摘要
In response to snapshot compressive imaging (SCI) in dynamic light field temporal domain, a method called dynamic light field deep equilibrium (DLFDEQ) was proposed to reconstruct high-quality dynamic light field image frames (5D data) from known encoding patterns and acquired snapshot compressed measurements (4D data). First, based on compressive sensing, the same compression encoding for each viewpoint of dynamic light field image frames in the temporal domain was adopted. Second, the reconstruction process of compressive measurements was modeled as an inverse problem with an implicit regularization term. Finally, the inverse problem was solved through a deep equilibrium model based on gradient descent (DEQ-GD). The DEQ-GD model allows for the stable reconstruction of the required dynamic light field image frames from snapshot compressive measurements. Experimental results demonstrate that proposed method can recover a 5×5 viewpoints dynamic light field composed of 4 frames of images from a single snapshot light field measurement of a 5×5 viewpoints. Compared with the current state-of-the-art methods, proposed method demonstrates stronger robustness and preserves more accurate details in the reconstructed dynamic light field image frames. By repeatedly capturing and recovering these compressive measurement values, the temporal frame rate of reconstructed image is 4 times of the original camera frame rate.
投稿的翻译标题 | Dynamic Light Field Reconstruction Based on Gradient Descent Deep Equilibrium Model (Invited) |
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源语言 | 繁体中文 |
文章编号 | 1611006 |
期刊 | Laser and Optoelectronics Progress |
卷 | 61 |
期 | 16 |
DOI | |
出版状态 | 已出版 - 8月 2024 |
关键词
- compressive imaging
- computational photography
- deep equilibrium model
- dynamic light field