Perceptual error optimization for Monte Carlo rendering

Realistic image synthesis involves computing high-dimensional light transport integrals which in practice are numerically estimated using Monte Carlo integration. The error of this estimation manifests itself in the image as visually displeasing aliasing or noise. To ameliorate this, we develop a theoretical framework for optimizing screen-space error distribution. Our model is flexible and works for arbitrary target error power spectra. We focus on perceptual error optimization by leveraging models of the human visual system's (HVS) point spread function (PSF) from halftoning literature. This results in a specific optimization problem whose solution distributes the error as visually pleasing blue noise in image space. We develop a set of algorithms that provide a trade-off between quality and speed, showing substantial improvements over prior state of the art. We perform evaluations using both quantitative and perceptual error metrics to support our analysis, and provide extensive supplemental material to help evaluate the perceptual improvements achieved by our methods

Utilising path-vertex data to improve Monte Carlo global illumination.

Efficient techniques for photo-realistic rendering are in high demand across a wide array of industries. Notable applications include visual effects for film, entertainment and virtual reality. Less direct applications such as visualisation for architecture, lighting design and product development also rely on the synthesis of realistic and physically based illumination. Such applications assert ever increasing demands on light transport algorithms, requiring the computation of photo-realistic effects while handling complex geometry, light scattering models and illumination. Techniques based on Monte Carlo integration handle such scenarios elegantly and robustly, but despite seeing decades of focused research and wide commercial support, these methods and their derivatives still exhibit undesirable side effects that are yet to be resolved. In this thesis, Monte Carlo path tracing techniques are improved upon by utilizing path vertex data and intermediate radiance contributions readily available during rendering. This permits the development of novel progressive algorithms that render low noise global illumination while striving to maintain the desirable accuracy and convergence properties of unbiased methods. The thesis starts by presenting a discussion into optical phenomenon, physically based rendering and achieving photo realistic image synthesis. This is followed by in-depth discussion of the published theoretical and practical research in this field, with a focus on stochastic methods and modem rendering methodologies. This provides insight into the issues surrounding Monte Carlo integration both in the general and rendering specific contexts, along with an appreciation for the complexities of solving global light transport. Alternative methods that aim to address these issues are discussed, providing an insight into modem rendering paradigms and their characteristics. Thus, an understanding of the key aspects is obtained, that is necessary to build up and discuss the novel research and contributions to the field developed throughout this thesis. First, a path space filtering strategy is proposed that allows the path-based space of light transport to be classified into distinct subsets. This permits the novel combination of robust path tracing and recent progressive photon mapping algorithms to handle each subset based on the characteristics of the light transport in that space. This produces a hybrid progressive rendering technique that utilises the strengths of existing state of the art Monte Carlo and photon mapping methods to provide efficient and consistent rendering of complex scenes with vanishing bias. The second original contribution is a probabilistic image-based filtering and sample clustering framework that provides high quality previews of global illumination whilst remaining aware of high frequency detail and features in geometry, materials and the incident illumination. As will be seen, the challenges of edge-aware noise reduction are numerous and long standing, particularly when identifying high frequency features in noisy illumination signals. Discontinuities such as hard shadows and glossy reflections are commonly overlooked by progressive filtering techniques, however by dividing path space into multiple layers, once again based on utilising path vertex data, the overlapping illumination of varying intensities, colours and frequencies is more effectively handled. Thus noise is removed from each layer independent of features present in the remaining path space, effectively preserving such features

Foveated Path Tracing with Fast Reconstruction and Efficient Sample Distribution

Polunseuranta on tietokonegrafiikan piirtotekniikka, jota on käytetty pääasiassa ei-reaaliaikaisen realistisen piirron tekemiseen. Polunseuranta tukee luonnostaan monia muilla tekniikoilla vaikeasti saavutettavia todellisen valon ilmiöitä kuten heijastuksia ja taittumista. Reaaliaikainen polunseuranta on hankalaa polunseurannan suuren laskentavaatimuksen takia. Siksi nykyiset reaaliaikaiset polunseurantasysteemi tuottavat erittäin kohinaisia kuvia, jotka tyypillisesti suodatetaan jälkikäsittelykohinanpoisto-suodattimilla. Erittäin immersiivisiä käyttäjäkokemuksia voitaisiin luoda polunseurannalla, joka täyttäisi laajennetun todellisuuden vaatimukset suuresta resoluutiosta riittävän matalassa vasteajassa. Yksi mahdollinen ratkaisu näiden vaatimusten täyttämiseen voisi olla katsekeskeinen polunseuranta, jossa piirron resoluutiota vähennetään katseen reunoilla. Tämän johdosta piirron laatu on katseen reunoilla sekä harvaa että kohinaista, mikä asettaa suuren roolin lopullisen kuvan koostavalle suodattimelle. Tässä työssä esitellään ensimmäinen reaaliajassa toimiva regressionsuodatin. Suodatin on suunniteltu kohinaisille kuville, joissa on yksi polunseurantanäyte pikseliä kohden. Nopea suoritus saavutetaan tiileissä käsittelemällä ja nopealla sovituksen toteutuksella. Lisäksi työssä esitellään Visual-Polar koordinaattiavaruus, joka jakaa polunseurantanäytteet siten, että niiden jakauma seuraa silmän herkkyysmallia. Visual-Polar-avaruuden etu muihin tekniikoiden nähden on että se vähentää työmäärää sekä polunseurannassa että suotimessa. Nämä tekniikat esittelevät toimivan prototyypin katsekeskeisestä polunseurannasta, ja saattavat toimia tienraivaajina laajamittaiselle realistisen reaaliaikaisen polunseurannan käyttöönotolle.Photo-realistic offline rendering is currently done with path tracing, because it naturally produces many real-life light effects such as reflections, refractions and caustics. These effects are hard to achieve with other rendering techniques. However, path tracing in real time is complicated due to its high computational demand. Therefore, current real-time path tracing systems can only generate very noisy estimate of the final frame, which is then denoised with a post-processing reconstruction filter. A path tracing-based rendering system capable of filling the high resolution in the low latency requirements of mixed reality devices would generate a very immersive user experience. One possible solution for fulfilling these requirements could be foveated path tracing, wherein the rendering resolution is reduced in the periphery of the human visual system. The key challenge is that the foveated path tracing in the periphery is both sparse and noisy, placing high demands on the reconstruction filter. This thesis proposes the first regression-based reconstruction filter for path tracing that runs in real time. The filter is designed for highly noisy one sample per pixel inputs. The fast execution is accomplished with blockwise processing and fast implementation of the regression. In addition, a novel Visual-Polar coordinate space which distributes the samples according to the contrast sensitivity model of the human visual system is proposed. The specialty of Visual-Polar space is that it reduces both path tracing and reconstruction work because both of them can be done with smaller resolution. These techniques enable a working prototype of a foveated path tracing system and may work as a stepping stone towards wider commercial adoption of photo-realistic real-time path tracing

Towards interactive global illumination effects via sequential Monte Carlo adaptation

Journal ArticleThis paper presents a novel method that effectively combines both control variates and importance sampling in a sequential Monte Carlo context while handling general single-bounce global illumination effects. The radiance estimates computed during the rendering process are cached in an adaptive per-pixel structure that defines dynamic predicate functions for both variance reduction techniques and guarantees well-behaved PDFs, yielding continually increasing efficiencies thanks to a marginal computational overhead

Perceptual Error Optimization for {Monte Carlo} Rendering

Realistic image synthesis involves computing high-dimensional light transport integrals which in practice are numerically estimated using Monte Carlo integration. The error of this estimation manifests itself in the image as visually displeasing aliasing or noise. To ameliorate this, we develop a theoretical framework for optimizing screen-space error distribution. Our model is flexible and works for arbitrary target error power spectra. We focus on perceptual error optimization by leveraging models of the human visual system's (HVS) point spread function (PSF) from halftoning literature. This results in a specific optimization problem whose solution distributes the error as visually pleasing blue noise in image space. We develop a set of algorithms that provide a trade-off between quality and speed, showing substantial improvements over prior state of the art. We perform evaluations using both quantitative and perceptual error metrics to support our analysis, and provide extensive supplemental material to help evaluate the perceptual improvements achieved by our methods

Image synthesis based on a model of human vision

Modern computer graphics systems are able to construct renderings of such high quality that viewers are deceived into regarding the images as coming from a photographic source. Large amounts of computing resources are expended in this rendering process, using complex mathematical models of lighting and shading. However, psychophysical experiments have revealed that viewers only regard certain informative regions within a presented image. Furthermore, it has been shown that these visually important regions contain low-level visual feature differences that attract the attention of the viewer. This thesis will present a new approach to image synthesis that exploits these experimental findings by modulating the spatial quality of image regions by their visual importance. Efficiency gains are therefore reaped, without sacrificing much of the perceived quality of the image. Two tasks must be undertaken to achieve this goal. Firstly, the design of an appropriate region-based model of visual importance, and secondly, the modification of progressive rendering techniques to effect an importance-based rendering approach. A rule-based fuzzy logic model is presented that computes, using spatial feature differences, the relative visual importance of regions in an image. This model improves upon previous work by incorporating threshold effects induced by global feature difference distributions and by using texture concentration measures. A modified approach to progressive ray-tracing is also presented. This new approach uses the visual importance model to guide the progressive refinement of an image. In addition, this concept of visual importance has been incorporated into supersampling, texture mapping and computer animation techniques. Experimental results are presented, illustrating the efficiency gains reaped from using this method of progressive rendering. This visual importance-based rendering approach is expected to have applications in the entertainment industry, where image fidelity may be sacrificed for efficiency purposes, as long as the overall visual impression of the scene is maintained. Different aspects of the approach should find many other applications in image compression, image retrieval, progressive data transmission and active robotic vision

Interactive global illumination on the CPU

Computing realistic physically-based global illumination in real-time remains one of the major goals in the fields of rendering and visualisation; one that has not yet been achieved due to its inherent computational complexity. This thesis focuses on CPU-based interactive global illumination approaches with an aim to develop generalisable hardware-agnostic algorithms. Interactive ray tracing is reliant on spatial and cache coherency to achieve interactive rates which conflicts with needs of global illumination solutions which require a large number of incoherent secondary rays to be computed. Methods that reduce the total number of rays that need to be processed, such as Selective rendering, were investigated to determine how best they can be utilised. The impact that selective rendering has on interactive ray tracing was analysed and quantified and two novel global illumination algorithms were developed, with the structured methodology used presented as a framework. Adaptive Inter- leaved Sampling, is a generalisable approach that combines interleaved sampling with an adaptive approach, which uses efficient component-specific adaptive guidance methods to drive the computation. Results of up to 11 frames per second were demonstrated for multiple components including participating media. Temporal Instant Caching, is a caching scheme for accelerating the computation of diffuse interreflections to interactive rates. This approach achieved frame rates exceeding 9 frames per second for the majority of scenes. Validation of the results for both approaches showed little perceptual difference when comparing against a gold-standard path-traced image. Further research into caching led to the development of a new wait-free data access control mechanism for sharing the irradiance cache among multiple rendering threads on a shared memory parallel system. By not serialising accesses to the shared data structure the irradiance values were shared among all the threads without any overhead or contention, when reading and writing simultaneously. This new approach achieved efficiencies between 77% and 92% for 8 threads when calculating static images and animations. This work demonstrates that, due to the flexibility of the CPU, CPU-based algorithms remain a valid and competitive choice for achieving global illumination interactively, and an alternative to the generally brute-force GPU-centric algorithms