a microfacet-based BTDF model, and multi-scale rough refractions are simulated on both front and back sides of an object as light enters and exits the object. In particular, non-linear filtering methods are applied to both macro-scale geometries and meso-scale bumps to reduce aliasing when viewed across a range of distances. Finally, experimental results illustrate that our approach produces resolution-dependent refraction effects that match super-sampled ground truth, while achieving a speed up of several orders of magnitude with hardware acceleration.

Line segment sampling has recently been adopted in many rendering algorithms for better handling of a wide range of effects such as motion blur, defocus blur and scattering media. A question naturally raised is how to generate line segment samples with good properties that can effectively reduce variance and aliasing artifacts observed in the rendering results. This paper studies this problem and presents a frequency analysis of line segment sampling. The analysis shows that the frequency content of a line segment sample is equivalent to the weighted frequency content of a point sample. The weight introduces anisotropy that smoothly changes among point samples, line segment samples and line samples according to the lengths of the samples. Line segment sampling thus makes it possible to achieve a balance between noise (point sampling) and aliasing (line sampling) under the same sampling rate. Based on the analysis, we propose a line segment sampling scheme to preserve blue-noise properties of samples which can significantly reduce noise and aliasing artifacts in reconstruction results. We demonstrate that our sampling scheme improves the quality of depth-of-field rendering, motion blur rendering, and temporal light field reconstruction.

We present a novel approach for real-time rendering of transparent objects with multi-scale rough refraction under all-frequency environmental lighting. In our rendering system, the normal distribution function (NDF) of the surface bumps is expressed via mixtures of von Mises-Fisher (vMF) distributions, while the corresponding perturbation of refracted rays (RDF) can be approximated as a spherical warp of NDF, taking into account correction factors. Under the assumption of two-sided refraction, we first generate the vMF lobes of the front surface refraction. Based on these lobes, we then estimate the RDF of back surface as a warped convolution of macroscopic and microscopic NDFs within the footprint of each lobe. Moreover, summed-area tables and dual-paraboloid maps are adopted to efficiently represent the environmental lighting in order to support fully dynamic lighting conditions. We finally get a coherent rendering at the different scales that reproduces high-quality meso- and micro-geometric effects under real-time performance.

The illumination of rough refraction is challenging due to the complex integrations of scattered lights from multiple directions. Prefiltered environment map is able to eliminate the comprehensive integrations, but the precomputation stage protects it from being adapted into dynamically varying environmental lighting. We propose a real-time method for rendering rough refraction, supporting dynamically changing lighting, geometries and materials. Environment maps are efficiently compressed by summed area table (SAT), whose construction only costs several milliseconds. Meanwhile, rough refraction effects are approximated by our lobe merging method. Solid results of our approach are demonstrated by comparing with ground truth results generated with a path tracing engine.

Complex natural lighting provides better realism compared to traditional artificial lights, which has been increasing in real-time graphic applications, such as video games and virtual reality. However, rendering with complex natural illumination proves quite costly owing to a spherical space integral. This paper addresses the problem of real-time rendering scenes under complex environment lighting that captures soft shadows and glossy reflections. The environment lighting is separated into low-frequency lighting component and highlight component based on a rejection-based sampling method. Scenes lit under low-frequency lighting are approximated via spherical harmonic lighting, while highlight illumination effects such as soft shadows and glossy reflections are simulated by a small set of sampled virtual point lights (VPL). Experimental results demonstrate that our method can be run in real-time under complex natural lighting without precomputation.

This paper presents a scalable, adaptive algorithm for direct illumination in scenes with many area light sources. Instead of presampling light sources into massive point lights like previous multilight algorithms, the algorithm builds a tree structure for all area lights using agglomerative hierarchical clustering algorithm and evaluates direct illumination by a collection of tree nodes. Each node represents a light cluster and its output radiance is computed using two estimation methods. For each pixel point, a node set is found adaptively through tree traversal guided by error estimation and overall radiance variation. As the algorithm works on area lights directly, the error incurred by converting area lights to point lights is avoided. The experimental results show that our algorithm can generate images with higher fidelity and is more efficient compared with existing point light based multi-light algorithms.

Dynamic environment lighting has been increasing in real-time graphics applications, such as 3D games and virtual environment applications because of its better realism compared to the traditional lights. However, rendering under dynamic environment lighting is sophisticated due to a complex hemispherical space integral operation. Spherical harmonics are used to illuminate diffuse surface in real-time. Screen space ambient occlusion is adopted to approximate soft shadows due to occlusion. Results show that the whole process can run in real-time with little precomputation.