• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.218-220
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• 2021

본 논문에서는 CAR(content adaptive resampler)로 축소된 저해상도 이미지를 직접 다른 모델에 여러가지 방식으로 훈련을 시켜 성능을 개선시키고자 하였다. 본 논문에서는 단일 영상 super resolution 에 관하여 여러 기술이 존재하는 상황에 더 나은 기술을 테스트하려 하고 그를 위해 과거의 모델들에 대한 이해가 필요하여 이를 구현하였다. 현재 가장 뛰어난 성능을 보이고 있는 모델 중의 하나인 CAR 에서 복원 전 이미지를 사용하여 훈련을 시키면 더 나은 성능의 모델을 만들 수 있을 것이라고 가정하고 다양한 훈련을 통해 성능을 개선시키고자 하였다.

• Korean Journal of Optics and Photonics
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• v.13 no.3
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• pp.251-257
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• 2002

The measuring resolution and speed for wavefronts are important to improve the performance of an adaptive optics system. In this paper, we propose a fast measuring algorithm with high resolution in the Shack-Hartmann wavefront sensor for an adaptive optics system. We designed ground isolated electrical devices whose differential data signals are used to control the deformable mirror and tip/tilt mirror for robust control. The conventional mass centroid algorithm in the Shack-Hartmann sensor to measure wavefront has been widely used and provided good measurement results. In this paper, the proposed fast measuring algorithm for measuring the wavefront combines the conventional mass centroid algorithm with a weighting factor. The weighting factor is a real value estimating the real center of mass in a wavefront spot image. This proposed wavefront measuring algorithm provided fast measurement results with high resolution from experimental tests.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.34-42
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• 2010

The DOA(direction of arrival), which is based on parametric and nonparametric estimation algorithm, and adaptive beamforming algorithm for mobile communication environments are researched and analyzed. In parametric estimation algorithm, eigenvalues of the signal component and the noise component are obtained from correlation matrix of received signal by array antenna and power spectrum of the received signal is discriminated from them. Otherwise, in nonparametric estimation algorithm, we minimize a regularized objective function for finding a estimate of the signal energy as a function of angle, using nonquadratic norm which leads to supper resolution and noise suppression. And then, DOA is estimated by the signal and noise spatial steering vector, and adaptive beam-forming pattern is improved by weight vectors obtained from the spatial vector. Therefore, the improved directional estimation algorithm with regularizing sparsity constraints offers super-resolution and noise suppression compared to other algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.3
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• pp.240-248
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• 2013

In this paper, we propose a super-resolution algorithm using an adaptive weighted interpolation(AWI) and discrete wavelet transform(DWT). In general, super-resolution algorithms for single-image, probability based operations have been used for searching high-frequency components. Consequently, the complexity of the algorithm is increased and it causes the increase of processing time. In the proposed algorithm, we first find high-frequency sub-bands by using DWT. Then we apply an AWI to the obtained high-frequency sub-bands to make them have the same size as the input image. Now, the interpolated high-frequency sub-bands and input image are properly combined and perform the inverse DWT. For the experiments, we use the down-sampled version of the original image($512{\times}512$) as a test image($256{\times}256$). Through experiment, we confirm the improved efficiency of the proposed algorithm comparing with interpolation algorithms and also save the processing time comparing with the probability based algorithms even with the similar performance.

• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.166-175
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• 2020

Recently, application fields for processing and using digital image contents in various forms and types are rapidly increasing. Since image content is high value-added content, the intellectual property rights of this content must be protected in order to activate the production and use of the digital image content. In this paper, we propose a deep learning based watermark embedding and extraction network. The proposed method is to maximize the robustness of the watermark against malicious/non-malicious attacks while preserving the invisibility of the host image. This network consists of a preprocessing network that changes the watermark to have the same resolution as the host image, a watermark embedding network that embeds watermark data while maintaining the resolution of the host image by three-dimensionally concatenating the changed host image and the watermark information, and a watermark extraction network that reduces the resolution and extracts watermarks. This network verifies the invisibility and robustness of the proposed method by experimenting with various pixel value change attacks and geometric attacks against various watermark data and host images with various resolutions, and shows that this method is universal and practical.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.8 s.179
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• pp.2091-2099
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• 2000

The object of the present study is to present an adaptive wavelet-Galerkin method for the analysis of thin-walled box beam. Due to good localization properties of wavelets, wavelet methods emerge as alternative efficient solution methods to finite element methods. Most structural applications of wavelets thus far are limited in fixed-scale, non-adaptive frameworks, but this is not an appropriate use of wavelets. On the other hand, the present work appears the first attempt of an adaptive wavelet-based Galerkin method in structural problems. To handle boundary conditions, a fictitous domain method with penalty terms is employed. The limitation of the fictitious domain method is also addressed.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.3
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• pp.363-369
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• 2017

Phase-change random access memory (PRAM) has been emerged as a potential memory due to its excellent scalability, non-volatility, and random accessibility. But, as the cell current is reducing due to cell size scaling, the read-sensing window margin is also decreasing due to increased variation of cell performance distribution, resulting in a substantial loss of yield. To cope with this problem, a novel adaptive read-sensing reference current generation scheme is proposed, whose trimming range and resolution are adaptively controlled depending on process conditions. Performance evaluation in a 58-nm CMOS process indicated that the proposed read-sensing reference current scheme allowed the integral nonlinearity (INL) to be improved from 10.3 LSB to 2.14 LSB (79% reduction), and the differential nonlinearity (DNL) from 2.29 LSB to 0.94 LSB (59% reduction).

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.505-508
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• 2005

Wavelet scheme can be applied to the various remote sensing problems: conventional multi-resolution image analysis, compression of large image sets, fusion of heterogeneous sensor image and segmentation of features. In this study, we attempted wavelet-based filtering and its analysis. Traditionally, statistical methods and adaptive filter are used to manipulate noises in the image processing procedure. While we tried to filter random noise from optical image and radar image using Discrete Wavelet Transform (DW1) and Stationary Wavelet Transform (SW1) and compared with existing methods such as median filter and adaptive filter. In result, SWT preserved boundaries and reduced noises most effectively. If appropriate thresholds are used, wavelet filtering will be applied to detect road boundaries, buildings, cars and other complex features from high-resolution imagery in an urban environment as well as noise filtering

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.3
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• pp.75-81
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• 2017

This paper estimate a desired signal in a correlation wireless communication. The transmitted signal is mixed with the information signal, interference, and noise in wireless channel, and it is incident on the receiver. In this paper, we apply MUSIC algorithm and sub-array method to recover the total rank of the correlation matrix in order to estimation a desired signal among receiving signals. Through simulation, we analyze to compare the proposed method with the classical MUSIC algorithm. As a result of the simulation, the proposed method improved the resolution about 10degrees compared to the conventional MUSIC algorithm. We prove the superiority of the proposed method for the desired signal estimation in correlation channel.

• ETRI Journal
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• v.36 no.6
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• pp.894-904
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• 2014

Blind mismatch correction of time-interleaved analog-to-digital converters (TI-ADC) is a challenging task. We present a practical blind calibration technique for low-computation, low-complexity, and high-resolution applications. Its key features are: dramatically reduced computation; simple hardware; guaranteed parameter convergence with an arbitrary number of TI-ADC channels and most real-life input signals, with no bandwidth limitation; multiple Nyquist zone operation; and mixed-domain error correction. The proposed technique is experimentally verified by an M = 4 400 MSPS TI-ADC system. In a single-tone test, the proposed practical blind calibration technique suppressed mismatch spurs by 70 dB to 90 dB below the signal tone across the first two Nyquist zones (10 MHz to 390 MHz). A wideband signal test also confirms the proposed technique.