Joint just noticeable difference model based on depth perception for stereoscopic images

Abstract

Just noticeable difference (JND) model can reflect the least perceptible distortion from images, including 2D images and stereoscopic images. As we know, for the perception of human visual system (HVS), stereoscopic images have quite different characteristics from 2D images, since stereoscopic images contain not only planar information, but also depth information. This paper proposes a joint JND (JJND) model based on depth perception for stereoscopic images. Firstly, disparity estimation is performed in order to decompose the image into the occlusion region and the non-overlapped region. Then, different JND thresholds are applied on different regions, according to the depth information of the region, which can be derived from the disparity of the region. Experimental results verified our model's validity for stereoscopic images. © 2011 IEEE.