• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.197-200
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• 2005

Super resolution image reconstruction method refers to image processing algorithms that produce a high resolution(HR) image from observed several low resolution(LR) images of the same scene. This method is proved to be useful in many practical cases where multiple frames of the same scene can be obtained, such as satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. In this paper we applied super resolution reconstruction method in spatial domain to video sequences. Test images are adjacently sampled images from continuous video sequences and overlapped for high rate. We constructed the observation model between the HR images and LR images applied by the Maximum A Posteriori(MAP) reconstruction method that is one of the major methods in the super resolution grid construction. Based on this method, we reconstructed high resolution images from low resolution images and compared the results with those from other known interpolation methods.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.199-202
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• 2003

In this paper, we propose a new 3D coding method for heterogeneous systems over enhanced Access Grid (e-AG) with 3D display using spatio-temporal scalability. The proposed encoder produces four bit-streams: one base layer and enhancement layer l, 2 and 3. The base layer represents a video sequence for left eye with lower spatial resolution. An enhancement layer l provides additional bit-stream needed for reproduction of frames produced in base layer with full resolution. Similarly, the enhancement layer 2 represents a video sequence for right eye with lower spatial resolution and an enhancement layer 3 provides additional bit-stream needed for reproduction of its reference pictures with full resolution. In this system, temporal resolution reduction is obtained by dropping B-frames in the receiver according to network condition. The receiver system can select the spatial and temporal resolution of video sequence with its display condition by properly combining bit-streams.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.132-141
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• 2019

The necessity of transmitting video data over a narrow-bandwidth exists steadily despite that video service over broadband is common. In this paper, we propose a scalable video coding framework for low-resolution video transmission over a very narrow-bandwidth network by super-resolution of decoded frames of a base layer using a convolutional neural network based super resolution technique to improve the coding efficiency by using it as a prediction for the enhancement layer. In contrast to the conventional scalable high efficiency video coding (SHVC) standard, in which upscaling is performed with a fixed filter, we propose a scalable video coding framework that replaces the existing fixed up-scaling filter by using the trained convolutional neural network for super-resolution. For this, we proposed a neural network structure with skip connection and residual learning technique and trained it according to the application scenario of the video coding framework. For the application scenario where a video whose resolution is $352{\times}288$ and frame rate is 8fps is encoded at 110kbps, the quality of the proposed scalable video coding framework is higher than that of the SHVC framework.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7C
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• pp.654-662
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• 2009

Video streams for mobile video streaming can be encoded to fit the available network bandwidth by controlling three factors: temporal resolution, spatial resolution, and picture quality. The controlling of picture quality by modifying the quantization parameter (QP) is most widely used. In this paper, we demonstrate that reducing the spatial resolution adaptively can be more efficient in terms of picture quality and energy consumption in low bit-rate environment, and present a model to find the optimal spatial resolution for the available bandwidth. Adaptive spatial resolution control scheme is especially effective when the bandwidth between the video server and the mobile device varies considerably with time, and when the mobile device is sensitive to energy consumption. Our scheme can improve the picture quality by approximately O.5dB and reduce energy consumption by more than 50% compared to the conventional video coding in low bit-rate environment.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.306-314
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• 2019

Since the resolutions of videos increase rapidly, there are continuing needs for effective video compression methods despite an increase in the transmission bandwidth. In order to satisfy such a demand, a reconstructive video coding (RVC) method by using a super resolution has been proposed. Since RVC reduces the resolution of the input video, when frames are compressed to the same size, the number of bits per pixel increases, thereby reducing coding artifacts caused by video coding. However, RVC method using super resolution is not effective in all target bitrates. Comparing the size of the loss generated while downsizing the resolution and the size of the loss caused by the video compression, only when the size of loss generated in the video compression is larger, RVC method can perform the improved compression performance compared to direct video coding. In particular, since HEVC has considerably higher compression performance than the previous standard video codec, it can be experimentally confirmed that the compression distortions become larger than the distortions of downsizing the resolution only in the very low-bitrate conditions. In this paper, we applied RVC based HEVC in various video types and measured the target bitrates that RVC method can be effectively applied.

• Journal of Space Technology and Applications
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• v.3 no.3
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• pp.257-279
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• 2023

Korea Aerospace Research Institute has developed 6U Nano-Satellite high resolution video and image (HiREV) for the purpose of developing core technology for deep space exploration. The 6U HiREV Nano-Satellite has a mission of high-resolution image and video for earth observation, and the thermal pointing error between the lens and the camera module can occur due to the high temperature in camera module on mission mode. The thermal pointing error has a large effect on the resolution, so thermal design should solve it because the HiREV optical camera is developed based on commercial products that are the industrial level. So, when it operates in space, the thermal design is needed, because it has the best performance at room temperature. In this paper, three passive thermal designs were performed for the camera mission payload, and the thermal design was proved to be effective by performing on-orbit thermal analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.232-248
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• 2014

A series of kernel regression (KR) algorithms, such as the classic kernel regression (CKR), the 2- and 3-D steering kernel regression (SKR), have been proposed for image and video super-resolution. In existing KR frameworks, a single algorithm is usually adopted and applied for a whole image/video, regardless of region characteristics. However, their performances and computational efficiencies can differ in regions of different characteristics. To take full advantage of the KR algorithms and avoid their disadvantage, this paper proposes a kernel regression framework for video super-resolution. In this framework, each video frame is first analyzed and divided into three types of regions: flat, non-flat-stationary, and non-flat-moving regions. Then different KR algorithm is selected according to the region type. The CKR and 2-D SKR algorithms are applied to flat and non-flat-stationary regions, respectively. For non-flat-moving regions, this paper proposes a similarity-assisted steering kernel regression (SASKR) algorithm, which can give better performance and higher computational efficiency than the 3-D SKR algorithm. Experimental results demonstrate that the computational efficiency of the proposed framework is greatly improved without apparent degradation in performance.

• Journal of Broadcast Engineering
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• v.21 no.5
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• pp.651-661
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• 2016

최근의 디지털 사이니지는 대형 고해상도 디스플레이를 이용해 사용자에게 초고해상도 파노라마형태의 볼거리를 제공하거나 사용자와 인터렉션 등을 통해 맞춤형광고를 제공하는 등 다양한 형태로 발전하고 있다. 또 개방형 디지털 사이니지의 발전과 함께 대형 멀티 사이니지를 이용한 초고화질 영상콘텐츠를 다양한 서비스 단말장치의 연동과 웹기반의 상호운용성을 갖춘 관리시스템이 활발히 연구될 것으로 보인다. 본 논문에서는 수십대에서 백여대 이상의 고해상도 디스플레이를 연동하여 초고해상도 영상표출의 기술의 구현방안과 정형화된 영상 해상도가 아닌 초고화질 영상의 개별 콘텐츠에 대한 동기화 시키는 기술을 이용하여 멀티 콘텐츠 플레이 단말기에서 고해상도 영상을 Play Sync하는 기술을 연구한다.

• Spatial Information Research
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• v.13 no.4 s.35
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• pp.345-354
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• 2005

Super resolution image reconstruction method refers to image processing algorithms that produce a high resolution(HR) image from observed several low resolution(LR) images of the same scene. This method has proven to be useful in many practical cases where multiple frames of the same scene can be obtained, such as satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. In this paper, we applied the super resolution reconstruction method in spatial domain to video sequences. Test images are adjacently sampled images from continuous video sequences and are overlapped at high rate. We constructed the observation model between the HR images and LR images applied with the Maximum A Posteriori(MAP) reconstruction method which is one of the major methods in the super resolution grid construction. Based on the MAP method, we reconstructed high resolution images from low resolution images and compared the results with those from other known interpolation methods.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.74-85
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• 2018

The research investigated the interaction effect of video resolution and device luminance on the perceived characteristics, presence, and fatigue viewing virtual reality. Experiments were composed of mixed design, and the resolution and luminance were classified into three types, HD, 2K, and 4K, and 20, 60, and 100, respectively. Participants watched video of 6-minutes randomly, and responded to the questionnaire after watching each video. The results showed that no interaction effect existed. Meanwhile, there are statistically significant differences on the luminance of depth perception, the resolution of visual intervention, and the resolution of adjustment fatigue. Also, higher resolution and luminance showed higher cognitive function, presence and fatigue.