Photon Mapping Research Articles

Efficient Progressive Radiance Estimation Engine Architecture and Implementation for Progressive Photon Mapping

We propose a progressive radiance estimation engine (PREE) hardware architecture to accelerate the processing of the progressive photon mapping with satisfactory graphic quality. The presented PREE architecture consists of four progressive radiance estimation units (PREUs), approximate full task schedule-oriented hit-point update operation controller (AFTSO-HpUOC) and approximate data-independent schedule-oriented radiance evaluation controller (ADISO-REC). The PREUs accelerate the radiance estimation computation by a pipeline technique and share and configure the hardware resource for hit-point update operation and radiance evaluation. Through AFTSO-HpUOC and ADISO-REC, the data can be efficiently dispatched to achieve better parallelism and the data dependence can be alleviated within the four PREUs, respectively. The core area of the proposed PREE architecture implemented in TSMC 90-nm CMOS process is 1.78 mm2. According to the post-layout simulation results, the implementation achieves 496.79 million hit-point update operations per second (MHpUO/s) and consumes 184 mW at 125 MHz for Cornell box with three balls.

Efficient Caustic Rendering with Lightweight Photon Mapping

AbstractRobust and efficient rendering of complex lighting effects, such as caustics, remains a challenging task. While algorithms like vertex connection and merging can render such effects robustly, their significant overhead over a simple path tracer is not always justified and – as we show in this paper ‐ also not necessary. In current rendering solutions, caustics often require the user to enable a specialized algorithm, usually a photon mapper, and hand‐tune its parameters. But even with carefully chosen parameters, photon mapping may still trace many photons that the path tracer could sample well enough, or, even worse, that are not visible at all.Our goal is robust, yet lightweight, caustics rendering. To that end, we propose a technique to identify and focus computation on the photon paths that offer significant variance reduction over samples from a path tracer. We apply this technique in a rendering solution combining path tracing and photon mapping. The photon emission is automatically guided towards regions where the photons are useful, i.e., provide substantial variance reduction for the currently rendered image. Our method achieves better photon densities with fewer light paths (and thus photons) than emission guiding approaches based on visual importance. In addition, we automatically determine an appropriate number of photons for a given scene, and the algorithm gracefully degenerates to pure path tracing for scenes that do not benefit from photon mapping.

Time‐varying light motion in single convergence

AbstractAs light travels fast in the physical world, it is generally hard to capture the propagation of light with a real camera. However, with the development of photon mapping, it is possible to simulate and visualize such fantastic effect. In this paper, we propose a new algorithm based on progressive photon mapping to render the time‐varying light motion. By incorporating our algorithm with participating media, we synthesis the animation of time‐varying light beams expanding in space with slow motion. Interesting phenomena can be observed in our experiments through designating either a constant light source or a bullet light that only emits instantaneously. Our algorithm is efficient in the sense that all frames of the animation can be rendered with only one convergence of the progressive photon mapping, showing the advantage of revealing the light propagation process by our algorithm. The experiments demonstrate the effectiveness and efficiency of our approach.

Photon mapping with visible kernel domains

Despite the strong efforts made in the last three decades, lighting simulation systems still remain prone to various types of imprecisions. This paper specifically tackles the problem of biases due to density estimation used in photon mapping approaches. We study the fundamental aspects of density estimation and exhibit the need for handling visibility in the early stage of the kernel domain definition. We show that properly managing visibility in the density estimation process allows to reduce or to remove biases all at once. In practice, we have implemented a 3D product kernel based on a polyhedral domain, with both point-to-point and point-to-surface visibility computation. Our experimental results illustrate the enhancements produced at every stage of density estimation, for direct photon maps visualization and progressive photon mapping.

Bidirectional Rendering of Vector Light Transport

AbstractOn the foundations of many rendering algorithms it is the symmetry between the path traversed by light and its adjoint path starting from the camera. However, several effects, including polarization or fluorescence, break that symmetry, and are defined only on the direction of light propagation. This reduces the applicability of bidirectional methods that exploit this symmetry for simulating effectively light transport. In this work, we focus on how to include these non‐symmetric effects within a bidirectional rendering algorithm. We generalize the path integral to support the constraints imposed by non‐symmetric light transport. Based on this theoretical framework, we propose modifications on two bidirectional methods, namely bidirectional path tracing and photon mapping, extending them to support polarization and fluorescence, in both steady and transient state.

The Effect of Incident Angle and Filling Factor on Dispersion Properties of Different Structures of One-Dimensional Photonic Crystals

In this paper, we applied the transfer matrix method in conjunction with the Bloch theorem to study the dispersion properties of one-dimensional photonic crystals made by TiO2/ GaAs and TiO2/ MgF2. The effects of filling factor and incident angle on photonic gap map are investigated for both TE and TM polarizations. It is found that location, number, and width of the photonic gap are affected significantly by the filling factor and incident angle of the structure. Results are compared with published data and are found to be in good agreement.

Beyond points and beams

We develop a theory of volumetric density estimation which generalizes prior photon point (0D) and beam (1D) approaches to a broader class of estimators using " n D" samples along photon and/or camera subpaths. Volumetric photon mapping performs density estimation by point sampling propagation distances within the medium and performing density estimation over the generated points (0D). Beam-based (1D) approaches consider the expected value of this distance sampling process along the last camera and/or light subpath segments. Our theory shows how to replace propagation distance sampling steps across multiple bounces to form higher-dimensional samples such as photon planes (2D), photon volumes (3D), their camera path equivalents, and beyond. We perform a theoretical error analysis which reveals that in scenarios where beams already outperform points, each additional dimension of n D samples compounds these benefits further. Moreover, each additional sample dimension reduces the required dimensionality of the blurring needed for density estimation, allowing us to formulate, for the first time, fully unbiased forms of volumetric photon mapping. We demonstrate practical implementations of several of the new estimators our theory predicts, including both biased and unbiased variants, and show that they outperform state-of-the-art beam-based volumetric photon mapping by a factor of 2.4--40×.

A Spatial Target Function for Metropolis Photon Tracing

The human visual system is sensitive to relative differences in luminance, but light transport simulation algorithms based on Metropolis sampling often result in a highly nonuniform relative error distribution over the rendered image. Although this issue has previously been addressed in the context of the Metropolis light transport algorithm, our work focuses on Metropolis photon tracing. We present a new target function (TF) for Metropolis photon tracing that ensures good stratification of photons leading to pixel estimates with equalized relative error. We develop a hierarchical scheme for progressive construction of the TF from paths sampled during rendering. In addition to the approach taken in previous work, where the TF is defined in the image plane, ours can be associated with compact spatial regions. This allows us to take advantage of illumination coherence to more robustly estimate the TF while adapting to geometry discontinuities. To sample from this TF, we design a new replica exchange Metropolis scheme. We apply our algorithm in progressive photon mapping and show that it often outperforms alternative approaches in terms of image quality by a large margin.

Efficient rendering of caustics with streamed photon mapping

AbstractIn this paper, we present the streamed photon mapping method for enhancing the rendering of caustics. In order to achieve a realistic caustic effect, global illumination methods require additional data, which are gathered by creating a caustic map or increasing the number of samples used for rendering. Our method employs a stream of photons with a varying luminance level depending on the material properties of the surface. The application of a concentrated photon stream provides the ability to render caustics effectively without increasing the number of photons in a photon map. Such an approach increases visibility of results, while also allowing for faster computations.

Gradient-Domain Photon Density Estimation

The most common solutions to the light transport problem rely on either Monte Carlo MC integration or density estimation methods, such as uni- & bi-directional path tracing or photon mapping. Recent gradient-domain extensions of MC approaches show great promise; here, gradients of the final image are estimated numerically instead of the image intensities themselves with coherent paths generated from a deterministic shift mapping. We extend gradient-domain approaches to light transport simulation based on density estimation. As with previous gradient-domain methods, we detail important considerations that arise when moving from a primal- to gradient-domain estimator. We provide an efficient and straightforward solution to these problems. Our solution supports stochastic progressive density estimation, so it is robust to complex transport effects. We show that gradient-domain photon density estimation converges faster than its primal-domain counterpart, as well as being generally more robust than gradient-domain uni- & bi-directional path tracing for scenes dominated by complex transport.

A spatial target function for metropolis photon tracing

The human visual system is sensitive to relative differences in luminance, but light transport simulation algorithms based on Metropolis sampling often result in a highly nonuniform relative error distribution over the rendered image. Although this issue has previously been addressed in the context of the Metropolis light transport algorithm, our work focuses on Metropolis photon tracing. We present a new target function (TF) for Metropolis photon tracing that ensures good stratification of photons leading to pixel estimates with equalized relative error. We develop a hierarchical scheme for progressive construction of the TF from paths sampled during rendering. In addition to the approach taken in previous work, where the TF is defined in the image plane, ours can be associated with compact spatial regions. This allows us to take advantage of illumination coherence to more robustly estimate the TF while adapting to geometry discontinuities. To sample from this TF, we design a new replica exchange Metropolis scheme. We apply our algorithm in progressive photon mapping and show that it often outperforms alternative approaches in terms of image quality by a large margin.

A Spatial Target Function for Metropolis Photon Tracing

The human visual system is sensitive to relative differences in luminance, but light transport simulation algorithms based on Metropolis sampling often result in a highly nonuniform relative error distribution over the rendered image. Although this issue has previously been addressed in the context of the Metropolis light transport algorithm, our work focuses on Metropolis photon tracing. We present a new target function (TF) for Metropolis photon tracing that ensures good stratification of photons leading to pixel estimates with equalized relative error. We develop a hierarchical scheme for progressive construction of the TF from paths sampled during rendering. In addition to the approach taken in previous work, where the TF is defined in the image plane, ours can be associated with compact spatial regions. This allows us to take advantage of illumination coherence to more robustly estimate the TF while adapting to geometry discontinuities. To sample from this TF, we design a new replica exchange Metropolis scheme. We apply our algorithm in progressive photon mapping and show that it often outperforms alternative approaches in terms of image quality by a large margin.

Low overhead path regeneration

Monte Carlo Path Tracing is a core light transport technique which is used for modern methods (like BDPT, MLT, VCM and others). One of the main challenge of efficient GPU Path Tracing implementation is inefficient workload caused by paths of different lengths; few threads process the long paths, while other threads are idle. A work distribution technique called "Path Regeneration" is commonly used to solve this problem. We introduce a novel GPU implementation of path regeneration technique called "in place block based path regeneration." In comparison to previous approaches our algorithm possesses two main advantages: it has lower self-cost and it does not move any per-ray data along threads in memory, thus, our algorithm can be easily integrated to any advanced path tracing technique (like BDPT, MLT and other) or photon mapping. We tested our solution with path tracing using both CUDA and OpenCL.

TSS BVHs: Tetrahedron Swept Sphere BVHs for Ray Tracing Subdivision Surfaces

AbstractWe present a novel, compact bounding volume hierarchy, TSS BVH, for ray tracing subdivision surfaces computed by the Catmull‐Clark scheme. We use Tetrahedron Swept Sphere (TSS) as a bounding volume to tightly bound limit surfaces of such subdivision surfaces given a user tolerance. Geometric coordinates defining our TSS bounding volumes are implicitly computed from the subdivided mesh via a simple vertex ordering method, and each level of our TSS BVH is associated with a single distance bound, utilizing the Catmull‐Clark scheme. These features result in a linear space complexity as a function of the tree depth, while many prior BVHs have exponential space complexity. We have tested our method against different benchmarks with path tracing and photon mapping. We found that our method achieves up to two orders of magnitude of memory reduction with a high culling ratio over the prior AABB BVH methods, when we represent models with two to four subdivision levels. Overall, our method achieves three times performance improvement thanks to these results. These results are acquired by our theorem that rigorously computes our TSS bounding volumes.

Correlated Photon Mapping for Interactive Global Illumination of Time-Varying Volumetric Data.

We present a method for interactive global illumination of both static and time-varying volumetric data based on reduction of the overhead associated with re-computation of photon maps. Our method uses the identification of photon traces invariant to changes of visual parameters such as the transfer function (TF), or data changes between time-steps in a 4D volume. This lets us operate on a variant subset of the entire photon distribution. The amount of computation required in the two stages of the photon mapping process, namely tracing and gathering, can thus be reduced to the subset that are affected by a data or visual parameter change. We rely on two different types of information from the original data to identify the regions that have changed. A low resolution uniform grid containing the minimum and maximum data values of the original data is derived for each time step. Similarly, for two consecutive time-steps, a low resolution grid containing the difference between the overlapping data is used. We show that this compact metadata can be combined with the transfer function to identify the regions that have changed. Each photon traverses the low-resolution grid to identify if it can be directly transferred to the next photon distribution state or if it needs to be recomputed. An efficient representation of the photon distribution is presented leading to an order of magnitude improved performance of the raycasting step. The utility of the method is demonstrated in several examples that show visual fidelity, as well as performance. The examples show that visual quality can be retained when the fraction of retraced photons is as low as 40%-50%.

Development of high-resolution cathodoluminescence system for STEM and application to plasmonic nanostructures.

A high-resolution cathodoluminescence (CL) system for scanning transmission electron microscope (STEM) has been developed by employing a field emission gun and a spherical aberration corrector, which realizes a probe size of 1 nm even at an accelerating voltage of 80 kV and beam current of the order of 1 nA. Angle resolved measurement of light emission from a sample in the STEM is possible by combining a parabolic mirror and position-controlled pinhole. CL spectra are successively acquired by a highly sensitive charge-coupled device while scanning the incident electron beam or pinhole, which enables various detection modes, i.e. (i) angle resolved spectral pattern, (ii) beam scan spectral image and (iii) photon map. In order to calibrate the acquired spectrum, the correction function is created from the comparison between the observed and theoretical spectra of the transition radiation. Furthermore, the modification of polarization by the parabolic mirror is discussed. Some examples of the applications of the STEM-CL system to plasmonics are presented to demonstrate the unique measurement features of the CL system, i.e. (i) multipole modes in silver nanoparticles, (ii) surface plasmon polariton modes in a 2D plasmonic crystal and (iii) localized surface plasmon modes in a gold bow tie nano-antenna.

An out-of-core photon mapping approach to daylight coefficients

Climate-based daylight modelling (CBDM) is an effective means of assessing the performance of daylight redirecting components (DRCs) with highly directional scattering to determine their impact on daylight availability and visual comfort. Such a simulation imposes significant computational demands on commodity hardware as it requires high density luminance samples obtained by forward raytracing. We propose an out-of-core photon mapping method within the Radiance framework to compute high quality daylight coefficients as a basis for CBDM. The method is particularly suited to angularly selective DRCs exhibiting strong redirection in conjunction with non-uniform sky luminance distributions with high resolution subdivisions. Our implementation is a work in progress and currently accommodates up to 4.3G photons on disk, while optimizing the in-core memory footprint by loading only photons which actually contribute flux to sensor points. We also leverage the fact that photon paths are independent through parallelization.

Stylized Caustics: Progressive Rendering of Animated Caustics

AbstractIn recent years, much work was devoted to the design of light editing methods such as relighting and light path editing. So far, little work addressed the target‐based manipulation and animation of caustics, for instance to a differently‐shaped caustic, text or an image. The aim of this work is the animation of caustics by blending towards a given target irradiance distribution. This enables an artist to coherently change appearance and style of caustics, e.g., for marketing applications and visual effects. Generating a smooth animation is nontrivial, as photon density and caustic structure may change significantly. Our method is based on the efficient solution of a discrete assignment problem that incorporates constraints appropriate to make intermediate blends plausibly resemble caustics. The algorithm generates temporally coherent results that are rendered with stochastic progressive photon mapping. We demonstrate our system in a number of scenes and show blends as well as a key frame animation.

Rendering Participating Media with Streamed Photon Mapping

The research on Streamed Photon Mapping method has shown its effciency and potential. Significant caustic effects without an additional caustic map are its undeniable advantage. The method assumed that light spreads in a vacuum; however, such approach excluded the visualization of such phenomena as fog, smoke, or clouds. This paper presents a modification of the basic method of rendering with the help of photon streams, taking into account the simulation of light in dense mediums. The specifics of stream structure and the applied solutions allow to eliminate multiple assessment of the same photons as it occurred in the case of standard Volumetric Photon Mapping.

A survey of photon mapping state-of-the-art research and future challenges

Global illumination is the core part of photo-realistic rendering. The photon mapping algorithm is an effective method for computing global illumination with its obvious advantage of caustic and color bleeding rendering. It is an active research field that has been developed over the past two decades. The deficiency of precise details and efficient rendering are still the main challenges of photon mapping. This report reviews recent work and classifies it into a set of categories including radiance estimation, photon relaxation, photon tracing, progressive photon mapping, and parallel methods. The goals of our report are giving readers an overall introduction to photon mapping and motivating further research to address the limitations of existing methods.