Resolution-enhanced 3D image correlator using computationally reconstructed integral images

Park, Jaesung; Hwang, Dong‐Choon; Shin, Dong-Hak; Kim, Eun-Soo

doi:10.1016/j.optcom.2007.04.007

Cited by 41 publications

(25 citation statements)

References 16 publications

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“…[1][2][3][4][5][6][7][8][9][10][11][12][13][14] 집적 영상은 안경 및 기 타 보조기구를 사용하지 않고 렌즈릿 어레이를 이용한 한 번 의 촬영으로 관측자의 시야각 내에서 연속적 (viewing angle) 인 시점 수직수평 시차 실시간 동영상의 재생을 , , full color 지원한다. [3] 컴퓨터를 이용한 집적 영상의 복원은 가상 핀홀 어레이 를 통해서 임의의 차원 공간 평면에 물 (pinhole array) 3 체를 복원한다 컴퓨터를 이용하는 집적 영상의 복원은 복원 .…”

Section: 서 론unclassified

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Occluded Object Reconstruction and Recognition with Computational Integral Imaging

Lee¹,

Yeom²,

Kim³

et al. 2008

Hankook Kwanghak Hoeji

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This paper addresses occluded object reconstruction and recognition with computational integral imaging (II). Integral imaging acquires and reconstructs target information in the three-dimensional (3D) space. The reconstruction is performed by averaging the intensities of the corresponding pixels. The distance to the object is estimated by minimizing the sum of the standard deviation of the pixels. We adopt principal component analysis (PCA) to classify occluded objects in the reconstruction space. The Euclidean distance is employed as a metric for decision making. Experimental and simulation results show that occluded targets are successfully classified by the proposed method.

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Section: 서 론unclassified

“…[4][5][6][7] 최근에는 집적 영상을 이용한 활용 방법으로 왜곡 및 부분적으 로 가려진 장애물을 제거하고 표적을 인식하는 방법도 연구되 고 있다. [8][9][10][11] 또한 광자 계수 검출기(photon counting detector)…”

Section: 서 론unclassified

Occluded Object Reconstruction and Recognition with Computational Integral Imaging

Lee¹,

Yeom²,

Kim³

et al. 2008

Hankook Kwanghak Hoeji

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“…Recently, several approaches employed a 3D imaging technique to solve the occlusion problem [1][2][3][4][5][6][7][8][9]. Among them, integral imaging can be considered as one of the promising solutions, and thus some techniquesbased on integral imaging have been proposed for 3D recognition of partially occluded objects.…”

Section: Introductionmentioning

confidence: 99%

3D Image Correlator using Computational Integral Imaging Reconstruction Based on Modified Convolution Property of Periodic Functions

Jang¹,

Shin²,

Lee³

et al. 2014

Journal of the Optical Society of Korea

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In this paper, we propose a three-dimensional (3D) image correlator by use of computational integral imaging reconstruction based on the modified convolution property of periodic functions (CPPF) for recognition of partially occluded objects. In the proposed correlator, elemental images of the reference and target objects are picked up by a lenslet array, and subsequently are transformed to a sub-image array which contains different perspectives according to the viewing direction. The modified version of the CPPF is applied to the sub-images. This enables us to produce the plane sub-image arrays without the magnification and superimposition processes used in the conventional methods. With the modified CPPF and the sub-image arrays, we reconstruct the reference and target plane sub-image arrays according to the reconstruction plane. 3D object recognition is performed through cross-correlations between the reference and the target plane sub-image arrays. To show the feasibility of the proposed method, some preliminary experiments on the target objects are carried out and the results are presented. Experimental results reveal that the use of plane sub-image arrays enables us to improve the correlation performance, compared to the conventional method using the computational integral imaging reconstruction algorithm.

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“…Basically, there are two kinds of integral imaging reconstruction techniques, optical integral image reconstruction (OIIR) technique and computational integral imaging reconstruction (CIIR) technique ([6]- [9]). The OIIR technique has problems such as degraded image quality of the displayed 3D images caused by physical limitation of optical devices such as diffraction and interference between elemental images ( [8], [10]). In order to overcome these drawbacks of OIIR technique, a CIIR technique based on a pinhole array model has been introduced, in which 3D object can be computationally reconstructed through digital simulation of geometrical optics [8].…”

Section: Introductionmentioning

confidence: 99%

“…The OIIR technique has problems such as degraded image quality of the displayed 3D images caused by physical limitation of optical devices such as diffraction and interference between elemental images ( [8], [10]). In order to overcome these drawbacks of OIIR technique, a CIIR technique based on a pinhole array model has been introduced, in which 3D object can be computationally reconstructed through digital simulation of geometrical optics [8]. Several attempts for 3D object reconstruction and visualization using InIms have been reported in the literature ([10]- [13]).…”

Section: Introductionmentioning

confidence: 99%

Computational Technique of 3D Reconstruction in Integral Imaging using FPGA Hardware

Hussein¹,

Kishk²,

Abo-Elsoud³

2012

IJCA

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This paper presents hardware implementation for a computational 3D integral imaging reconstruction technique. The reconstruction technique is based on a single pixel extraction from corresponding elemental images of a 3D scene, which is formed using an integral imaging system. The proposed hardware exploits both of the parallel processing and memory organization features, that is available in fieldprogrammable gate array (FPGA) device to achieve several computational operations at real time. In this method the need for optical equipment such as micro-optics lens and special high-quality LCD to display 3D scene, which will make it suitable to field view TV application, is eliminated. Some experiments were carried out to show the feasibility of the proposed scheme, its result exposes that the hardware is able to process digital reconstruction at real time rate with low power consumption.

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Resolution-enhanced 3D image correlator using computationally reconstructed integral images

Cited by 41 publications

References 16 publications

Occluded Object Reconstruction and Recognition with Computational Integral Imaging

Occluded Object Reconstruction and Recognition with Computational Integral Imaging

3D Image Correlator using Computational Integral Imaging Reconstruction Based on Modified Convolution Property of Periodic Functions

Computational Technique of 3D Reconstruction in Integral Imaging using FPGA Hardware

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