论文标题
立体声内窥镜图像超分辨率使用差异约束的平行注意力
Stereo Endoscopic Image Super-Resolution Using Disparity-Constrained Parallel Attention
论文作者
论文摘要
随着计算机辅助手术技术中立体相机的普及，第二个观点将提供手术中的其他信息。但是，如何有效访问和使用立体声信息以实现超分辨率（SR）目的通常是一个挑战。在本文中，我们提出了一个差异约束的立体声超分辨率网络（DCSSRNET），以同时计算立体声图像对中的超级分辨图像。特别是，我们将基于差异的约束机制纳入了深层神经网络框架中的SR图像的产生，并具有额外的严重视差学模块。腹腔镜图像的实验结果表明，所提出的框架在定量和定性评估上都优于当前的SR方法。我们的DCSSRNET为增强立体图像对的空间分辨率提供了一种有希望的解决方案，这对内窥镜手术非常有益。
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.
