• Journal of the Optical Society of Korea
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• v.19 no.4
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• pp.390-396
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• 2015

We propose a partial occlusion removal method for computational integral imaging reconstruction (CIIR) based on the usage of the exemplar based inpainting technique. The proposed method is an improved version of the original linear inpainting based CIIR (LI-CIIR), which uses the inpainting technique to fill in the data missing region. The LI-CIIR shows good results for images which contain objects with smooth surfaces. However, if the object has a textured surface, the result of the LI-CIIR deteriorates, since the linear inpainting cannot recover the textured data in the data missing region well. In this work, we utilize the exemplar based inpainting to fill in the textured data in the data missing region. We call the proposed method the neighboring elemental image exemplar based inpainting (NEI-exemplar inpainting) method, since it uses sources from neighboring elemental images to fill in the data missing region. Furthermore, we also propose an automatic occluding region extraction method based on the use of the mutual constraint using depth estimation (MC-DE) and the level set based bimodal segmentation. Experimental results show the validity of the proposed system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2563-2568
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• 2010

SAII (synthetic aperture integral imaging) is a useful technique to record many multi view images of 3D objects by using a moving camera and to reconstruct 3D depth images from the recorded multiviews. This is largely composed of two processes. A pickup process provides elemental images of 3D objects and a reconstruction process generates 3D depth images computationally. In this paper, a signal model for SAII is presented. We defined the granular noise and analyzed its characteristics. Our signal model revealed that we could reduce the noise in the reconstructed images and increase the computational speed by reducing the shifting distance of a single camera.

• Journal of information and communication convergence engineering
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• v.14 no.1
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• pp.57-63
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• 2016

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.

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.548-556
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• 2016

Integral imaging is an auto-stereoscopic display method that can produce 3D image of a finite viewing window through an array of micro elemental lenses. Integral imaging requires the pickup part of each elemental images acquisition and display part of reconstruction of the images. The successful reconstructed image depends on various parameters such as distance between lens arrays and display device, focal length of lenses, and a number of the array. In this paper, we present reconstruction emulator for display of Integral imaging in order to adjust parameters for 3D contents reconstruction and to observe the result from different configuration. Especially, we provide the user interface for the emulator to control the distance easily. We have confirmed through various experiments that the emulator adjusted the distance and could check error in the process of creating elemental images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.167-174
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• 2016

In this paper, we propose a generation of 2D elemental images for 3D objects using Kinect in 3D depth-priority integral imaging (DPII) display. First, we analyze a principle to pickup elemental images based on ray optics. Based on our analysis, elemental images are generated with both RGB image and depth image recorded from Kinect. We reconstruct 3D images from the elemental images with the computational integral imaging reconstruction technique and then compare various perspective images. To show the usefulness of the proposed method, we carried out the preliminary experiments. The experimental results reveal that our method can provide correct 3D images with full parallax.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.10
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• pp.1848-1853
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• 2006

In this paper, we propose a method to reconstruct resolution-improved 3D images computationally based on lenslet array model in integral imaging technique and analyze its performance. While conventional view-point reconstruction method has low resolution based on pinhole array model, the proposed method can obtain resolution-improved 3D images because of extracting multiple pixels from elemental images by use of lenslet way model. To show the usefulness of proposed method, we perform computational experiments and present its results.

• Journal of Information Display
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• v.10 no.1
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• pp.1-5
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• 2009

A novel computational integral imaging technique with enhanced depth sensitivity is proposed. For each lateral position at a given depth plane, the dissimilarity between corresponding pixels of the elemental images is measured and used as a suppressing factor for that position. The intensity values are aggregated to determine the correct depth plane of each plane object. The experimental and simulation results show that the reconstructed depth image on the incorrect depth plane is effectively suppressed, and that the depth image on the correct depth plane is reconstructed clearly without any noise. The correct depth plane is also exactly determined.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1598-1603
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• 2011

This paper describes an enhancement method for a computational pickup model. The conventional computational pickup model utilizes the ray-trace model and the pinhole model. The conventional model is very useful, however, it suffers from quality degradation of reconstructed images at long distances. To overcome the problem, we propose an accurate pickup model. The proposed model includes integration of the rays incoming to a sensor that generates a pixel, resulting in robustness on the Aliasing artifact. To show the effectiveness of the proposed method, experimental results are carried out. The results indicated that the proposed method is superior to the conventional method.

• Proceedings of the Optical Society of Korea Conference
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• 2008.02a
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• pp.179-180
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• 2008

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.180-187
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• 2021

In this paper, we present a computational volumetric reconstruction method for three-dimensional (3D) photon counting imaging with enhanced visual quality when low-resolution elemental images are used under photon-starved conditions. In conventional photon counting imaging with low-resolution elemental images, it may be difficult to estimate the 3D scene correctly because of a lack of scene information. In addition, the reconstructed 3D images may be blurred because volumetric computational reconstruction has an averaging effect. In contrast, with our method, the pixels of the elemental image rearrangement technique and a Bayesian approach are used as the reconstruction and estimation methods, respectively. Therefore, our method can enhance the visual quality and estimation accuracy of the reconstructed 3D images because it does not have an averaging effect and uses prior information about the 3D scene. To validate our technique, we performed optical experiments and demonstrated the reconstruction results.