Comparing Real and Synthetic Images: Some Ideas About Metrics

Rushmeier, Holly; Ward, Greg; Piatko, Christine D.; Sanders, Phil; Rust, Bert W.

doi:10.1007/978-3-7091-9430-0_9

Cited by 83 publications

(66 citation statements)

References 4 publications

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“…Specular radiosity and participating media were also not examined. The accuracy of simulations was measured using a simple, view-independent error metric, rather than attempt to account for perception [10]. We feel that error metrics that model colour sensitivity and nonlinearity alone would not change our results significantly, but that metrics that model sensitivity to spatial frequencies would emphasize shadow problems and bring our objective error measure closer to a subjective one.…”

Section: Introductionmentioning

confidence: 98%

An Empirical Comparison of Progressive and Wavelet Radiosity

Willmott

Heckbert

1997

Eurographics

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Abstract. This paper presents a comparison of basic progressive and wavelet radiosity algorithms. Several variants of each algorithm were run on a set of scenes at several parameter settings, and results were examined in terms of their error, speed, and memory consumption. We did not compare more advanced variations such as clustering or discontinuity meshing. Our results show that progressive radiosity with substructuring works fairly well for all scenes. Among wavelet methods, the Haar basis works best, while higher order methods suffer because of extreme memory consumption and because poor visibility handling causes discontinuous, blocky shadows.

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Section: Introductionmentioning

confidence: 98%

An Empirical Comparison of Progressive and Wavelet Radiosity

Willmott

Heckbert

1997

Eurographics

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“…They focus on measuring the distance between images. Most of the methods compute distance between the two images is computed by finding the MSE (mean squared error) [9] d(X, Y ) = m,n i=0,j=0…”

Section: Numerical Metrics For Noise Measurementmentioning

confidence: 99%

Measurement of noise in the Monte Carlo point sampling method

Guzek¹,

Napieralski²

2011

Bulletin of the Polish Academy of Sciences: Technical Sciences

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Abstract. This paper gives a concise overview of the techniques we have used to find out the degree of measuring the quality of rendered images and a level of noise in particular. First part of the paper presents designed and conducted psychophysical experiment involving human subjective judgment. Then, two of the existing numerical image comparison methods are considered in the context of assessing the level of noise produced by global illuminations algorithms. The results of the participants' subjective responses are correlated with the data obtained from objective mathematical metrics. The main goal of research was to determine the objective and perceptual measure of quality for images with fixed sampling strategy. The results will help to establish the measures of identifying the human perception in the assessment of images generated with global illumination algorithms.

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“…We have had promising results using a simple mathematical model of the CSF, namely Rushmeier's simplification of Daly's equation [26]. However, for the results shown here we chose to take an empirical approach that allows us to achieve simplicity and speed, while still accounting for real-world factors (such as ambient light) that affect perception.…”

Section: An Empirical Perceptual Modelmentioning

confidence: 99%

Perceptually Driven Simplification for Interactive Rendering

2001

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We present a framework for accelerating interactive rendering, grounded in psychophysical models of visual perception. This framework is applicable to multiresolution rendering techniques that use a hierarchy of local simplification operations. Our method drives those local operations directly by perceptual metrics; the effect of each simplification on the final image is considered in terms of the contrast the operation will induce in the image and the spatial frequency of the resulting change. A simple and conservative perceptual model determines under what conditions the simplification operation will be perceptible, enabling imperceptible simplification in which operations are performed only when judged imperceptible. Alternatively, simplifications may be ordered according to their perceptibility, providing a principled approach to best-effort rendering. We demonstrate this framework applied to view-dependent polygonal simplification. Our approach addresses many interesting topics in the acceleration of interactive rendering, including imperceptible simplification, silhouette preservation, and gaze-directed rendering.

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Comparing Real and Synthetic Images: Some Ideas About Metrics

Cited by 83 publications

References 4 publications

An Empirical Comparison of Progressive and Wavelet Radiosity

An Empirical Comparison of Progressive and Wavelet Radiosity

Measurement of noise in the Monte Carlo point sampling method

Perceptually Driven Simplification for Interactive Rendering

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