A Survey of Stereoscopic 3D Just Noticeable Difference Models

Abstract

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.

Quality Assessment for DIBR-Synthesized Images With Local and Global Distortions

“…Holes and strip distortions as two of the most obvious local artifacts are captured by analyzing local similarity. Meanwhile, based on the Just-Noticed-Difference (JND) [23], [24] threshold we calculate the difference between synthesized image and original image, and the difference based on JND is used to quality the global sharpness. The finally quality evaluation is obtained by combining the three parts abovementioned.…”

Visual Attention Guided Pixel-Wise Just Noticeable Difference Model

“…To model this perceptual characteristic, the just noticeable difference (JND) model has been presented, in which the smallest perceptual visual threshold values of the human eyes for the input image are obtained [5], [6]. Therefore, the JND models are widely applied on variable kinds of perceptual-oriented image/video related tasks, such as perceptual compression [7]- [9], perceptual quality assessment [10], [11], watermarking [12], display [13], to name a few.…”