Disparity-based Error Concealment for Stereoscopic Images with Superpixel Segmentation

• Yizhang Zhang,
• Guijin Tang,
• Xiaohua Liu,
• Changming Sun,

Vol. 12, No. 9, September 29, 2018
10.3837/tiis.2018.09.014 , Download Paper (Free):

• superpixel segmentation
• Adaptive Support-Weight
• Disparity Estimation
• Adaptive Strategy
• Disparity Selection

Abstract

To solve the problem of transmission errors in stereoscopic images, this paper proposes a novel error concealment (EC) method using superpixel segmentation and adaptive disparity selection (SSADS). Our algorithm consists of two steps. The first step is disparity estimation for each pixel in a reference image. In this step, the numbers of superpixel segmentation labels of stereoscopic images are used as a new constraint for disparity matching to reduce the effect of mismatching. The second step is disparity selection for a lost block. In this step, a strategy based on boundary smoothness is proposed to adaptively select the optimal disparity which is used for error concealment. Experimental results demonstrate that compared with other methods, the proposed method has significant advantages in both objective and subjective quality assessment.

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