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Item Fast Volumetric Data Exploration with Importance-Based Accumulated Transparency Modulation(The Eurographics Association, 2010) Wan, Yong; Hansen, Chuck; Ruediger Westermann and Gordon KindlmannDirect volume rendering techniques have been successfully applied to visualizing volumetric datasets across many application domains. Due to the sensitivity of transfer functions and the complexity of fine-tuning transfer functions, direct volume rendering is still not widely used in practice. For fast volumetric data exploration, we propose Importance-Based Accumulated Transparency Modulation which does not rely on transfer function manipulation. This novel rendering algorithm is a generalization and extension of the Maximum Intensity Difference Accumulation technique. By only modifying the accumulated transparency, the resulted volume renderings are essentially high dynamic range. We show that by using several common importance measures, different features of the volumetric datasets can be highlighted. The results can be easily extended to a high-dimensional importance difference space, by mixing the results from an arbitrary number of importance measures with weighting factors, which all control the final output with a monotonic behavior. With Importance-Based Accumulated Transparency Modulation, the end-user can explore a wide variety of volumetric datasets quickly without the burden of manually setting and adjusting a transfer function.Item Feature-Driven Ambient Occlusion for Direct Volume Rendering(The Eurographics Association, 2010) Ancel, Alexandre; Dischler, Jean-Michel; Mongenet, Catherine; Ruediger Westermann and Gordon KindlmannAmbient occlusion techniques were introduced to improve data comprehension by bringing soft fading shadows. They consist in attenuating light by considering the occlusion resulting from the presence of neighboring structures. Recently introduced in volume rendering, we show that the straightforward application of ambient occlusion in direct volume rendering has its limits as rendering a multi-layer volume results in overdarkening the internal layers of the volume. This paper proposes to address the overdarkening issue by computing ambient occlusion according to the features present in the dataset. This allows us to neglect inter-occlusions between features without losing the auto-occlusions that give cues on the shape of the considered features. We use a GPU-based approach with bricking to speed up the computations of our ambient occlusion method. Results show that our approach not only improves the visual quality of images compared to classical ambient occlusion, but it is also less parametersensitive, thus furthermore improving usability for every-day users.Item Realtime Aesthetic Image Retargeting(The Eurographics Association, 2010) Liu, Ligang; Jin, Yong; Wu, Qingbiao; Pauline Jepp and Oliver DeussenHumans have always sought to achieve aesthetics in art. In this paper, we present a novel approach for retargeting images to different aspect ratios while improving the composition aesthetics of the results. A simpler computational aesthetic energy is proposed and used to drive the salient objects and prominent lines to move towards their corresponding optimal positions. A mesh-based warping scheme is presented to transform the images while protecting the visual appearance of salient objects. The objective function is quadratic and thus it can be quickly minimized by solving a sparse linear system. The retargeting results are generated in realtime while the user changes the aspect ratios of the target images. A variety of experiments have shown the applicability and effectiveness of our algorithm.Item A Robust and Universal Gradient Domain Imaging Solver Using Gradient Variables and Locally Varying Metrics(The Eurographics Association, 2010) Neumann, László; Hegedüs, Ramón; Pauline Jepp and Oliver DeussenGradient Domain Imaging (GDI) has gained a high importance and provoked numerous powerful applications over the last decade. It employs a workflow of creating an inconsistent gradient field (GF) from one or more images using different non-linear operations and finally it determines an image with a consistent, integrable GF that falls near to the prescribed inconsistent one. However, the result is not really predictable, often suffers from halo-effects and other local distortions at higher frequencies as well as from uncontrollable far-effects arising from local gradient-contradictions. The unfolding of these artifacts culminates in an undesired overall image appearance. None of the common GDI solvers can overcome these side-effects as they utilize the same local isotropic 'coefficient-pattern' in a sparse matrix description and they differ only in the numerical solution techniques. We present a powerful GDI method solving the problem completely in the gradient domain with gradient-variables and using spatially varying metrics that depends only on the starting inconsistent gradient field. After obtaining the nearest consistent gradient field with the pre-defined metrics we return into the image space by double integration that yields the wanted pixel intensity values. Our method delivers a great aesthetic enhancement by eliminating halo effects and saving small details, furthermore providing a realistic and pleasant overall light distribution at lower frequencies. By significantly extending the range of allowed inconsistency in the prescribed gradient field, it also allows for solving a large class of problems that proved hopeless beforehand.