Lightfield Recovery from Its Focal Stack

Pérez, Fernando; Juan, Ángel A.; Rodríguez, María Candelaria Gil; Magdaleno, Eduardo

doi:10.1007/s10851-016-0658-4

Cited by 15 publications

(16 citation statements)

References 22 publications

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“…where α and β are the coefficients, and α + β = 1. The computation of X guided follows (12). Repeat steps (2) -( 5) until the convergence requirement or the specified number of iterations are reached.…”

Section: The Filter-based Iterative Methodsmentioning

confidence: 99%

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Filter-Based Landweber Iterative Method for Reconstructing the Light Field

Gao

2020

IEEE Access

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The light field reconstruction aims to recover the 4D light field from the 3D focal stack, so it is a severe incomplete data reconstructing problem. The Landweber iteration is a general method to find the least-square solution of the discretized linear system, which is widely used for solving such problem. The relaxation strategies of the Landweber iteration are essential for both accelerating iterative convergence and decreasing errors. As a fast and non-approximate linear-time method, the fast guided filtering has good edgepreserving smoothing properties. It can be incorporated into the light field reconstruction process to improve the precision of the reconstructed results. In this paper, we propose a filter-based Landweber iterative method by introducing the optimized relaxation strategy and the fast guided filter. Specifically, the updated image in the iteration step contains the guidance image and the image obtained by the Landweber iteration, which makes the proposed method flexible. The experimental results show that the proposed method is more practical and effective compared with the relevant reconstruction methods.INDEX TERMS Light field reconstruction, Landweber iteration, relaxation strategy, the fast guided filter.

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Section: The Filter-based Iterative Methodsmentioning

confidence: 99%

“…Mousnier et al [11] applied a masked back-projection algorithm to partially reconstruct the light field by reconstructing epipolar images from the focal stack. Perez et al [12] studied the inverse for the focal stack transform. A subset of the light field is obtained by this method.…”

Section: Related Workmentioning

confidence: 99%

Filter-Based Landweber Iterative Method for Reconstructing the Light Field

Gao

2020

IEEE Access

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“…The 3D focal stack can also be inversely converted to a 4D representation (Subaperture images, SAIs), e.g. using the focal stack based deconvolution [24] [25], or recovering from the Fourier domain [26]. The LF can be instead represented by a set of layers, each one corresponding to a different disparity value [13], and computed using a fast disparity regularized least square regression in frequency domain.…”

Section: Light Field Representationmentioning

confidence: 99%

A Light Field FDL-HSIFT Feature in Scale-Disparity Space

Xiao¹,

Zhang²,

Jin³

et al. 2021

2021 IEEE International Conference on Image Processing (ICIP)

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Many computer vision applications rely on feature matching, hence the need for computationally efficient and robust 4D light field (LF) feature detectors and descriptors for applications using this imaging modality. In this paper, we propose a novel LF feature extraction method in the scale-disparity space, based on a Fourier disparity layer representation. The proposed feature extraction takes advantage of both the Harris feature detector and SIFT descriptor, and is shown to yield more accurate feature matching, compared with the LiFF light field feature with low computational complexity. In order to evaluate the feature matching performance with the proposed descriptor, we generated synthetic LF datasets with ground truth matching points. Experimental results with synthetic and real datasets show that, our solution outperforms existing methods in terms of both feature detection robustness and feature matching accuracy.

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“…The proposed method in [15] utilizes fast discrete Fourier transform to generate refocus planes in a reasonably fast computational time. The reverse of this transformation in studied in [16] where a focal stack is used to obtain a 4D light field image set using discrete focal stack transform.…”

Section: Previous Workmentioning

confidence: 99%

Application of preconditioned alternating direction method of multipliers in depth from focal stack

Javidnia

Corcoran

2018

J. Electron. Imag.

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Post capture refocusing effect in smartphone cameras is achievable by using focal stacks. However, the accuracy of this effect is totally dependent on the combination of the depth layers in the stack. The accuracy of the extended depth of field effect in this application can be improved significantly by computing an accurate depth map which has been an open issue for decades. To tackle this issue, in this paper, a framework is proposed based on Preconditioned Alternating Direction Method of Multipliers (PADMM) for depth from the focal stack and synthetic defocus application. In addition to its ability to provide high structural accuracy and occlusion handling, the optimization function of the proposed method can, in fact, converge faster and better than state of the art methods. The evaluation has been done on 21 sets of focal stacks and the optimization function has been compared against 5 other methods. Preliminary results indicate that the proposed method has a better performance in terms of structural accuracy and optimization in comparison to the current state of the art methods.

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Lightfield Recovery from Its Focal Stack

Cited by 15 publications

References 22 publications

Filter-Based Landweber Iterative Method for Reconstructing the Light Field

Filter-Based Landweber Iterative Method for Reconstructing the Light Field

A Light Field FDL-HSIFT Feature in Scale-Disparity Space

Application of preconditioned alternating direction method of multipliers in depth from focal stack

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