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Quality Index for Stereoscopic Images by Separately Evaluating Adding and Subtracting

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  • Jiachen Yang
  • Yancong Lin
  • Zhiqun Gao
  • Zhihan Lv
  • Wei Wei
  • Houbing Song

Abstract

The human visual system (HVS) plays an important role in stereo image quality perception. Therefore, it has aroused many people’s interest in how to take advantage of the knowledge of the visual perception in image quality assessment models. This paper proposes a full-reference metric for quality assessment of stereoscopic images based on the binocular difference channel and binocular summation channel. For a stereo pair, the binocular summation map and binocular difference map are computed first by adding and subtracting the left image and right image. Then the binocular summation is decoupled into two parts, namely additive impairments and detail losses. The quality of binocular summation is obtained as the adaptive combination of the quality of detail losses and additive impairments. The quality of binocular summation is computed by using the Contrast Sensitivity Function (CSF) and weighted multi-scale (MS-SSIM). Finally, the quality of binocular summation and binocular difference is integrated into an overall quality index. The experimental results indicate that compared with existing metrics, the proposed metric is highly consistent with the subjective quality assessment and is a robust measure. The result have also indirectly proved hypothesis of the existence of binocular summation and binocular difference channels.

Suggested Citation

  • Jiachen Yang & Yancong Lin & Zhiqun Gao & Zhihan Lv & Wei Wei & Houbing Song, 2015. "Quality Index for Stereoscopic Images by Separately Evaluating Adding and Subtracting," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-19, December.
  • Handle: RePEc:plo:pone00:0145800
    DOI: 10.1371/journal.pone.0145800
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    References listed on IDEAS

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    1. Fernanda da C e C Faria & Jorge Batista & Helder Araújo, 2013. "Stereoscopic Depth Perception Using a Model Based on the Primary Visual Cortex," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-10, December.
    2. Fei Zhou & Zongqing Lu & Can Wang & Wen Sun & Shu-Tao Xia & Qingmin Liao, 2015. "Image Quality Assessment Based on Inter-Patch and Intra-Patch Similarity," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-21, March.
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    Cited by:

    1. Shaoyan Gai & Feipeng Da & Xu Fang, 2016. "A Novel Camera Calibration Method Based on Polar Coordinate," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-18, October.

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