• Journal of Satellite, Information and Communications
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• v.9 no.3
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• pp.47-52
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• 2014

This paper introduces the Optical Camera Communications (OCC) using image processing technique. The architecture and operation of OCC system are given. To enhance data rate which is limited by sampling operation of commercial 30fps camera, multi colors transmission technique is employed, leading to the importance of color image processing technique. Multi color encoding and image processing based decoding will be proposed in the paper.

• Current Optics and Photonics
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• v.3 no.6
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• pp.548-554
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• 2019

A binary encoding method for grayscale images is proposed to address their unsatisfactory decryption results from joint transform correlator (JTC) encryption systems. The method converts the encryption and decryption of grayscale images into that of binary images, and effectively improves decrypted-image quality. In the simulation, we replaced unencoded grayscale images with their binary encoded counterparts in the JTC encryption and decryption processes, then adopted a median filter to suppress saturation noise while keeping other settings unchanged. Accordingly, decrypted-image quality was clearly enhanced as the correlation coefficient (CC) between a decrypted image and its original rose from 0.8237 to 0.9473 initially, and then further to 0.9937, following the above two steps respectively. Finally, optical experimental results confirmed that the proposed encryption system works correctly.

• Journal of Biomedical Engineering Research
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• v.22 no.6
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• pp.527-534
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• 2001

Conventional stereo image acquisition uses a pair of frame grabbers in the CAS(Computer Assisted Surgery) system. In this Paper, we developed a synchronized stereo image acquisition method with only one frame grabber Two images from left and right camera each other. were merged with different color space without time delay and thus only one frame grabber was enough toy stereo image. Due to this synchronous Property of image acquisition, we can improve spatial revolution on the computation of 3D Position. Furthermore the overall costs for 3D navigator can be down and the extraction time of stereo Position tan be shortened.

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.472-476
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• 2014

The Joint Transform Correlator (JTC) has been the most suitable technique for real time optical pattern recognition and target tracking applications. This paper proposes a new application of the JTC system for an analysis of the blurring effect of the optical images caused by a defocused lens. We present the relation between the correlation peak, optical transfer function (OTF), and the amount of blurring caused by focusing error. Moreover, we show a possibility of calibrating the blurred image by simply measuring the correlation peak.

• 한국정보디스플레이학회:학술대회논문집
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• 2003.07a
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• pp.443-443
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• 2003

• Proceedings of the Optical Society of Korea Conference
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• 1999.08a
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• pp.52-53
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• 1999

• Proceedings of the Optical Society of Korea Conference
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• 1999.08a
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• pp.58-59
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• 1999

• Proceedings of the Optical Society of Korea Conference
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• 1999.08a
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• pp.160-161
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• 1999

• Proceedings of the Optical Society of Korea Conference
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• 1996.09a
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• pp.77-77
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• 1996

• Current Optics and Photonics
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• v.2 no.5
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• pp.453-459
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• 2018

We have developed a high-performance signal-processing and image-rendering heterogeneous computation system for optical coherence tomography (OCT) on mobile processor. In this paper, we reveal it by demonstrating real-time OCT image processing using a Snapdragon 800 mobile processor, with the introduction of a heterogeneous image visualization architecture (HIVA) to accelerate the signal-processing and image-visualization procedures. HIVA has been designed to maximize the computational performances of a mobile processor by using a native language compiler, which targets mobile processor, to directly access mobile-processor computing resources and the open computing language (OpenCL) for heterogeneous computation. The developed mobile image processing platform requires only 25 ms to produce an OCT image from $512{\times}1024$ OCT data. This is 617 times faster than the naïve approach without HIVA, which requires more than 15 s. The developed platform can produce 40 OCT images per second, to facilitate real-time mobile OCT image visualization. We believe this study would facilitate the development of portable diagnostic image visualization with medical imaging modality, which requires computationally expensive procedures, using a mobile processor.