By the same authors

Stereoscopic image quality metrics and compression

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Stereoscopic image quality metrics and compression. / Gorley, Paul; Holliman, Nicolas Steven.

SPIE Proceedings : Stereoscopic displays and applications XIX. Vol. 6803 SPIE--The International Society for Optical Engineering, 2008. p. n/a.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Gorley, P & Holliman, NS 2008, Stereoscopic image quality metrics and compression. in SPIE Proceedings : Stereoscopic displays and applications XIX. vol. 6803, SPIE--The International Society for Optical Engineering, pp. n/a. https://doi.org/10.1117/12.763530

APA

Gorley, P., & Holliman, N. S. (2008). Stereoscopic image quality metrics and compression. In SPIE Proceedings : Stereoscopic displays and applications XIX (Vol. 6803, pp. n/a). SPIE--The International Society for Optical Engineering. https://doi.org/10.1117/12.763530

Vancouver

Gorley P, Holliman NS. Stereoscopic image quality metrics and compression. In SPIE Proceedings : Stereoscopic displays and applications XIX. Vol. 6803. SPIE--The International Society for Optical Engineering. 2008. p. n/a https://doi.org/10.1117/12.763530

Author

Gorley, Paul ; Holliman, Nicolas Steven. / Stereoscopic image quality metrics and compression. SPIE Proceedings : Stereoscopic displays and applications XIX. Vol. 6803 SPIE--The International Society for Optical Engineering, 2008. pp. n/a

Bibtex - Download

@inproceedings{579301edc2de4406885c997511adfdf5,
title = "Stereoscopic image quality metrics and compression",
abstract = "We are interested in metrics for automatically predicting the compression settings for stereoscopic images so that we can minimize file size, but still maintain an acceptable level of image quality. Initially we investigate how Peak Signal to Noise Ratio (PSNR) measures the quality of varyingly coded stereoscopic image pairs. Our results suggest that symmetric, as opposed to asymmetric stereo image compression, will produce significantly better results. However, PSNR measures of image quality are widely criticized for correlating poorly with perceived visual quality. We therefore consider computational models of the Human Visual System (HVS) and describe the design and implementation of a new stereoscopic image quality metric. This, point matches regions of high spatial frequency between the left and right views of the stereo pair and accounts for HVS sensitivity to contrast and luminance changes at regions of high spatial frequency, using Michelson's Formula and Peli's Band Limited Contrast Algorithm. To establish a baseline for comparing our new metric with PSNR we ran a trial measuring stereoscopic image encoding quality with human subjects, using the Double Stimulus Continuous Quality Scale (DSCQS) from the ITU-R BT.500-11 recommendation. The results suggest that our new metric is a better predictor of human image quality preference than PSNR and could be used to predict a threshold compression level for stereoscopic image pairs.",
author = "Paul Gorley and Holliman, {Nicolas Steven}",
year = "2008",
month = "4",
day = "2",
doi = "10.1117/12.763530",
language = "English",
isbn = "9780819469755",
volume = "6803",
pages = "n/a",
booktitle = "SPIE Proceedings",
publisher = "SPIE--The International Society for Optical Engineering",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - Stereoscopic image quality metrics and compression

AU - Gorley, Paul

AU - Holliman, Nicolas Steven

PY - 2008/4/2

Y1 - 2008/4/2

N2 - We are interested in metrics for automatically predicting the compression settings for stereoscopic images so that we can minimize file size, but still maintain an acceptable level of image quality. Initially we investigate how Peak Signal to Noise Ratio (PSNR) measures the quality of varyingly coded stereoscopic image pairs. Our results suggest that symmetric, as opposed to asymmetric stereo image compression, will produce significantly better results. However, PSNR measures of image quality are widely criticized for correlating poorly with perceived visual quality. We therefore consider computational models of the Human Visual System (HVS) and describe the design and implementation of a new stereoscopic image quality metric. This, point matches regions of high spatial frequency between the left and right views of the stereo pair and accounts for HVS sensitivity to contrast and luminance changes at regions of high spatial frequency, using Michelson's Formula and Peli's Band Limited Contrast Algorithm. To establish a baseline for comparing our new metric with PSNR we ran a trial measuring stereoscopic image encoding quality with human subjects, using the Double Stimulus Continuous Quality Scale (DSCQS) from the ITU-R BT.500-11 recommendation. The results suggest that our new metric is a better predictor of human image quality preference than PSNR and could be used to predict a threshold compression level for stereoscopic image pairs.

AB - We are interested in metrics for automatically predicting the compression settings for stereoscopic images so that we can minimize file size, but still maintain an acceptable level of image quality. Initially we investigate how Peak Signal to Noise Ratio (PSNR) measures the quality of varyingly coded stereoscopic image pairs. Our results suggest that symmetric, as opposed to asymmetric stereo image compression, will produce significantly better results. However, PSNR measures of image quality are widely criticized for correlating poorly with perceived visual quality. We therefore consider computational models of the Human Visual System (HVS) and describe the design and implementation of a new stereoscopic image quality metric. This, point matches regions of high spatial frequency between the left and right views of the stereo pair and accounts for HVS sensitivity to contrast and luminance changes at regions of high spatial frequency, using Michelson's Formula and Peli's Band Limited Contrast Algorithm. To establish a baseline for comparing our new metric with PSNR we ran a trial measuring stereoscopic image encoding quality with human subjects, using the Double Stimulus Continuous Quality Scale (DSCQS) from the ITU-R BT.500-11 recommendation. The results suggest that our new metric is a better predictor of human image quality preference than PSNR and could be used to predict a threshold compression level for stereoscopic image pairs.

U2 - 10.1117/12.763530

DO - 10.1117/12.763530

M3 - Conference contribution

SN - 9780819469755

VL - 6803

SP - n/a

BT - SPIE Proceedings

PB - SPIE--The International Society for Optical Engineering

ER -