• Proceedings of the Optical Society of Korea Conference
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• 2006.07a
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• pp.113-114
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• 2006

• Journal of the Korea Computer Industry Society
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• v.6 no.5
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• pp.767-774
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• 2005

In this paper, we propose an efficient coding method of digital hologram using standard compression tools for video images. At first, we convert fringe patterns into video data using a principle of CGH(Computer Generated Hologram), and then encode it. In this research, we propose a compression algorithm is made up of various method such as pre-processing for transform, local segmentation with global information of object image, frequency transform for coding, scanning to make fringe to video stream, classification of coefficients, and hybrid video coding. The proposed algorithm illustrated that it have better properties for reconstruction and compression rate than the previous methods.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.847-859
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• 2011

cDNA microarray-based comparative genomic hybridization(CGH) data includes low-intensity spots and thus a statistical strategy is needed to detect subtle differences between different cancer classes. In this study, genes displaying a high frequency of alteration in one of the different classes were selected among the pre-selected genes that show relatively large variations between genes compared to total variations. Utilizing copy-number changes of the selected genes, this study suggests a statistical approach to predict patients' classes with increased performance by pre-classifying patients with similar genetic alteration scores. Two-stage logistic regression model(TLRM) was suggested to pre-classify homogeneous patients and predict patients' classes for cancer prediction; a decision tree(DT) was combined with logistic regression on the set of informative genes. TLRM was constructed in cDNA microarray-based CGH data from the Cancer Metastasis Research Center(CMRC) at Yonsei University; it predicted the patients' clinical diagnoses with perfect matches (except for one patient among the high-risk and low-risk classified patients where the performance of predictions is critical due to the high sensitivity and specificity requirements for clinical treatments. Accuracy validated by leave-one-out cross-validation(LOOCV) was 83.3% while other classification methods of CART and DT performed as comparisons showed worse performances than TLRM.

• Korean Journal of Optics and Photonics
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• v.17 no.1
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• pp.31-37
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• 2006

We propose a digital watermarking technique using a computer generated hologram. The proposed method uses two random patterns separated from the computer generated hologram (CGH). One of those is embedded into the original image as hidden watermark information and then the reconstructed image can be obtained by an optical decoding algorithm with the other one as a decoding key. We analyze an occlusion of the watermarked image that is the original image containing the hidden pattern. The embedding process is performed digitally and reconstruction optically Computer simulation and an optical experiment are shown in support of the proposed technique.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.8
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• pp.67-75
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• 2000

In this paper, we proposed a new method to find dive parameters of an ellipse from the optical Hough transform (HT) results. The method employs the HT for detection of a straight line and the one-dimensional analysis of the resultant parameter domain. Using this algorithm, we simulated about the ellipses with different positions, and obtained the information of the ellipse with 94% accuracy in the worst case. To compare the simulation results with the experimental ones, we performed optical experiments using a HT Computer Generated Hologram (CGH) filter. Through the experiments, we showed that our results were very similar to the simulation results.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.07a
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• pp.135-136
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• 2015

컴퓨터 생성 홀로그램(CGH: computer generated hologram) 기법은 기존의 광학계 장치와 변수들을 수학적으로 모델링하여 일반 범용 컴퓨터(PC: personal computer)로도 디지털 홀로그램을 생성할 수 있는 기술이다. 이 기술은 디지털 홀로그램의 해상도와 3D 물체의 광원 수에 따라 알고리즘의 연산량이 좌우되기 때문에, 실용적인 사용을 위해서 알고리즘의 연산량을 낮추거나 하드웨어의 연산 속도를 높이는 연구가 필수적이다. 본 논문에서는 초다광원 3D 물체의 디지털 홀로그램을 고속으로 생성할 수 있는 방법을 제안한다. 제안하는 방법은 한 개의 서버 PC와 다수의 클라이언트 PC들로 구성되어 있으며, 이들은 일반적으로 사용되는 범용 GPU (graphic processing unit)가 장착되어 있다. 서버에서 3D 물체의 광원을 스캔하여 데이터화 하고, 클라이언트 PC들의 연산 능력에 따라 광원 데이터를 분할하여 클라이언트들에게 각각 전송한다. 각각의 클라이언트들은 전송받은 데이터를 이용해 다중 GPU 기반의 CGH 연산을 수행하여 간섭 패턴들을 생성하고, 생성된 패턴들은 다시 서버 PC로 재전송된다. 서버 PC로 재전송 된 패턴들이 하나로 누적되면 디지털 홀로그램이 생성된다. 본 실험에서, 기존의 방법으로는 139,655개의 광원에 대해 $1,024{\times}1,024$ 해상도의 홀로그램을 생성하는데 약 2,250 ms가 걸린 반면, 제안하는 방법은 약 478 ms의 속도로 생성할 수 있음을 확인하였다.

• Journal of Animal Science and Technology
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• v.52 no.6
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• pp.491-498
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• 2010

Copy-number variation (CNV) in particular genomic segments owing to deletions or duplications can induce changes in cellular gene expression patterns and may increase susceptibility to diseases such as cancer. The aim of this study was to examine CNVs related to the incidence of epithelial ovarian cancer in chickens. Genomic DNA was extracted from blood cells and cancerous ovaries collected from four 120-week-old White Leghorn chickens and were used for array-based comparative genome hybridization (CGH) analysis. As a result, 25 amplified and 10 deleted CNV regions were detected in chicken ovarian cancer. Of these, 10 amplified and two deleted CNV regions contained genes associated with human ovarian cancer. Our study using a chicken model may provide a better understanding of human epithelial ovarian cancer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.335-344
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• 2014

In this paper we analysis for in out signal by previous study and implement virtual master that generate CGH processor signals. Also, we propose memory address mapping. By constructing the system model of our method and by analyzing the latencies according to the memory access methods in a system including our model and several other models, the low-latency memory access method has been obtained. The proposed method is reduce number of activation in DRAM.

• Current Optics and Photonics
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• v.5 no.4
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• pp.409-420
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• 2021

We propose a method to synthesize a color non-hogel-based computer-generated-hologram (CGH) from light field data of a three-dimensional scene with a hologram pixel pitch shared for all color channels. The non-hogel-based CGH technique generates a continuous wavefront with arbitrary carrier wave from given light field data by interpreting the ray angle in the light field to the spatial frequency of the plane wavefront. The relation between ray angle and spatial frequency is, however, dependent on the wavelength, which leads to different spatial frequency sampling grid in the light field data, resulting in color aberrations in the hologram reconstruction. The proposed method sets a hologram pixel pitch common to all color channels such that the smallest blue diffraction angle covers the field of view of the light field. Then a spatial frequency sampling grid common to all color channels is established by interpolating the light field with the spatial frequency range of the blue wavelength and the sampling interval of the red wavelength. The common hologram pixel pitch and light field spatial frequency sampling grid ensure the synthesis of a color hologram without any color aberrations in the hologram reconstructions, or any loss of information contained in the light field. The proposed method is successfully verified using color light field data of various test or natural 3D scenes.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.21-30
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• 2023

Computer-generated holography requires much more computation costs and memory space rather than image processing. We implemented the diffraction calculation with low-precision and mixed-precision floating point numbers and compared the processing time and quality of the hologram with various precision. We compared diffraction quality with double, single and bfloat16 precision. bfloat16 shows 5.94x and 1.52x times faster performance than double precision and single precision. Also, bfloat16 shows lower PSNR and SSIM and higher MSE than other precision. However, there is no significant effect on reconstructed images. These results show low precision, like bfloat16, can be utilized for computer-generated holography.