• BMB Reports
• /
• 제31권4호
• /
• pp.384-390
• /
• 1998

DNA fragments (51-587 bp) were separated by capillary electrophoresis using entangled polymer, hydroxyethylcellulose, in uncoated fused silica capillary columns. The factors affecting the separation of DNA fragments with hydroxyethylcellulose media were evaluated, i.e., the concentration of buffer and entangled polymer, effects of additives (methanol, ethidium bromide, EDTA), temperature, and injection methods. Maximum performance was obtained by adding 5% methanol in 0.5% hydroxyethylcellulose solution at $30^{\circ}C$. Addition of methanol in polymer media increased the resolution of small size DNA fragments (< 100 bp). On the other hand, addition of ethidium bromide and EDTA, which are commonly used in conventional DNA separation, reduced the resolution of DNA fragments in the polymer solution. It turns out that the separation behavior of DNA in entangled polymer is more sensitive to the running condition compared to that in polyacrylamide gel-filled capillary, but the reproducibility of DNA separation in entangled polymer is reliable.

• 한국멀티미디어학회논문지
• /
• 제21권7호
• /
• pp.795-801
• /
• 2018

In these days, various technologies to provide a service of high quality of 360 VR media contents is being studied and developed. However, rendering high-quality of media images is very difficult with the limited resources of HMD (Head Mount Display). In this paper, we designed and implemented a 360 VR Player for high quality 360 tiled video image render to HMD. Furthermore, we developed multi-resolution-based Foveated Rendering technology. By conducting several experiments, We have confirmed that it improved the performance of video rendering far more than existing tiled video rendering technology.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송공학회 2009년도 IWAIT
• /
• pp.446-449
• /
• 2009

In this paper, we present a novel method for reconstructing a super-resolution image using multi-view low-resolution images captured for depth varying scene without requiring complex analysis such as depth estimation and feature matching. The proposed method is based on the iterative back projection technique that is extended to the 3D volume domain (i.e., space + depth), unlike the conventional superresolution methods that handle only 2D translation among captured images.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송공학회 2009년도 IWAIT
• /
• pp.233-237
• /
• 2009

This paper represents a new approach which addresses quality degradation of a synthesized view, when a virtual camera moves forward. Generally, interpolation technique using only two neighboring views is used when a virtual view is synthesized. Because a size of the object increases when the virtual camera moves forward, most methods solved this by interpolation in order to synthesize a virtual view. However, as it generates a degraded view such as blurred images, we prevent a synthesized view from being blurred by using more cameras in multiview camera configuration. That is, we solve this by applying super-resolution concept which reconstructs a high resolution image from several low resolution images. Therefore, data fusion is executed by geometric warping using a disparity of the multiple images followed by deblur operation. Experimental results show that the image quality can further be improved by reducing blur in comparison with interpolation method.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송∙미디어공학회 2018년도 추계학술대회
• /
• pp.59-61
• /
• 2018

Highly compressed images typically not only have low resolution, but are also affected by compression artifacts. Performing image super-resolution (SR) directly on highly compressed image would simultaneously magnify the blocking artifacts. In this paper, a SR method based on deep learning is proposed. The method is an end-to-end trainable deep convolutional neural network which performs SR on compressed images so as to reduce compression artifacts and improve image resolution. The proposed network is divided into compression artifacts removal (CAR) part and SR reconstruction part, and the network is trained by three-step training method to optimize training procedure. Experiments on JPEG compressed images with quality factors of 10, 20, and 30 demonstrate the effectiveness of the proposed method on commonly used test images and image sets.

• ETRI Journal
• /
• 제41권4호
• /
• pp.415-425
• /
• 2019

Generative adversarial networks (GAN) have been successfully used in many image restoration tasks, including image denoising, super-resolution, and compression artifact reduction. By fully exploiting its characteristics, state-of-the-art image restoration techniques can be used to generate images with photorealistic details. However, there are many applications that require faithful rather than visually appealing image reconstruction, such as medical imaging, surveillance, and video coding. We found that previous GAN-training methods that used a loss function in the form of a weighted sum of fidelity and adversarial loss fails to reduce fidelity loss. This results in non-negligible degradation of the objective image quality, including peak signal-to-noise ratio. Our approach is to alternate between fidelity and adversarial loss in a way that the minimization of adversarial loss does not deteriorate the fidelity. Experimental results on compression-artifact reduction and super-resolution tasks show that the proposed method can perform faithful and photorealistic image restoration.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송공학회 1996년도 학술대회
• /
• pp.191-194
• /
• 1996

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송∙미디어공학회 2021년도 하계학술대회
• /
• pp.49-51
• /
• 2021

Versatile Video Coding(VVC)에서 동영상 압축 효율을 증가시키기 위한 다양한 화면 간 예측(inter prediction) 기법 중에 적응적 움직임 벡터 해상도(Adaptive motion vector resolution, 이하 AMVR) 기술이 채택되었다. 다만 AMVR을 위해서는 다양한 움직임 벡터 해상도를 테스트해야 하는 부호화 복잡도를 야기하였다. AMVR의 부호화 복잡도를 줄이기 위하여, 본 논문에서는 가벼운 신경망 모델 기반의 AMVR 조기 판별 기법을 제안한다. 이에 따라 불필요한 상황을 미리 조기에 인지하여 대응한다면 나머지 AMVR 과정을 생략할 수 있기에 부호화 복잡도의 향상을 볼 수 있다.

• 방송공학회논문지
• /
• 제25권1호
• /
• pp.105-108
• /
• 2020

본 논문은 초고해상도 기법을 이용한 실시간 저해상도 얼굴 인식 시스템을 제안한다. 기존의 비대면 얼굴인식은 거리에 따라 해상도가 저하되면서 얼굴인식의 성능이 저하되는 한계가 있다. 이러한 문제를 해결하기 위해서 초고해상도 기법에 대한 연구도 진행되었으나 비대면 얼굴인식 전 과정에 대한 통합적인 설계에 관한 연구는 미흡하다. 제안한 비대면 얼굴인식은 저해상도 영상으로 키프레임 검출, 얼굴검출, 초고해상도 기법, 특징추출 및 얼굴인식 결과까지 약 2초 이내에 수행함으로써 먼 거리에서도 비대면 얼굴인식의 성능을 향상하였다. 다양한 형태의 영상에 대한 실험을 통해 제안한 방법은 기존 방법에 비해 실시간 및 성능측면에서 저해상도 얼굴 인식이 우수함을 확인하였다.

• ETRI Journal
• /
• 제35권4호
• /
• pp.718-721
• /
• 2013

This letter proposes a novel calibration method for a multiport amplifier (MPA) to achieve optimum port-to-port isolation by correcting both the amplitude and phase of the calibration signals. The proposed architecture allows for the detection of the phase error and amplitude error in each RF signal path simultaneously and can enhance the calibrated resolution by controlling the analog phase shifters and attenuators. The designed $2{\times}2$ and $4{\times}4$ MPAs show isolation characteristics of 30 dB and 27 dB over a frequency range of 19.5 GHz to 22.5 GHz, respectively.