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Metrics for Stereoscopic Image Compression

GORLEY, PAUL,WARD (2012) Metrics for Stereoscopic Image Compression. Doctoral thesis, Durham University.

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Metrics for automatically predicting the compression settings for stereoscopic images, to minimize file size, while still maintaining an acceptable level of image quality are investigated. This research evaluates whether symmetric or asymmetric compression produces a better quality of stereoscopic image.
Initially, how Peak Signal to Noise Ratio (PSNR) measures the quality of varyingly compressed stereoscopic image pairs was investigated. Two trials with human subjects, following the ITU-R BT.500-11 Double Stimulus Continuous Quality Scale (DSCQS) were undertaken to measure the quality of symmetric and asymmetric stereoscopic image compression. Computational models of the Human Visual System (HVS) were then investigated and a new stereoscopic image quality metric designed and implemented. The metric 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 in these regions.
The PSNR results show that symmetric, as opposed to asymmetric stereo image compression, produces significantly better results. The human factors trial suggested that in
general, symmetric compression of stereoscopic images should be used.
The new metric, Stereo Band Limited Contrast, has been demonstrated as a better predictor of human image quality preference than PSNR and can be used to predict
a perceptual threshold level for stereoscopic image compression. The threshold is the maximum compression that can be applied without the perceived image quality being
Overall, it is concluded that, symmetric, as opposed to asymmetric stereo image encoding, should be used for stereoscopic image compression. As PSNR measures of image
quality are correctly criticized for correlating poorly with perceived visual quality, the new HVS based metric was developed. This metric produces a useful threshold to provide a practical starting point to decide the level of compression to use.

Item Type:Thesis (Doctoral)
Award:Doctor of Philosophy
Keywords:Stereo Image Quality, Human Perception, Mixed Resolutions Stereo Images, Symmetric and Asymmetric Stereo image Compression
Faculty and Department:Faculty of Science > Engineering and Computing Science, School of (2008-2017)
Thesis Date:2012
Copyright:Copyright of this thesis is held by the author
Deposited On:05 Apr 2012 11:52

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