Visual difference metric for realistic image synthesis
Paper
19 May 1999 Visual difference metric for realistic image synthesis
Mark R. Bolin, Gary W. Meyer
Author Affiliations +
Proceedings Volume 3644, Human Vision and Electronic Imaging IV; (1999) https://doi.org/10.1117/12.348431
Event: Electronic Imaging '99, 1999, San Jose, CA, United States
Abstract
An accurate and efficient model of human perception has been developed to control the placement of sample in a realistic image synthesis algorithm. Previous sampling techniques have sought to spread the error equally across the image plane. However, this approach neglects the fact that the renderings are intended to be displayed for a human observer. The human visual system has a varying sensitivity to error that is based upon the viewing context. This means that equivalent optical discrepancies can be very obvious in one situation and imperceptible in another. It is ultimately the perceptibility of this error that governs image quality and should be used as the basis of a sampling algorithm. This paper focuses on a simplified version of the Lubin Visual Discrimination Metric (VDM) that was developed for insertion into an image synthesis algorithm. The sampling VDM makes use of a Haar wavelet basis for the cortical transform and a less severe spatial pooling operation. The model was extended for color including the effects of chromatic aberration. Comparisons are made between the execution time and visual difference map for the original Lubin and simplified visual difference metrics. Results for the realistic image synthesis algorithm are also presented.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark R. Bolin and Gary W. Meyer "Visual difference metric for realistic image synthesis", Proc. SPIE 3644, Human Vision and Electronic Imaging IV, (19 May 1999); https://doi.org/10.1117/12.348431
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Cited by 20 scholarly publications.
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KEYWORDS
Visualization

Image quality

Spatial frequencies

Error analysis

Visual process modeling

Optical spheres

Chromatic aberrations

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