Multimodal Light-Field Camera with External Optical Filters Based on Unsupervised Learning
Multimodal Light-Field Camera with External Optical Filters Based on Unsupervised Learning
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DOI：
10.5220/0011801900003417
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Takumi Shibata;Fumihiko Sakaue;J. Sato
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文献类型：
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作者：
Takumi Shibata;Fumihiko Sakaue;J. Sato
在本文中，我们提出了一种方法，通过将各种光学滤波器连接到光场（LF）相机的前面，在一个单一的镜头捕捉多模态图像。然而，当将滤光器附接到透镜的前面时，从每个视点捕获图像的结果将是多种模态的混合。因此，所提出的方法使用不需要事先学习的神经网络来分析这样的模态混合图像，以生成在所有视点处的所有模态的图像。通过如所提出的方法中那样使用外部滤波器，可以容易地切换滤波器并且根据目的实现拍摄系统的灵活配置。
: In this paper, we propose a method of capturing multimodal images in a single shot by attaching various optical filters to the front of a light-field (LF) camera. However, when a filter is attached to the front of the lens, the result of capturing images from each viewpoint will be a mixture of multiple modalities. Therefore, the proposed method uses a neural network that does not require prior learning to analyze such a modal mixture image to generate an image of all the modalities at all viewpoints. By using external filters as in the proposed method, it is possible to easily switch filters and realize a flexible configuration of the shooting system according to the purpose.