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Item Polarization Demosaicking for Monochrome and Color Polarization Focal Plane Arrays(The Eurographics Association, 2019) Qiu, Simeng; Fu, Qiang; Wang, Congli; Heidrich, Wolfgang ; Schulz, Hans-Jörg and Teschner, Matthias and Wimmer, MichaelDivision-of-focal-plane (DoFP) polarization image sensors allow for snapshot imaging of linear polarization effects with inexpensive and straightforward setups. However, conventional interpolation based image reconstruction methods for such sensors produce unreliable and noisy estimates of quantities such as degree of linear polarization (DoLP) or angle of linear polarization (AoLP). In this paper, we propose a polarization demosaicking algorithm by inverting the polarization image formation model for both monochrome and color DoFP cameras. Compared to previous interpolation methods, our approach can significantly reduce noise induced artifacts and drastically increase the accuracy in estimating polarization states. We evaluate and demonstrate the performance of the methods on a new high-resolution color polarization dataset. Simulation and experimental results show that the proposed reconstruction and analysis tools offer an effective solution to polarization imaging.Item MetaISP -- Exploiting Global Scene Structure for Accurate Multi-Device Color Rendition(The Eurographics Association, 2023) Souza, Matheus; Heidrich, Wolfgang; Guthe, Michael; Grosch, ThorstenImage signal processors (ISPs) are historically grown legacy software systems for reconstructing color images from noisy raw sensor measurements. Each smartphone manufacturer has developed its ISPs with its own characteristic heuristics for improving the color rendition, for example, skin tones and other visually essential colors. The recent interest in replacing the historically grown ISP systems with deep-learned pipelines to match DSLR's image quality improves structural features in the image. However, these works ignore the superior color processing based on semantic scene analysis that distinguishes mobile phone ISPs from DSLRs. Here we present MetaISP, a single model designed to learn how to translate between the color and local contrast characteristics of different devices. MetaISP takes the RAW image from device A as input and translates it to RGB images that inherit the appearance characteristics of devices A, B, and C. We achieve this result by employing a lightweight deep learning technique that conditions its output appearance based on the device of interest. In this approach, we leverage novel attention mechanisms inspired by cross-covariance learn global scene semantics. Additionally, we make use of metadata that typically accompanies raw images, and we estimate scene illuminants when they are not available.Item Real-Time Bump Map Synthesis(The Eurographics Association, 2001) Kautz, Jan; Heidrich, Wolfgang; Seidel, Hans-Peter; Kurt Akeley and Ulrich NeumannIn this paper we present a method that automatically synthesizes bump maps at arbitrary levels of detail in real-time. The only input data we require is a normal density function; the bump map is generated according to that function. It is also used to shade the generated bump map. The technique allows to infinitely zoom into the surface, because more (consistent) detail can be created on the fly. The shading of such a surface is consistent when displayed at different distances to the viewer (assuming that the surface structure is self-similar). The bump map generation and the shading algorithm can also be used separately.Item Linear Polarization Demosaicking for Monochrome and Colour Polarization Focal Plane Arrays(© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2021) Qiu, Simeng; Fu, Qiang; Wang, Congli; Heidrich, Wolfgang; Benes, Bedrich and Hauser, HelwigDivision‐of‐focal‐plane (DoFP) polarization image sensors allow for snapshot imaging of linear polarization effects with inexpensive and straightforward setups. However, conventional interpolation based image reconstruction methods for such sensors produce unreliable and noisy estimates of quantities such as Degree of Linear Polarization (DoLP) or Angle of Linear Polarization (AoLP). In this paper, we propose a polarization demosaicking algorithm by inverting the polarization image formation model for both monochrome and colour DoFP cameras. Compared to previous interpolation methods, our approach can significantly reduce noise induced artefacts and drastically increase the accuracy in estimating polarization states. We evaluate and demonstrate the performance of the methods on a new high‐resolution colour polarization dataset. Simulation and experimental results show that the proposed reconstruction and analysis tools offer an effective solution to polarization imaging.Item Stochastic Convolutional Sparse Coding(The Eurographics Association, 2019) Xiong, Jinhui; Richtarik, Peter; Heidrich, Wolfgang ; Schulz, Hans-Jörg and Teschner, Matthias and Wimmer, MichaelState-of-the-art methods for Convolutional Sparse Coding usually employ Fourier-domain solvers in order to speed up the convolution operators. However, this approach is not without shortcomings. For example, Fourier-domain representations implicitly assume circular boundary conditions and make it hard to fully exploit the sparsity of the problem as well as the small spatial support of the filters. In this work, we propose a novel stochastic spatial-domain solver, in which a randomized subsampling strategy is introduced during the learning sparse codes. Afterwards, we extend the proposed strategy in conjunction with online learning, scaling the CSC model up to very large sample sizes. In both cases, we show experimentally that the proposed subsampling strategy, with a reasonable selection of the subsampling rate, outperforms the state-of-the-art frequency-domain solvers in terms of execution time without losing the learning quality. Finally, we evaluate the effectiveness of the over-complete dictionary learned from large-scale datasets, which demonstrates an improved sparse representation of the natural images on account of more abundant learned image features.Item Fast Primitive Distribution for Illustration(The Eurographics Association, 2002) Secord, Adrian; Heidrich, Wolfgang; Streit, Lisa; P. Debevec and S. GibsonIn this paper we present a high-quality, image-space approach to illustration that preserves continuous tone by probabilistically distributing primitives while maintaining interactive rates. Our method allows for frame-to-frame coherence by matching movements of primitives with changes in the input image. It can be used to create a variety of drawing styles by varying the primitive type or direction. We show that our approach is able to both preserve tone and (depending on the drawing style) high-frequency detail. Finally, while our algorithm requires only an image as input, additional 3D information enables the creation of a larger variety of drawing styles.Item Neural Adaptive Scene Tracing (NAScenT)(The Eurographics Association, 2022) Li, Rui; Rückert, Darius; Wang, Yuanhao; Idoughi, Ramzi; Heidrich, Wolfgang; Bender, Jan; Botsch, Mario; Keim, Daniel A.Neural rendering with implicit neural networks has recently emerged as an attractive proposition for scene reconstruction, achieving excellent quality albeit at high computational cost. While the most recent generation of such methods has made progress on the rendering (inference) times, very little progress has been made on improving the reconstruction (training) times. In this work we present Neural Adaptive Scene Tracing (NAScenT ), that directly trains a hybrid explicit-implicit neural representation. NAScenT uses a hierarchical octree representation with one neural network per leaf node and combines this representation with a two-stage sampling process that concentrates ray samples where they matter most - near object surfaces. As a result, NAScenT is capable of reconstructing challenging scenes including both large, sparsely populated volumes like UAV captured outdoor environments, as well as small scenes with high geometric complexity. NAScenT outperforms existing neural rendering approaches in terms of both quality and training time.Item Real Illumination from Virtual Environments(The Eurographics Association, 2005) Ghosh, Abhijeet; Trentacoste, Matthew; Seetzen, Helge; Heidrich, Wolfgang; Kavita Bala and Philip DutreWe introduce a method for actively controlling the illumination in a room so that it is consistent with a virtual world. In combination with a high dynamic range display, the system produces both uniform and directional illumination at intensity levels covering a wide range of real-world environments. It thereby allows natural adaptation processes of the human visual system to take place, for example when moving between bright and dark environments. In addition, the directional illumination provides additional information about the environment in the user s peripheral field of view. We describe both the hardware and the software aspects of our system. We also conducted an informal survey to determine whether users prefer the dynamic illumination over constant room illumination in an entertainment setting.Item Bidirectional Importance Sampling for Direct Illumination(The Eurographics Association, 2005) Burke, David; Ghosh, Abhijeet; Heidrich, Wolfgang; Kavita Bala and Philip DutreImage-based representations for illumination can capture complex real-world lighting that is difficult to represent in other forms. Current importance sampling strategies for image-based illumination have difficulties in cases where both the illumination and the surface BRDF contain important high-frequency detail for example, when a specular surface is illuminated by an environment map containing small light sources. We introduce the notion of bidirectional importance sampling, in which samples are drawn from the product distribution of both the surface reflectance and the light source energy. While this approach makes the sample selection process more expensive, we drastically reduce the number of visibility tests required to obtain good image quality. As a consequence, we achieve significant quality improvements over previous sampling strategies for the same compute time. Keywords: Methods and Applications Monte Carlo Techniques; Rendering Ray Tracing; Rendering Global Illumination.Item Computational Plenoptic Imaging(The Eurographics Association and Blackwell Publishing Ltd., 2011) Wetzstein, Gordon; Ihrke, Ivo; Lanman, Douglas; Heidrich, Wolfgang; Eduard Groeller and Holly RushmeierThe plenoptic function is a ray‐based model for light that includes the colour spectrum as well as spatial, temporal and directional variation. Although digital light sensors have greatly evolved in the last years, one fundamental limitation remains: all standard CCD and CMOS sensors integrate over the dimensions of the plenoptic function as they convert photons into electrons; in the process, all visual information is irreversibly lost, except for a two‐dimensional, spatially varying subset—the common photograph. In this state‐of‐the‐art report, we review approaches that optically encode the dimensions of the plenoptic function transcending those captured by traditional photography and reconstruct the recorded information computationally.
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