Arc Blanc: a real time ocean simulation framework David Algis Université de Poitiers and Studio Nyx Bérenger Bramas INRIA Nancy Emmanuelle Darles Université de Poitiers Lilian Aveneau Université de Poitiers

The oceans cover the vast majority of the Earth. Therefore, their simulation has many scientific, industrial and military interests, including computer graphics domain. By fully exploiting the multi-threading power of GPU and CPU, current state-of-the-art tools can achieve real-time ocean simulation, even if it is sometimes needed to reduce the physical realism for large scenes. Although most of the building blocks for implementing an ocean simulator are described in the literature, a clear explanation of how they interconnect is lacking. Hence, this paper proposes to bring all these components together, detailing all their interactions, in a comprehensive and fully described real-time framework that simulates the free ocean surface and the coupling between solids and fluid. This article also presents several improvements to enhance the physical realism of our model. The two main ones are: calculating the real-time velocity of ocean fluids at any depth; computing the input of the fluid to solid coupling algorithm.

Compression of Spectral Images using Spectral JPEG XL Alban Fichet Intel Corporation Christoph Peters Intel Corporation

The advantages of spectral rendering are increasingly well known, and corresponding rendering algorithms have matured. In this context, spectral images are used as input (e.g., reflectance and emission textures) and output of a renderer. Their large memory footprint is one of the big remaining issues with spectral rendering. Our method applies a cosine transform in the wavelength domain. We then reduce the dynamic range of higher-frequency Fourier coefficients by dividing them by the mean brightness, i.e., the Fourier coefficient for frequency zero. Then we store all coefficient images using JPEG XL. The mean brightness is perceptually most important and we store it with high quality. At higher frequencies, we use higher compression ratios and optionally lower resolutions. Our format supports the full feature set of spectral OpenEXR, but compared to this lossless compression, we achieve file sizes that are 10 to 60 times smaller than their ZIP compressed counterparts.

A Stack-Free Traversal Algorithm for Left-Balanced k-d Trees Ingo Wald NVIDIA

We present an algorithm that allows for find-closest-point and k-nearest-neighbor (kNN) style traversals of left-balanced k-d trees, without the need for either recursion or software-managed stacks; instead using only current and last previously traversed node to compute which node to traverse next.

GPU Friendly Laplacian Texture Blending Bartlomiej Wronski NVIDIA

Texture and material blending is one of the leading methods for adding variety to rendered virtual worlds, creating composite materials, and generating procedural content. When done naively, it can introduce either visible seams or contrast loss, leading to an unnatural look not representative of blended textures. Earlier work proposed addressing this problem through careful manual parameter tuning, lengthy per-texture statistics precomputation, look-up tables, or training deep neural networks. In this work, we propose an alternative approach based on insights from image processing and Laplacian pyramid blending. Our approach does not require any precomputation or increased memory usage (other than the presence of a regular, non-Laplacian, texture mipmap chain), does not produce ghosting, preserves sharp local features, and can run in real time on the GPU at the cost of a few additional lower mipmap texture taps.

Chromaticity preserving analytic approximations to the CIE color matching functions Thomas Puls

Previous attempts to approximate the tabulated CIE color matching functions used least-square-fit methods applied to the functions' absolute values. However, these approximations do not preserve chromaticity well when the color matching functions fade out near the wavelength limits of human vision.

Additionally, the analytical functions used to date were mostly defined piecewise, for example asymmetrical halves of a Gaussian normal distribution, resulting in discontinuities in higher-order derivatives.

The method of approximation by analytical functions presented in this article accurately preserves chromaticity and is infinitely differentiable. It is applied to the industry standard CIE 1931 2° Standard Observer. With the latter, the root-mean-square (RMS) error in the color matching functions is below 0.4% and below 0.0019 in the respective chromaticity values. Computing all three color matching functions requires only a total of ten calls of the exponential function (or just nine at the expense of accuracy), and no other functions are required.

We also applied the method to the more modern CIE 170-1:2006 10° Standard Observer. The source code for this standard is part of the supplementary material.