• 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 the Korea Society of Computer and Information
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• v.16 no.6
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• pp.71-77
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• 2011

In this paper, we propose a learning based super resolution algorithm using local block for image enhancement of vehicle license plate. Local block is defined as the minimum measure of block size containing the associative information in the image. Proposed method essentially generates appropriate local block sets suitable for various imaging conditions. In particular, local block training set is first constructed as ordered pair between high resolution local block and low resolution local block. We then generate low resolution local block training set of various size and blur conditions for matching to all possible blur condition of vehicle license plates. Finally, we perform association and merging of information to reconstruct into enhanced form of image from training local block sets. Representative experiments demonstrate the effectiveness of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2946-2952
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• 2014

Among the Example based Super Resolution(SR) techniques, Neighbor embedding(NE) has been inspired by manifold learning method, particularly locally linear embedding. However, the poor generalization of NE decreases the performance of such algorithm. The sizes of local training sets are always too small to improve the performance of NE. We propose the Learning Sparse-Neighbor Image Representation baesd on SVR having an excellent generalization ability to solve this problem. Given a low resolution image, we first use bicubic interpolation to synthesize its high resolution version. We extract the patches from this synthesized image and determine whether each patch corresponds to regions with high or low spatial frequencies. After the weight of each patch is obtained by our method, we used to learn separate SVR models. Finally, we update the pixel values using the previously learned SVRs. Through experimental results, we quantitatively and qualitatively confirm the improved results of the proposed algorithm when comparing with conventional interpolation methods and NE.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.451-457
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• 2020

Diverse sensors are equipped on P-3C Maritime Patrol Aircraft for RoKN to detect and monitor tactical targets. Tactical targets are maintained/shared by tactical computer stations which consist of a clustering network in the aircraft and displayed in various ways on TSDs(Tactical Situation Displays) for mission operators to perform their specified missions. Korea peninsula is widely covered with the sea areas and neighboured with several countries; which makes huge number of ships and aircraft deployment around the place. Due to an increase in number of sensors and enhancement of their sensitivities; we were aware of the necessity of TSD improvements to provide huge number of tactical targets and to display them efficiently. In this paper, we propose a solution for the improvements by using previous backup data and re-usage of the data, then we verify the proposal through implementation and evaluation results.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.333-336
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• 2023

Recently, the transformer model used in natural language processing is also applied to the image super resolution field, showing good performance. However, these transformer based models have a disadvantage that they are difficult to use in small mobile devices because they are complex and have many learning parameters and require high hardware resources. Therefore, in this paper, we propose a knowledge distillation technique that can effectively reduce the size of a transformer based super resolution model. As a result of the experiment, it was confirmed that by applying the proposed technique to the student model with reduced number of transformer blocks, performance similar to or higher than that of the teacher model could be obtained.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1779-1782
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• 2003

본 논문에서는 새로운 색역폭(color gamut) 매핑 방법을 이용하여 디지털 TV 디스플레이 장치의 화질을 개선하는 방법을 제안하였다. 기존에 실시간 적응이 어렵던 색역폭 매핑 방법을 실시간으로 처리하기 위한 하드웨어 구조를 제안하였으며 이를 통하여 수 나노 초 단위의 처리 속도가 필요한 디지털 TV 의 디스플레이 장치에 성공적으로 적용이 가능하였다. 또한 제안된 하드웨어 구조는 필요에 따라 색역폭 매핑 해상도의 조절이 가능하여 해상도 및 하드웨어 구현 비용을 적절히 조절할 수 있는 장점이 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.774-781
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• 2004

The HF band SSB communication of coast radio station had operated with principal axis of maritime communication until early in the 1990. But, that is changed with development of data communication and satellite technique, which have operated a few by rapidly decrement of user with accomplishment of the CMDSS. Recently, the radio system of HF band is expanded to globe maritime communication, which is support to maritime safety information and data traffic service by low charge with the SSB high speed modem. This study have proposed the digitalize method for maritime communication system using HF band in domestic.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.116-122
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• 2004

The HF band communication of roast radio station had operated with principal axis of maritime communication until early in the 1990. But, that is changed with development of data communication and satellite technique, which have operated a few by rapidly decrement of user with accomplishment of the GMDSS. Recently, the radio system of 11u band is expanded to globe maritime communication, which is support to maritime safety information and data traffic service by low charge with the SSB high speed modem. This study have proposed the digitalize method for maritime communication system using HF band in domestic.

• Proceedings of the Korea Water Resources Association Conference
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• 1987.07a
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• pp.261-261
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• 1987

황해의 조석 역학을 포함한 중규모 순환을 연구하기 위해 수립되었던 황해 조석 모델(최, 1980 ; 최, 1984)을 세격자체계로서 개선하였다. 과거 기본모델의 위도 1/5도, 경도 1/4도의 해상도(약 12 해리)는 본 모델에 의해 위도 1/15도, 경도 1/12도의 세격자체계로서 육붕 전역을 자세히 해상시켰다. 모델은 일차적으로 주태음반일주조에 의한 황해의 평균 조석 상황을 재현시키는데 이용되었으며 산정된 조류의 검증은 86년 동계의 해양관측중 해류관측결과(미국 Florida 주립대 - 성균관대 협력연구)로서 수행하였다. 계산 결과에 의하면 과거 모델보다 높은 해상력에 의해 연안에서의 조석 파급 효과가 개선되게 산정되었으므로 연안 해양학적인 각종 응용에 더 나은 입력 및 해석에 이용될 수 있다. 계산 시간간격은 69.00333초로서 1태음조석 주기당 648 timestep 을 형성하였는데 매 조석주기당 약 80 C.P.U.(분)이었으며 7번째 조석주기의 산정 결과를 분석하는데 이용하였다. 본 연구는 기보고된 세계 여타 해역의 육붕모델보다도 자세한 해상도를 갖는 3차원 모델의 결과로서 여겨진다. 아마도 육붕단의 조석 관측이 모델 개선을 위해 필수적인 사항으로 대두되는데 이는 조석 입력(예: 구주 서측 deamphidromic zone)의 중요성이 판별되었기 때문이다. 모델을 이용한 추후의 연구는 극한 상황의 3차원적 해류 분포, 대륙붕 해저 경계층 연구를 포함하는 퇴적 역학 연구 등이 될 것이다.

• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.12-20
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• 2018

Efforts have been made to reconstruct low-resolution underwater images to high-resolution ones by using the image SR (Super-Resolution) method, all to improve efficiency when acquiring side-scan sonar images. As side-scan sonar images are similar with the optical images with respect to exploiting 2-dimensional signals, conventional image restoration methods for optical images can be considered as a solution. One of the most typical super-resolution methods for optical image is a sparse coding and there are studies for verifying applicability of sparse coding method for underwater images by analyzing sparsity of underwater images. Sparse coding is a method that obtains recovered signal from input signal by linear combination of dictionary and sparse coefficients. However, it requires huge computational load to accurately estimate sparse coefficients. In this study, a sparse coding based underwater image super-resolution method is applied while a selective reconstruction method for object region is suggested to reduce the processing time. For this method, this paper proposes an edge detection and object and non object region classification method for underwater images and combine it with sparse coding based image super-resolution method. Effectiveness of the proposed method is verified by reducing the processing time for image reconstruction over 32 % while preserving same level of PSNR (Peak Signal-to-Noise Ratio) compared with conventional method.