Cai Zewei, Liu Xiaoli, Pedrini Giancarlo, Osten Wolfgang, Peng Xiang
Opt Express. 2019 Apr 29;27(9):13532-13546. doi: 10.1364/OE.27.013532.
Passive light field imaging generally uses depth cues that depend on the image structure to perform depth estimation, causing robustness and accuracy problems in complex scenes. In this study, the commonly used depth cues, defocus and correspondence, were analyzed by using phase encoding instead of the image structure. The defocus cue obtained by spatial variance is insensitive to the global spatial monotonicity of the phase-encoded field. In contrast, the correspondence cue is sensitive to the angular variance of the phase-encoded field, and the correspondence responses across the depth range have single-peak distributions. Based on this analysis, a novel active light field depth estimation method is proposed by directly using the correspondence cue in the structured light field to search for non-ambiguous depths, and thus no optimization is required. Furthermore, the angular variance can be weighted to reduce the depth estimation uncertainty according to the phase encoding information. The depth estimation of an experimental scene with rich colors demonstrated that the proposed method could distinguish different depth regions in each color segment more clearly, and was substantially improved in terms of phase consistency compared to the passive method, thus verifying its robustness and accuracy.
被动光场成像通常使用依赖于图像结构的深度线索来进行深度估计，这在复杂场景中会导致鲁棒性和准确性问题。在本研究中，通过使用相位编码而非图像结构来分析常用的深度线索——散焦和对应关系。通过空间方差获得的散焦线索对相位编码场的全局空间单调性不敏感。相比之下，对应线索对相位编码场的角方差敏感，并且在深度范围内的对应响应具有单峰分布。基于此分析，提出了一种新颖的主动光场深度估计方法，即直接在结构化光场中使用对应线索来搜索无歧义深度，因此无需优化。此外，可以根据相位编码信息对角方差进行加权，以降低深度估计的不确定性。对具有丰富色彩的实验场景进行深度估计表明，所提出的方法能够更清晰地区分每个颜色段中的不同深度区域，并且与被动方法相比，在相位一致性方面有显著提高，从而验证了其鲁棒性和准确性。
