Information Technology Reference
In-Depth Information
Chapter 3
Quality of Visual Experience for 3D
Presentation - Stereoscopic Image
Junyong You, Gangyi Jiang, Liyuan Xing, and Andrew Perkis
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Abstract.
Three-dimensional television (3DTV) technology is becoming increas-
ingly popular, as it can provide high quality and immersive experience to end users.
Stereoscopic imaging is a technique capable of recoding 3D visual information or
creating the illusion of depth. Most 3D compression schemes are developed for
stereoscopic images including applying traditional two-dimensional (2D) compres-
sion techniques, and considering theories of binocular suppression as well. The
compressed stereoscopic content is delivered to customers through communication
channels. However, both compression and transmission errors may degrade the
quality of stereoscopic images. Subjective quality assessment is the most accurate
way to evaluate the quality of visual presentations in either 2D or 3D modality,
even though it is time-consuming. This chapter will offer an introduction to related
issues in perceptual quality assessment for stereoscopic images. Our results are a
subjective quality experiment on stereoscopic images and focusing on four typical
distortion types including Gaussian blurring, JPEG compression, JPEG2000 com-
pression, and white noise. Furthermore, although many 2D image quality metrics
have been proposed that work well on 2D images, developing quality metrics for
3D visual content is almost an unexplored issue. Therefore, this chapter will further
introduce some well-known 2D image quality metrics and investigate their capa-
bilities in stereoscopic image quality assessments. As an important attribute of
stereoscopic images, disparity refers to the difference in image location of an object
seen by the left and right eyes, which has a significant impact on the stereoscopic
image quality assessment. Thus, a study on an integration of the disparity informa-
tion in quality assessment is presented. The experimental results demonstrated that
better performance can be achieved if the disparity information and original images
are combined appropriately in the stereoscopic image quality assessment.
