Chapter 4

Assessment of Quality of 3D Displays

4.1 Introduction and Overview

Quality is assessed by objective and by subjective criteria. Objective criteria are centered around disparity, depth, luminance, contrast, gray shades, and values of the color components such as location in the chromaticity diagram or the noise level in an image. Subjective criteria are harder to define but are subsumed under the perception of structural similarities or the reality of a depth perception.

Objective measures such as the peak signal to noise ratio (PSNR) [1, 2] are virtually not correlated to the quality perceived by the human visual system (HVS), while subjective measures are. The investigation of structural similarities is motivated by the observation that the HVS is highly adapted to detect structural differences, especially in structures that are spatially proximate [3, 4].

Algorithms providing quality information are as a rule based on area-wise or even pixel-wise comparisons between a reference image and the image to be characterized, or between the right eye image and the left eye image, or between two neighboring areas in an image. In this context also comparisons between different properties arise such as contrast or luminance in neighboring pixels or the luminance of an object compared to the luminance in the background.

In 2D and 3D displays the investigation of disparity or depth associated with the pixels or the areas in an image plays a dominant role. It provides depth maps ...

Get 3D Displays now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.