• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10B
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• pp.1111-1116
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• 2009

In this paper, we discuss distortion-tolerant pattern recognition using computational integral imaging reconstruction. Three-dimensional object information is captured by the integral imaging pick-up process. The captured information is numerically reconstructed at arbitrary depth-levels by averaging the corresponding pixels. We apply Fisher linear discriminant analysis combined with principal component analysis to computationally reconstructed images for the distortion-tolerant recognition. Fisher linear discriminant analysis maximizes the discrimination capability between classes and principal component analysis reduces the dimensionality with the minimum mean squared errors between the original and the restored images. The presented methods provide the promising results for the classification of out-of-plane rotated objects.

• Journal of the Optical Society of Korea
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• v.19 no.3
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• pp.248-254
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• 2015

In this paper we propose an improved version of the computational integral imaging reconstruction (CIIR) for visualizing a partially occluded object by utilizing an image inpainting technique. In the proposed method the elemental images for a partially occluded three-dimensional (3D) object are recorded through the integral imaging pickup process. Next, the depth of occlusion within the elemental images is estimated using two different CIIR methods, and the weight mask pattern for occlusion is generated. After that, we apply our image inpainting technique to the recorded elemental images to fill in the occluding area with reliable data, using information from neighboring pixels. Finally, the inpainted elemental images for the occluded region are reconstructed using the CIIR process. To verify the validity of the proposed system, we carry out preliminary experiments in which faces are the objects. The experimental results reveal that the proposed system can dramatically improve the quality of a reconstructed CIIR image.

• Journal of information and communication convergence engineering
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• v.12 no.2
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• pp.89-96
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• 2014

Here, we present a review of the proposals and advances in the field of three-dimensional (3D) imaging acquisition and display made in the last century. The most popular techniques are based on the concept of stereoscopy. However, stereoscopy does not provide real 3D experience, and produces discomfort due to the conflict between convergence and accommodation. For this reason, we focus this paper on integral imaging, which is a technique that permits the codification of 3D information in an array of 2D images obtained from different perspectives. When this array of elemental images is placed in front of an array of microlenses, the perspectives are integrated producing 3D images with full parallax and free of the convergence-accommodation conflict. In the paper we describe the principles of this technique, together with some new applications of integral imaging.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.132-138
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• 2015

Enlarging the horizontal viewing angle is an important feature of integral imaging monitors. Thus far, the horizontal viewing angle has been enlarged in different ways, such as by changing the size of the elemental images or by tilting the lens array in the capture and reconstruction stages. However, these methods are limited by the microlenses used in the capture stage and by the fact that the images obtained cannot be easily projected into different displays. In this study, we upgrade our previously reported method, called SPOC 2.0. In particular, our new approach, which can be called SPOC 2.1, enlarges the viewing angle by increasing the density of the elemental images in the horizontal direction and by an appropriate application of our transformation and reshape algorithm. To illustrate our approach, we have calculated some high-viewing angle elemental images and displayed them on an integral imaging monitor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1171-1176
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• 2011

This paper describes an analysis on the relationship between elemental image size and object locations in the computational integral imaging reconstruction and in the pickup using a periodically-distributed lenslet array. A sparse sampling effect arises from a periodically-distributed lenslet array in the pickup of 3D objects. The relationship between elemental image size and object location is also reported. Based on the analysis, a method to eliminate the sparse sampling is proposed. To show the effectiveness of the proposed method, experimental results are carried out. It turns out that the theory works.

• Korean Journal of Optics and Photonics
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• v.19 no.6
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• pp.389-393
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• 2008

Enhanced reconstruction of heavy occluded objects was represented using estimation of variance in computational integral imaging. The system is analyzed to extract information of enhanced reconstruction from an elemental images set. To obtain elemental images with enhanced resolution, low focus error, and large depth of focus, synthetic aperture integral imaging (SAII) utilizing a digital camera has been adopted. The focused areas of the reconstructed image are varied with the distance of the reconstruction plane. When an occluded object is occluded heavily, an occluded object can not be reconstructed by removing the occluding object. To obtain reconstruction of the occluded object by remedying the effect of heavy occlusion, the statistical technique has been adopted.

• Journal of information and communication convergence engineering
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• v.14 no.1
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• pp.51-56
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• 2016

In this paper, we present a three-dimensional (3-D) automatic target recognition system based on optical integral imaging reconstruction. In integral imaging, elemental images of the reference and target 3-D objects are obtained through a lenslet array or a camera array. Then, reconstructed 3-D images at various reconstruction depths can be optically generated on the output plane by back-projecting these elemental images onto a display panel. 3-D automatic target recognition can be implemented using computational integral imaging reconstruction and digital nonlinear correlation filters. However, these methods require non-trivial computation time for reconstruction and recognition. Instead, we implement 3-D automatic target recognition using optical cross-correlation between the reconstructed 3-D reference and target images at the same reconstruction depth. Our method depends on an all-optical structure to realize a real-time 3-D automatic target recognition system. In addition, we use a nonlinear correlation filter to improve recognition performance. To prove our proposed method, we carry out the optical experiments and report recognition results.

• Journal of information and communication convergence engineering
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• v.13 no.4
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• pp.275-279
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• 2015

There are several methods to record three dimensional (3D) information of objects such as lens array based integral imaging, synthetic aperture integral imaging (SAII), computer synthesized integral imaging (CSII), axially distributed image sensing (ADS), and axially distributed stereo image sensing (ADSS). ADSS method is capable of recording partially occluded 3D objects and reconstructing high-resolution slice plane images. In this paper, we present a computational method for depth extraction of partially occluded 3D objects using ADSS. In the proposed method, the high resolution elemental stereo image pairs are recorded by simply moving the stereo camera along the optical axis and the recorded elemental image pairs are used to reconstruct 3D slice images using the computational reconstruction algorithm. To extract depth information of partially occluded 3D object, we utilize the edge enhancement and simple block matching algorithm between two reconstructed slice image pair. To demonstrate the proposed method, we carry out the preliminary experiments and the results are presented.

• Journal of the Optical Society of Korea
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• v.13 no.1
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• pp.139-145
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• 2009

Computational integral imaging (CII) is a new method for 3D imaging and visualization. However, it suffers from seriously poor image quality of the reconstructed image as the reconstructed image plane increases. In this paper, to overcome this problem, we propose a CII method based on a smart pixel mapping (SPM) technique for partially occluded 3D object recognition, in which the object to be recognized is located at far distance from the lenslet array. In the SPM-based CII, the use of SPM moves a far 3D object toward the near lenslet array and then improves the image quality of the reconstructed image. To show the usefulness of the proposed method, we carry out some experiments for occluded objects and present the experimental results.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.730-733
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• 2008

In this paper, a novel CII method using a depth conversion technique is proposed. The proposed method can move a far 3D object near lenslet array and reduce the computation cost dramatically. To show the usefulness of the proposed method, we carry out the preliminary experiment and its results are presented.