Depth extraction of three-dimensional objects using block matching for slice images in synthetic aperture integral imaging

Lee, Joon-Jae; Lee, Byung-Gook; Yoo, Hoon

doi:10.1364/ao.50.005624

Cited by 35 publications

(10 citation statements)

References 20 publications

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“…Integral imaging is a three-dimensional imaging technology that can provide full parallax and continuous viewing points [1]. More notably, integral imaging provides naturally colored images without the use of any special glasses [2].…”

Section: Introductionmentioning

confidence: 99%

Visual Quality Enhancement of Three-Dimensional Integral Imaging Reconstruction for Partially Occluded Objects Using Exemplar-Based Image Restoration

Zhang¹,

Zhong²,

Piao

2016

Journal of information and communication convergence engineerin

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In generally, the resolution of reconstructed three-dimensional images can be seriously degraded by undesired occlusions in the integral imaging system, because the undesired information of the occlusion overlap the three-dimensional images to be reconstructed. To solve the problem of the undesired occlusion, we present an exemplar-based image restoration method in integral imaging system. In the proposed method, a minimum spanning tree-based stereo matching method is used to remove the region of undesired occlusions in each elemental image. After that, the removed occlusion region of each elemental images are re-established by using the exemplar-based image restoration method. For further improve the performance of the image restoration, the structure tensor is used to solve the filling error cause by discontinuous structures. Finally, the resolution enhanced three-dimensional images are reconstructed by using the restored elemental images. The preliminary experiments are presented to demonstrate the feasibility of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Visual Quality Enhancement of Three-Dimensional Integral Imaging Reconstruction for Partially Occluded Objects Using Exemplar-Based Image Restoration

Zhang¹,

Zhong²,

Piao

2016

Journal of information and communication convergence engineerin

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“…On the other hand, in CIIR, 3D object images can be computationally reconstructed using a digital simulation model of geometrical optics. That is, CIIR allows us to reconstruct a set of depth-dependent plane object images along the output plane through a virtual lenslet (or pinhole) array [14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Accelerated Generation Algorithm for an Elemental Image Array Using Depth Information in Computational Integral Imaging

Piao

Kwon²,

Zhang³

et al. 2013

Journal of information and communication convergence engineerin

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In this paper, an accelerated generation algorithm to effectively generate an elemental image array in computational integral imaging system is proposed. In the proposed method, the depth information of 3D object is extracted from the images picked up by a stereo camera or depth camera. Then, the elemental image array can be generated by using the proposed accelerated generation algorithm with the depth information of 3D object. The resultant 3D image generated by the proposed accelerated generation algorithm was compared with that the conventional direct algorithm for verifying the efficiency of the proposed method. From the experimental results, the accuracy of elemental image generated by the proposed method could be confirmed.

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“…Depth maps are crucial for three-dimensional (3D) imaging [1] and displaying, and have been widely used in digital holography image processing [2], [3], object reconstruction in integral imaging [4], [5], 3D object retrieval [6]–[10] and tomographic phase microscopy [11]. Practically, high fidelity depth maps of a dynamic scene are calculated or captured in a temporal discrete manner due to the intensive computational complexity of depth reconstruction.…”

Section: Introductionmentioning

confidence: 99%

Dynamic 3D Scene Depth Reconstruction via Optical Flow Field Rectification

You

Liu

et al. 2012

PLoS ONE

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In this paper, we propose a depth propagation scheme based on optical flow field rectification towards more accurate depth reconstruction. In depth reconstruction, the occlusions and low-textural regions easily result in optical flow field errors, which lead ambiguous depth value or holes without depth in the obtained depth map. In this work, a scheme is proposed to improve the precision of depth propagation and the quality of depth reconstruction for dynamic scene. The proposed scheme first adaptively detects the occlusive or low-textural regions, and the obtained vectors in optical flow field are rectified properly. Subsequently, we process the occluded and ambiguous vectors for more precise depth propagation. We further leverage the boundary enhancement filters as a post-processing to sharpen the object boundaries in obtained depth maps for better quality. Quantitative evaluations show that the proposed scheme can reconstruct depth map with higher accuracy and better quality compared with the state-of-the-art methods.

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Depth extraction of three-dimensional objects using block matching for slice images in synthetic aperture integral imaging

Cited by 35 publications

References 20 publications

Visual Quality Enhancement of Three-Dimensional Integral Imaging Reconstruction for Partially Occluded Objects Using Exemplar-Based Image Restoration

Visual Quality Enhancement of Three-Dimensional Integral Imaging Reconstruction for Partially Occluded Objects Using Exemplar-Based Image Restoration

Accelerated Generation Algorithm for an Elemental Image Array Using Depth Information in Computational Integral Imaging

Dynamic 3D Scene Depth Reconstruction via Optical Flow Field Rectification

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