Stereo Endoscopic Image Super-Resolution Using Disparity-Constrained Parallel Attention

• URL: http://arxiv.org/abs/2003.08539v1
• Date: Thu, 19 Mar 2020 02:12:08 GMT
• Title: Stereo Endoscopic Image Super-Resolution Using Disparity-Constrained Parallel Attention
• Authors: Tianyi Zhang, Yun Gu, Xiaolin Huang, Enmei Tu and Jie Yang
• Abstract summary: We propose a disparity-constrained stereo super-resolution network (DCSSRnet) to simultaneously compute a super-resolved image in a stereo image pair. Experiment results on laparoscopic images demonstrate that the proposed framework outperforms current SR methods on both quantitative and qualitative evaluations.
• Score: 29.536587392367025
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: With the popularity of stereo cameras in computer assisted surgery techniques, a second viewpoint would provide additional information in surgery. However, how to effectively access and use stereo information for the super-resolution (SR) purpose is often a challenge. In this paper, we propose a disparity-constrained stereo super-resolution network (DCSSRnet) to simultaneously compute a super-resolved image in a stereo image pair. In particular, we incorporate a disparity-based constraint mechanism into the generation of SR images in a deep neural network framework with an additional atrous parallax-attention modules. Experiment results on laparoscopic images demonstrate that the proposed framework outperforms current SR methods on both quantitative and qualitative evaluations. Our DCSSRnet provides a promising solution on enhancing spatial resolution of stereo image pairs, which will be extremely beneficial for the endoscopic surgery.

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