TITLE

3D hybrid just noticeable distortion modeling for depth image-based rendering

AUTHOR(S)
Zhong, Rui; Hu, Ruimin; Wang, Zhongyuan; Wang, Shizheng
PUB. DATE
December 2015
SOURCE
Multimedia Tools & Applications;Dec2015, Vol. 74 Issue 23, p10457
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
The 3D Just Noticeable Distortion (JND) threshold in essence depends on Human Visual Sensitivity (HVS). This paper carves out a Hybrid Just Noticeable Distortion (HJND) model to measure JND threshold in the framework of Depth Image-Based Rendering (DIBR) for 3D video. The critical differences between 2D and 3D visual perception, depth saliency and geometric distortion, are combined into the HJND model because their significant influence on HVS. To save bit, the HJND model is introduced into the Multi-view Video plus Depth (MVD) encoding framework as a residual filter. After the residue is filtered by HJND and the reference model named Joint Just Noticeable Distortion (JJND), bit saving is achieved up to 28.79% and 23.53%, respectively, and the 3D impaired videos filtered by HJND and JJND have the similar subjective quality. The experiments demonstrate that HJND describes HVS for 3D video more accurately than the state-of-the-art methods.
ACCESSION #
110728193

 

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