Objective no-reference stereoscopic image quality prediction based on 2d image features and relative disparity

Z. M.Parvez Sazzad*, Roushain Akhter, J. Baltes, Y. Horita

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)

Abstract

Stereoscopic images are widely used to enhance the viewing experience of three-dimensional (3D) imaging and communication system. In this paper, we propose an image feature and disparity dependent quality evaluation metric, which incorporates human visible system characteristics. We believe perceived distortions and disparity of any stereoscopic image are strongly dependent on local features, such as edge (i.e., nonplane areas of an image) and nonedge (i.e., plane areas of an image) areas within the image. Therefore, a no-reference perceptual quality assessment method is developed for JPEG coded stereoscopic images based on segmented local features of distortions and disparity. Local feature information such as edge and non-edge area based relative disparity estimation, as well as the blockiness and the edge distortion within the block of images are evaluated in this method. Subjective stereo image database is used for evaluation of the metric. The subjective experiment results indicate that our metric has sufficient prediction performance.

Original languageEnglish
Article number256130
JournalAdvances in Multimedia
Volume2012
DOIs
Publication statusPublished - 2012
Externally publishedYes

ASJC Scopus subject areas

  • General Computer Science

Fingerprint

Dive into the research topics of 'Objective no-reference stereoscopic image quality prediction based on 2d image features and relative disparity'. Together they form a unique fingerprint.

Cite this