Experimental investigation of the effect of binocular disparity on the visibility threshold of asymmetric noise in stereoscopic viewing

Kim, Hak Gu; Lee, Seong-il; Ro, Yong Man

doi:10.1364/oe.24.019607

Cited by 4 publications

(7 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In general, the visibility threshold of the asymmetric distortion is proportional to the disparity magnitude under the same background luminance and luminance contrast. This conclusion is in agreement with the observations in [95]. Furthermore, higher depth values in the 3D image may make the asymmetric distortion more tolerable by the HVS.…”

Section: ) Results and Discussionsupporting

confidence: 93%

“…More specifically, the visibility threshold of the distortion in S3D image increases as the disparity amplitude increases in the case of similar luminance intensity and luminance contrast. This is consistent with the conclusion drawn in [95].…”

Section: ) Quantitative Evaluation and Comparisonsupporting

confidence: 93%

“…In other words, BJND ignored the effect of disparity of the visual stimuli on visibility thresholds, which makes it less suitable for real-life stereoscopic images. To avoid this constraint, Kim et al [95] conducted PE to measure the binocular visibility thresholds with different disparities under various amplitudes of the asymmetric noises and background luminance levels. However, they have not studied the impact of the disparity on JND estimation for CM.…”

Section: B Pros and Consmentioning

confidence: 99%

“…The positive disparity corresponds to ''inside'' 3D effect and the negative one to ''outside'' 3D effect. In contrast to the experiment described in [95], the reference stereo pair has been used in our experimental design. This is because we considered not only the noise distortion but also the blurring and compression artifacts.…”

Section: ) Stimulimentioning

confidence: 99%

See 3 more Smart Citations

A Survey of Stereoscopic 3D Just Noticeable Difference Models

et al. 2019

View full text Add to dashboard Cite

Just noticeable difference (JND) for stereoscopic 3D content reflects the maximum tolerable distortion; it corresponds to the visibility threshold of the asymmetric distortions in the left and right contents. The 3D-JND models can be used to improve the efficiency of the 3D compression or the 3D quality assessment. Compared to 2D-JND models, the 3D-JND models appeared recently and the related literature is rather limited. In this paper, we give a deep and comprehensive study of the pixel-based 3D-JND models. To our best knowledge, this is the first review on 3D-JND models. Each model is briefly described by giving its rationale and main components in addition to providing exhaustive information about the targeted application, the pros, and cons. Moreover, we present the characteristics of the human visual system presented in these models. In addition, we analyze and compare the 3D-JND models thoroughly using qualitative and quantitative performance evaluation based on Middlebury stereo datasets. Besides, we measure the JND thresholds of the asymmetric distortion based on psychophysical experiments and compare these experimental results to the estimates from the 3D-JND models in order to evaluate the accuracy of each model. INDEX TERMS Human visual system, just noticeable difference (JND), 3D compression, 3D-JND models, 3D quality assessment.

show abstract

Section: ) Results and Discussionsupporting

confidence: 93%

Section: ) Quantitative Evaluation and Comparisonsupporting

confidence: 93%

Section: B Pros and Consmentioning

confidence: 99%

Section: ) Stimulimentioning

confidence: 99%

See 2 more Smart Citations

A Survey of Stereoscopic 3D Just Noticeable Difference Models

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Here, the binocular disparity is not taken into account, making the model less reliable for real-world images. To solve this issue, Kim et al conduct PEs to measure JND thresholds by considering both luminance adaptation (LA) and binocular disparity effects [14]. Meanwhile, a joint JND (JJND) model [5] is proposed on top of a 2D-JND model [13], relying on the assumption that the HVS has different perceptions on objects with different depth values.…”

Section: Introductionmentioning

confidence: 99%

Just Noticeable Difference Model for Asymmetrically Distorted Stereoscopic Images

Fan¹,

Larabi²,

Cheikh³

et al. 2019

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

View full text Add to dashboard Cite

In this paper, we propose a saliency-weighted stereoscopic JND (SSJND) model constructed based on psychophysical experiments, accounting for binocular disparity and spatial masking effects of the human visual system (HVS). Specifically, a disparity-aware binocular JND model is first developed using psychophysical data, and then is employed to estimate the JND threshold for non-occluded pixel (NOP). In addition, to derive a reliable 3D-JND prediction, we determine the visibility threshold for occluded pixel (OP) by including a robust 2D-JND model. Finally, SSJND thresholds of one view are obtained by weighting the resulting JND for NOP and OP with their visual saliency. Based on subjective experiments, we demonstrate that the proposed model outperforms the other 3D-JND models in terms of perceptual quality at the same noise level.

show abstract