• IEIE Transactions on Smart Processing and Computing
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• v.3 no.6
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• pp.382-387
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• 2014

A computational approach to depth estimations using a color over lapped integral imaging system is presented. The proposed imaging system acquires multiple color images simultaneously through a single lens with an array of multiple pinholes that are distributed around the optical axis. This paper proposes a computational model of the relationship between the real distance of an object and the disparity among different color images. The proposed model can serve as a computational basis of a single camera-based depth estimation.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.1131-1134
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• 2008

In this invited paper, numerical reconstruction and pattern recognition using integral imaging are overviewed. The computational integral imaging method reconstructs three-dimensional information at arbitrary depth-levels. Photon-counting nonlinear matched filtering combined with the computational reconstruction provides promising results for the application of low-light level recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2273-2286
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• 2018

This paper describes transformations between elemental image arrays and a RGBD image for three-dimensional integral imaging and transmitting systems. Two transformations are introduced and analyzed in the proposed method. Normally, a RGBD image is utilized in efficient 3D data transmission although 3D imaging and display is restricted. Thus, a pixel-to-pixel mapping is required to obtain an elemental image array from a RGBD image. However, transformations and their analysis have little attention in computational integral imaging and transmission. Thus, in this paper, we introduce two different mapping methods that are called as the forward and backward mapping methods. Also, two mappings are analyzed and compared in terms of complexity and visual quality. In addition, a special condition, named as the hole-free condition in this paper, is proposed to understand the methods analytically. To verify our analysis, we carry out experiments for test images and the results indicate that the proposed methods and their analysis work in terms of the computational cost and visual quality.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.726-729
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• 2008

In this paper, we present an interference problem among elemental images in computational integral imaging reconstruction. To overcome the interference problem, we propose a method to calculate a minimum magnification factor and the preliminary experiments are performed.

• ETRI Journal
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• v.28 no.4
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• pp.521-524
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• 2006

In this letter, we propose a novel computational integral imaging reconstruction technique based on a lenslet array model. The proposed technique provides improvement of viewing images by extracting multiple pixels from elemental images according to ray tracing based on the lenslet array model. To show the feasibility of the proposed technique, we analyze it according to ray optics and present the experimental results.

• Proceedings of the Optical Society of Korea Conference
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• 2007.07a
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• pp.257-258
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• 2007

For objective evaluation of computational integral imaging reconstruction (CIIR) schemes, a framework with the computational pickup and the CIIR process using Gaussian images is presented and characteristics of CIIR along the distance between lenslet array and objects are investigated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2363-2369
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• 2016

In this paper, we propose three-dimensional (3D) quick-response (QR) code generation technique using passive 3D integral imaging and computational integral imaging reconstruction technique. In our proposed method, we divide 2D QR code into 4 planes with different reconstruction depths and then we generate 3D QR code using synthetic aperture integral imaging and computational reconstruction. In this 3D QR code generation process, we use integral imaging which is one of 3D imaging technologies. Finally, 3D QR code can be scanned by reconstructing and merging 3D QR codes at 4 different planes with computational reconstruction. Therefore, the security level for QR code scanning may be enhanced when QR code is scanned. To show that our proposed method can improve the security level for QR code scanning, in this paper, we carry out the optical experiments and computational reconstruction. In addition, we show that 3D QR code can be scanned when reconstruction depths are known.

• Journal of the Optical Society of Korea
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• v.12 no.3
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• pp.131-135
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• 2008

Computational integral imaging(CII) has the advantage of generating the volumetric information of the 3D scene without optical devices. However, the reconstruction process of CII requires increasingly larger sizes of reconstructed images and then the computational cost increases as the distance between the lenslet array and the reconstructed output plane increases. In this paper, to overcome this problem, we propose a novel CII method using a depth conversion technique. The proposed method can move a far 3D object near the lenslet array and reduce the computational cost dramatically. To show the usefulness of the proposed method, we carry out the preliminary experiment and its results are presented.

• Current Optics and Photonics
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• v.8 no.3
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• pp.270-281
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• 2024

Information-hiding technology is introduced into an optical ghost imaging encryption scheme, which can greatly improve the security of the encryption scheme. However, in the current mainstream research on camouflage ghost imaging encryption, information hiding techniques such as digital watermarking can only hide 1/4 resolution information of a cover image, and most secret images are simple binary images. In this paper, we propose an equal-resolution image-hiding encryption scheme based on deep learning and computational ghost imaging. With the equal-resolution image steganography network based on deep learning (ERIS-Net), we can realize the hiding and extraction of equal-resolution natural images and increase the amount of encrypted information from 25% to 100% when transmitting the same size of secret data. To the best of our knowledge, this paper combines image steganography based on deep learning with optical ghost imaging encryption method for the first time. With deep learning experiments and simulation, the feasibility, security, robustness, and high encryption capacity of this scheme are verified, and a new idea for optical ghost imaging encryption is proposed.

• Journal of the Optical Society of Korea
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• v.12 no.2
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• pp.88-92
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• 2008

This paper discusses a photon-counting linear discriminant analysis (LDA) with computational integral imaging (II). The computational II method reconstructs three-dimensional (3D) objects on the reconstruction planes located at arbitrary depth-levels. A maximum likelihood estimation (MLE) can be used to estimate the Poisson parameters of photon counts in the reconstruction space. The photon-counting LDA combined with the computational II method is developed in order to classify partially occluded objects with photon-limited images. Unknown targets are classified with the estimated Poisson parameters while reconstructed irradiance images are trained. It is shown that a low number of photons are sufficient to classify occluded objects with the proposed method.