Multi-depth filtering and occlusion suppression in 4-D light fields: Algorithms and architectures

Liyanage, Namalka; Wijenayake, Chamith; Edussooriya, Chamira U. S.; Madanayake, Arjuna; Agathoklis, P.; Bruton, L.T.; Ambikairajah, Eliathamby

doi:10.1016/j.sigpro.2019.107294

Cited by 18 publications

(3 citation statements)

References 18 publications

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“…Numerical simulations verify that the proposed shifted VFs provide significant improvement in SIR compared to conventional VFs when |v x | > 1 or |v y | > 1 pixels/frame, importantly without compromising the computational complexity. Future work includes extension of the shifted VF architecture to four-dimensional depth filters [22]- [24] and five-dimensional depth-velocity filters [25]- [27] for light field and light field video processing, respectively, in such applications as virtual reality and computational photography.…”

Section: Discussionmentioning

confidence: 99%

Improving the Attenuation of Moving Interfering Objects in Videos Using Shifted-Velocity Filtering

Edussooriya

Marasinghe

Wijenayake

et al. 2021

2021 IEEE International Symposium on Circuits and Systems (ISCAS)

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Three-dimensional space-time velocity filters may be used to enhance dynamic passband objects of interest in videos while attenuating moving interfering objects based on their velocities. In this paper, we show that the attenuation of interfering stopband objects may be significantly improved using recently proposed shifted-velocity filters. It is shown that an improvement of approximately 20 dB in signal-to-interference ratio may be achieved for stopband to passband velocity differences of only 1 pixels/frame. More importantly, this improvement is achieved without increasing the computational complexity.

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Section: Discussionmentioning

confidence: 99%

Improving the Attenuation of Moving Interfering Objects in Videos Using Shifted-Velocity Filtering

Edussooriya

Marasinghe

Wijenayake

et al. 2021

2021 IEEE International Symposium on Circuits and Systems (ISCAS)

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“…A four-dimensional (4-D) light field (LF) captures both textural and geometrical information of a scene whereas a two-dimensional (2-D) image captures only the textural information [1], [2]. We can exploit the geometrical information available with LFs to accomplish novel tasks which are not possible with 2-D images, e.g., depth estimation [3]- [6] and occlusion suppression [7]- [12].…”

Section: Introductionmentioning

confidence: 99%

Multi-Volumetric Refocusing of Light Fields

Jayaweera

Edussooriya

Wijenayake

et al. 2021

IEEE Signal Process. Lett.

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Geometric information of scenes available with fourdimensional (4-D) light fields (LFs) pave the way for postcapture refocusing. Light filed refocusing methods proposed so far have been limited to a single planar or a volumetric region of a scene. In this paper, we demonstrate simultaneous refocusing of multiple volumetric regions in LFs. To this end, we employ a 4-D sparse finite-extent impulse response (FIR) filter consisting of multiple hyperfan-shaped passbands. We design the 4-D sparse FIR filter as an optimal filter in the least-squares sense. Experimental results confirm that the proposed filter provides 64% average reduction in computational complexity with negligible degradation in the fidelity of multi-volumetric refocused LFs compared to a 4-D nonsparse FIR filter.

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“…It is dedicated to simultaneously recording the direction and intensity information of light, and its characteristic ensures that the light field camera can obtain multiple viewing angles with a single exposure [1,2]. Therefore, light field imaging can be applied to the three-dimensional (3D) reconstruction fields, such as physical measurement [3,4], depth estimation [5,6], intelligent detection [7,8], and so on.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Reconstruction of Light Field Based on Phase Similarity

Feng

Gao

et al. 2021

Sensors

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Light field imaging plays an increasingly important role in the field of three-dimensional (3D) reconstruction because of its ability to quickly obtain four-dimensional information (angle and space) of the scene. In this paper, a 3D reconstruction method of light field based on phase similarity is proposed to increase the accuracy of depth estimation and the scope of applicability of epipolar plane image (EPI). The calibration method of the light field camera was used to obtain the relationship between disparity and depth, and the projector calibration was removed to make the experimental procedure more flexible. Then, the disparity estimation algorithm based on phase similarity was designed to effectively improve the reliability and accuracy of disparity calculation, in which the phase information was used instead of the structure tensor, and the morphological processing method was used to denoise and optimize the disparity map. Finally, 3D reconstruction of the light field was realized by combining disparity information with the calibrated relationship. The experimental results showed that the reconstruction standard deviation of the two objects was 0.3179 mm and 0.3865 mm compared with the ground truth of the measured objects, respectively. Compared with the traditional EPI method, our method can not only make EPI perform well in a single scene or blurred texture situations but also maintain good reconstruction accuracy.

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Multi-depth filtering and occlusion suppression in 4-D light fields: Algorithms and architectures

Cited by 18 publications

References 18 publications

Improving the Attenuation of Moving Interfering Objects in Videos Using Shifted-Velocity Filtering

Improving the Attenuation of Moving Interfering Objects in Videos Using Shifted-Velocity Filtering

Multi-Volumetric Refocusing of Light Fields

Three-Dimensional Reconstruction of Light Field Based on Phase Similarity

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