基于视觉变换的单光子相机图像重建

Xingzheng Wang
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引用次数: 0

摘要

单光子相机是一种利用具有光子计数能力的图像传感器的新型相机。最近,这种传感器在实现高空间分辨率(例如,10^9像素/芯片)和帧速率(例如,10^6帧/秒)方面的潜力得到了证实。然而,单光子相机与传统CMOS传感器相机的输出数据存在显著差异。因此,传统的图像重建算法无法使用。vision Transformer在图像处理任务上的表现令人印象深刻,本文将设计一种即插即用算法来重建单光子相机的图像,并集成基于ViT等深度神经网络的图像处理算法。结果表明,我们的方法可以提高PSNR和SSIM。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Single-Photon Cameras Image Reconstruction Using Vision Transformer
Single-photon camera is a novel camera type that utilizes image sensor with photon-counting capability. Recently, the potential of such sensors to achieve high spatial resolutions (e.g., 10^9pixels/chip) and frame rates (e.g., 10^6frames/sec) is well-established. However, there is a significant difference in the output data between single-photon cameras and traditional CMOS sensor cameras. Therefore, conventional image reconstruction algorithms cannot be utilized. Vison Transformer has impressive performance on image processing tasks, and this paper will design a plug-and-play algorithm for reconstructing images from single-photon cameras and integrate image processing algorithms based on deep neural networks like ViT. The results demonstrate our methods can achieve improvement both in PSNR and SSIM.
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