Consistency analysis of focal stack-based light field reconstruction

Yang, Liu; Zhang, Runnan; Feng, Shijie; Zuo, Chuantao; Chen, Qian; Cai, Zewei

doi:10.1016/j.optlaseng.2023.107539

Cited by 4 publications

(1 citation statement)

References 25 publications

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“…Yin et al [14] proposed an iterative method that uses the guided filter to implement residual filtering during each sub-iteration, thereby reconstructing the 4D light field from the focal stack. Liu et al [15] illustrated the importance of the objectimage space consistency of focal stack-based light field reconstruction. However, the linear system is mostly inconsistent due to the influence of noise.…”

Section: Introductionmentioning

confidence: 99%

The Block Landweber Iterative Method for Light Field Reconstruction from a Focal Stack

Liu,

Qu,

Gao

2023

Photonics

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Light field imaging involves reconstructing a 4D light field from a 3D focal stack, which makes it challenging to reconstruct the light field from incomplete projection data. To address this problem, a linear projection system is established to model the focal stack imaging process using discrete refocusing equations. Based on this system, we propose the block Landweber iterative method to find the least-squares solution. This method computes the sparse matrix while iterating, which overcomes the problem of data storage. The 2-norm of the block matrix is utilized as the weighted matrix to normalize every block matrix on an identical scale, delivering an effective relaxation strategy under the convergence condition in the inconsistent case, which yields better reconstruction results and accelerates the convergence speed. The experimental results based on the image quality assessments of reference and non-reference images show that our method achieved better reconstruction results compared to other relevant common methods, even with fewer focal stacks and higher angle resolution.

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Section: Introductionmentioning

confidence: 99%

The Block Landweber Iterative Method for Light Field Reconstruction from a Focal Stack

Liu,

Qu,

Gao

2023

Photonics

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Noise sensitivity analysis of focal scanning light field imaging

Peng,

Huang,

Zuo

et al. 2024

Opt. Express

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Light field imaging can simultaneously record spatial and angular information of light signals to provide various computational imaging functions. However, traditional microlens array-based light field cameras usually suffer from a trade-off between spatial and angular resolutions. In contrast, focal scanning light field imaging (FSLFI) can digitally modulate an incident light field through an image stack captured at different focal planes and then utilize the transport-of-intensity property to computationally recover the full-resolution light field. This paper presents a unified light field reconstruction algorithm framework, which involves different types of algorithms, such as back-projection reconstruction and additive/multiplicative iterative reconstruction, for FSLFI. Based on the unified algorithm framework, we systematically analyze and investigate the FSLFI performance on noise sensitivity. Light fields are reconstructed at different noise levels to quantitatively analyze the FSLFI performances with different types of algorithms. Both simulation and actual experimental results demonstrate that the noise sensitivity and reconstruction accuracy are constrained by each other for FSLFI. Back-projection reconstruction is appropriate in high-efficiency light field reconstruction, while additive/multiplicative iterative reconstruction is suitable for high-accuracy light field imaging at high/low noise levels. These conclusions can apply to any FSLFI method covered by the unified algorithm framework, in which appropriate algorithms can be selected for high-quality light field imaging and measurement according to specific application scenarios.

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Dynamic light field reconstruction via densely connected deep equilibrium model

Wang,

Xiao

et al. 2024

Opt. Express

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High-resolution consumer plenoptic cameras usually feature low frame rates, making them not well-suited for capturing high-speed motion scenes. To compensate for this limitation, we extend the original snapshot compressive imaging system to plenoptic cameras and propose a densely connected deep equilibrium (DEQ) model for high-quality dynamic light field (LF) reconstruction, abbreviated as DLFDEQ. Specifically, we perform temporal compression encoding on a dynamic LF and model the reconstruction process as an inverse problem with an implicit regularization term. To solve this inverse problem, we present a densely connected DEQ model based on gradient descent. Our approach demonstrates stronger robustness and better detail retention than existing methods. We can practically quadruple the original camera’s frame rate by continually capturing and retrieving these measurement frames with high reconstruction accuracy.

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Consistency analysis of focal stack-based light field reconstruction

Cited by 4 publications

References 25 publications

The Block Landweber Iterative Method for Light Field Reconstruction from a Focal Stack

The Block Landweber Iterative Method for Light Field Reconstruction from a Focal Stack

Noise sensitivity analysis of focal scanning light field imaging

Dynamic light field reconstruction via densely connected deep equilibrium model

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