Energy redistribution path tracing

Cline, David; Talbot, Justin; Egbert, Parris K.

doi:10.1145/1186822.1073330

Cited by 32 publications

(32 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Energy Redistribution Path Tracing (ERPT) ERPT as proposed by Cline [9] is an extension of MLT. The core of ERPT is to choose an energy flow filter to redistribute the energy of initial Monte Carlo sampling points.…”

Section: Mutation Strategymentioning

confidence: 99%

A view of image denoising method based on Metropolis light transport

Huang¹,

Yang²,

Liu³

2015

Advances in Computer Science Research

View full text Add to dashboard Cite

Metropolis light transport was an unbiased and robust Monte Carlo method, which could efficiently reduce noise during rendering the realistic graphics to resolve the global illumination problem. First, described basic Metropolis method, and then focused on its own characteristics to outline typical research progress based on the main algorithm influence factors in recently years. Finally, proposed the next plan after summarizing its applications effect in the scenes.

show abstract

Section: Mutation Strategymentioning

confidence: 99%

A view of image denoising method based on Metropolis light transport

Huang¹,

Yang²,

Liu³

2015

Advances in Computer Science Research

View full text Add to dashboard Cite

show abstract

“…Many of these adaptive methods can perform poorly for difficult lighting conditions and high frequency features, reducing efficiency. Path space adaptive methods based on Metropolis sampling and Markov Chain mutations [1,16] are more effective and generally improve convergence, but still suffer from noise early on and in under sampled areas.…”

Section: Related Workmentioning

confidence: 99%

“…During path tracing, we account for f t (1) to f t (d) scaled by the specular throughput f s (1) to f s (d − 1) for each pixel using a set of texture buffers, one for each layer, accounting for anti-aliasing of textures and detail maps for each pixel. The unknown BRDF scalar coefficient can be obtained by rearranging Eq.…”

Section: Poisson Based Filter Weightsmentioning

confidence: 99%

Probabilistic illumination-aware filtering for Monte Carlo rendering

Doidge

Jones

2013

Vis Comput

View full text Add to dashboard Cite

Noise removal for Monte Carlo global illumination rendering is a well known problem, and has seen significant attention from image-based filtering methods. However, many state of the art methods breakdown in the presence of high frequency features, complex lighting and materials. In this work we present a probabilistic image based noise removal and irradiance filtering framework that preserves this high frequency detail such as hard shadows and glossy reflections, and imposes no restrictions on the characteristics of the light transport or materials. We maintain perpixel clusters of the path traced samples and, using statistics from these clusters, derive an illumination aware filtering scheme based on the discrete Poisson probability distribution. Furthermore, we filter the incident radiance of the samples, allowing us to preserve and filter across high frequency and complex textures without limiting the effectiveness of the filter.

show abstract

“…Although being general rendering approaches, many of them have been successfully used for the special case of cloth rendering. Instead of using a unidirectional path tracer, bidirectional path tracing [Veach and Guibas 1994], Metropolis light transport [Veach and Guibas 1997;Pauly et al 2000] or energy redistribution path tracing [Cline et al 2005] could directly be applied as well.…”

Section: Other Approachesmentioning

confidence: 99%

Recent advances in physically-based appearance modeling of cloth

Schröder¹,

Zhao²,

Zinke³

2012

SIGGRAPH Asia 2012 Courses

View full text Add to dashboard Cite

Figure 1: Two pieces of cloth rendered using state-of-the-art volumetric techniques. Left: [Jakob et al. 2010a], Right: [Schröder et al. 2011b] Polynomial Texture Maps. Polynomial Texture Maps (PTMs) [Malzbender et al. 2001] represent a subset of a full BTF, fixing the exitant direction (using a single camera view). This makes it possible to store all information in a two dimensional multi-channel texture map. In addition to storing a color value per pixel, coefficients for polynomials are stored, approximating the variation of luminance for different light directions (a common variation of the approach is to store different coefficients for each RGB channel). Although the simple polynomial approximation cannot reproduce all variations of cloth appearance faithfully, the technique may be appealing for some applications due to its simplicity.

show abstract

Energy redistribution path tracing

Cited by 32 publications

References 11 publications

A view of image denoising method based on Metropolis light transport

A view of image denoising method based on Metropolis light transport

Probabilistic illumination-aware filtering for Monte Carlo rendering

Recent advances in physically-based appearance modeling of cloth

Contact Info

Product

Resources

About