• Title/Summary/Keyword: 복원영상

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A study on the improvement of the network fee system under network neutrality (망 중립성 하에서 망 이용대가 개선에 대한 연구)

  • Byun, Sangkyu;Do, Joonho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.3
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    • pp.151-161
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    • 2022
  • As Internet traffic surges due to global CPs, a request to share network investment costs has emerged in the industry. This has significantly changed the issue of the principle of network neutrality from accessibility to network fee. Some of the academic researchers had a negative view to network fees in the Internet space. However, in the industry, a number of disputes have occurred and some have escalated into court battles, and attention has been focused on the court's decision. The courts began to accept fee-for-service under network neutrality, and the government responded quickly by revising regulations. However, it still focuses on service stability, and there is no regulation that directly stipulates payment of network fee. In the study, changes in network neutrality were verified by analyzing cases of disputes between operators, court judgments, and improvement of regulations. And referring to the tragedy of the commons, the restoration of the correct price signal based on the principle of beneficiary pays was suggested as the most important solution. The payment of network fee by CP is one of the solutions.

3D Ultrasound Panoramic Image Reconstruction using Deep Learning (딥러닝을 활용한 3차원 초음파 파노라마 영상 복원)

  • SiYeoul Lee;Seonho Kim;Dongeon Lee;ChunSu Park;MinWoo Kim
    • Journal of Biomedical Engineering Research
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    • v.44 no.4
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    • pp.255-263
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    • 2023
  • Clinical ultrasound (US) is a widely used imaging modality with various clinical applications. However, capturing a large field of view often requires specialized transducers which have limitations for specific clinical scenarios. Panoramic imaging offers an alternative approach by sequentially aligning image sections acquired from freehand sweeps using a standard transducer. To reconstruct a 3D volume from these 2D sections, an external device can be employed to track the transducer's motion accurately. However, the presence of optical or electrical interferences in a clinical setting often leads to incorrect measurements from such sensors. In this paper, we propose a deep learning (DL) framework that enables the prediction of scan trajectories using only US data, eliminating the need for an external tracking device. Our approach incorporates diverse data types, including correlation volume, optical flow, B-mode images, and rawer data (IQ data). We develop a DL network capable of effectively handling these data types and introduce an attention technique to emphasize crucial local areas for precise trajectory prediction. Through extensive experimentation, we demonstrate the superiority of our proposed method over other DL-based approaches in terms of long trajectory prediction performance. Our findings highlight the potential of employing DL techniques for trajectory estimation in clinical ultrasound, offering a promising alternative for panoramic imaging.

3D Human Shape Estimation from a Silhouette Image by using Statistical Human Shape Spaces (통계적 신체 외형 데이터베이스를 활용한 실루엣으로부터의 3차원 인체 외형 예측)

  • Dasol Ahn;Sang Il Park
    • Journal of the Korea Computer Graphics Society
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    • v.29 no.1
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    • pp.13-22
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    • 2023
  • In this paper, we present a method for estimating full 3D shapes from given 2D silhouette images of human bodies. Because the silhouette only consists of the partial information on the true shape, it is an ill-posed problem. To address the problem, we use the statistical human shape space obtained from the existing large 3D human shape database. The method consists of three steps. First, we extract the boundary pixels and their appropriate normal vectors from the input silhouette images. Then, we initialize the correspondences of each pixel to the vertex of the statistically-deformable 3D human model. Finally, we numerically optimize the parameters of the statistical model to fit best to the given silhouettes. The viability and the robustness of the method is demonstrated with various experiments.

In-Loop Filtering with a Deep Network in HEVC (깊은 신경망을 사용한 HEVC의 루프 내 필터링)

  • Kim, Dongsin;Lee, So Yoon;Yang, Yoonmo;Oh, Byung Tae
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2020.11a
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    • pp.145-147
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    • 2020
  • As deep learning technology advances, there have been many attempts to improve video codecs such as High-Efficiency-Video-Coding (HEVC) using deep learning technology. One of the most researched approaches is improving filters inside codecs through image restoration researches. In this paper, we propose a method 01 replacing the sample adaptive offset (SAO) filtering with a deep neural network. The proposed method uses the deep neural network to find the optimal offset value. The proposed network consists of two subnetworks to find the offset value and its type of the signal, which can restore nonlinear and complex type of error. Experimental results show that the performance is better than the conventional HEVC in low delay P and random access mode.

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Blind Super-Resolution Kernel estimation using two images (두 장의 이미지를 활용한 이미지 화질 저하 커널 예측)

  • Cho, Sunwoo;Cho, Nam Ik
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2021.06a
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    • pp.303-306
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    • 2021
  • 이미지 초해상도는 영상 취득 과정에서 센서와 렌즈의 물리적인 한계 등으로 인하여 의해 화질이 저하된 이미지를 더 높은 배율로 복원하는 문제이다. 이미지 초해상도는 딥러닝을 통해 놀라운 성능향상을 이루었지만, 카메라로 촬영된 실제 이미지에서는 좋은 성능을 내지 못하였다. 이는 딥러닝에서는 'bicubic' 커널로 down-sampling된 합성 이미지 데이터를 사용하였던 것과 달리 실제 이미지에서는 'bicubic' 커널을 통한 화질 저하와는 다른 화질 저하, 즉 다른 커널을 통한 화질 저하가 발생하기 때문이다. 따라서 실제 이미지에 대한 성능을 높이기 위해서는 이에 대한 정확한 커널 예측이 필요하다. 최근 주목받기 시작한 이미지 초해상도를 위한 커널 예측은 초해상도를 잘 시켜주는 커널을 직접 찾는 방법[10, 13]과 이미지의 분포와 커널을 통해 다운샘플된 이미지에 대한 분포를 일치시켜주면서 커널을 예측하는 방법[14]으로 나누어져 있다. 그러나 두 방법 모두 ill-posed problem 인 커널 예측 문제를 한 장의 이미지만으로 해결하려는 것이기 때문에 정확한 예측에는 어려움이 발생한다. 따라서 본 논문에서는 두 장의 이미지를 활용한 이미지 화질 저하 커널 예측 방법을 제안한다. 제안된 방법은 두 장의 이미지가 같은 카메라를 통해 촬영되었으며 이때 이미지 화질 저하는 카메라에 의해서만 영향을 받는다는 가정을 기반으로 한다. 즉, 두 장의 이미지는 같은 커널을 통해 저하된 이미지라는 가정을 한다. 제안된 방법은 [14]에서처럼 이미지 분포를 기반으로 한 커널 예측을 진행하며, 이미지 초해상도를 진행하고자 하는 이미지 외에 참고 이미지 또한 같은 커널에서 화질 저하를 시켰을 때 본래의 이미지와 같은 분포에 있도록 학습을 진행한다. 결과적으로 본 논문에서는 두 장의 이미지를 사용하였을 때 더욱 정확하게 커널을 찾을 수 있음을 보여준다. 두 장의 이미지를 활용하는 방식이 한 장의 이미지만을 활용하는 기존의 최고 수준의 방법에 비해 합성된 다양한 커널 데이터셋[14]에서 약 0.17dB 성능 향상이 있었다.

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Distance and Entropy Based Image Viewpoint Selection for Accurate 3D Reconstruction with NeRF (NeRF의 정확한 3차원 복원을 위한 거리-엔트로피 기반 영상 시점 선택 기술)

  • Jinwon Choi;Chanho Seo;Junhyeok Choi;Sunglok Choi
    • The Journal of Korea Robotics Society
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    • v.19 no.1
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    • pp.98-105
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    • 2024
  • This paper proposes a new approach with a distance-based regularization to the entropy applied to the NBV (Next-Best-View) selection with NeRF (Neural Radiance Fields). 3D reconstruction requires images from various viewpoints, and selecting where to capture these images is a highly complex problem. In a recent work, image acquisition was derived using NeRF's ray-based uncertainty. While this work was effective for evaluating candidate viewpoints at fixed distances from a camera to an object, it is limited when dealing with a range of candidate viewpoints at various distances, because it tends to favor selecting viewpoints at closer distances. Acquiring images from nearby viewpoints is beneficial for capturing surface details. However, with the limited number of images, its image selection is less overlapped and less frequently observed, so its reconstructed result is sensitive to noise and contains undesired artifacts. We propose a method that incorporates distance-based regularization into entropy, allowing us to acquire images at distances conducive to capturing both surface details without undesired noise and artifacts. Our experiments with synthetic images demonstrated that NeRF models with the proposed distance and entropy-based criteria achieved around 50 percent fewer reconstruction errors than the recent work.

A Habitat Analysis of the Historical Breeding Sites of Oriental White Storks(Ciconia boyciana) in Gyeonggi and Chungcheong Provinces, Korea (GIS를 이용한 황새(Ciconia boyciana) 번식지의 환경특성 분석 - 1970년대의 경기도와 충청도 지역을 대상으로 -)

  • Kim, Su-Kyung;Kim, Nam-Shin;Cheong, Seokwan;Kim, Young-Hoon;Sung, Ha-Cheol;Park, Shi-Ryong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.11 no.1
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    • pp.125-137
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    • 2008
  • This research aims to produce basic data for developing habitat suitability models on the breeding sites of Oriental White Storks(Ciconia boyciana) which will be reintroduced to the wild in the future. The habitat characteristics of ten historical nesting sites of the Oriental White Storks at Gyeonggi and Chungcheong provinces in South Korea were analyzed with 1970's land use maps and Landsat MSS. The range of altitude on nesting sites was 40~116.38m. The mean distance from nesting sites to rice fields, to 30m wider river, and to reservoirs was $54.8{\pm}84.48m$, $869.8{\pm}708.01m$, and $1721.2{\pm}906.05m$ respectively. Historical nesting sites were located close to human settlements, and the mean distance of nesting sites to human settlements was $144.1{\pm}182.97m$. The land types within 5km radius from ten historical nesting sites consisted of 53.7% forest, 28.3% rice fields, 16.7% grasslands, 0.8% water bodies, and 0.6% human settlements. The composition of four land types(forest, rice fields, grasslands, and human settlements) was significantly differed between 93 random points and 10 historical nesting sites.

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Efficient Transmission of Scalable Video Streams Using Dual-Channel Structure (듀얼 채널 구조를 이용한 Scalable 비디오(SVC)의 전송 성능 향상)

  • Yoo, Homin;Lee, Jaemyoun;Park, Juyoung;Han, Sanghwa;Kang, Kyungtae
    • KIPS Transactions on Computer and Communication Systems
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    • v.2 no.9
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    • pp.381-392
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    • 2013
  • During the last decade, the multitude of advances attained in terminal computers, along with the introduction of mobile hand-held devices, and the deployment of high speed networks have led to a recent surge of interest in Quality of Service (QoS) for video applications. The main difficulty is that mobile devices experience disparate channel conditions, which results in different rates and patterns of packet loss. One way of making more efficient use of network resources in video services over wireless channels with heterogeneous characteristics to heterogeneous types of mobile device is to use a scalable video coding (SVC). An SVC divides a video stream into a base layer and a single or multiple enhancement layers. We have to ensure that the base layer of the video stream is successfully received and decoded by the subscribers, because it provides the basis for the subsequent decoding of the enhancement layer(s). At the same time, a system should be designed so that the enhancement layer(s) can be successfully decoded by as many users as possible, so that the average QoS is as high as possible. To accommodate these characteristics, we propose an efficient transmission scheme which incorporates SVC-aware dual-channel repetition to improve the perceived quality of services. We repeat the base-layer data over two channels, with different characteristics, to exploit transmission diversity. On the other hand, those channels are utilized to increase the data rate of enhancement layer data. This arrangement reduces service disruption under poor channel conditions by protecting the data that is more important to video decoding. Simulations show that our scheme safeguards the important packets and improves perceived video quality at a mobile device.

Landscape Fragmenation of Forest of the Cropland Increase Using Landsat Images of Manpo and Gangae, Jagang Cities, Northwest Korea (위성영상 분석에 의한 만포-강계 지역 경지확대에 따른 산림경관 변화)

  • Lee, Min-Boo;Kim, Nam-Shin;Choe, Han-Sung;Shin, Keun-Ha;Kang, Chul-Sung;Han, Uk
    • Journal of the Korean association of regional geographers
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    • v.9 no.4
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    • pp.481-492
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    • 2003
  • This study aims to analyze quantitatively changes of forest and cropland landscape due to cropland increase toward higher mountain slope during 9 years from 1993 to 2002, using Landsat images and field survey in the vicinity of Manpo and Gangae cities, Jagang Province, Northwest Korea, During 9 years, cropland has increased as 49.9%, forest area decreased as 16%. The spatial characteristics of cropland changes present that average elevation of cropland are increased from 381m of 1993 year to 412m of 2002 year, and average gradient increased from $10^{\circ}$ to $13^{\circ}$. In increased area of cropland during 9 years, the average elevation is 455m, and average gradient is $15^{\circ}$ with maximum gradient $70^{\circ}$. Analysis of the patch phenomena by fragmentation of vegetation landscape show that number of patch increased from 394 to 1,241 and also values of shape index, and fractal dimension of vegetation are increased slightly, during 9 years. Croplands have developed mainly in mountain slopes of elevation between 450 to 750m. For improvement of agricultural productivity, it should be required political and social stabilization, international and South Korea's assistance, and restoration of mountain forest.

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Fixed-Point Modeling and Performance Analysis of a SIFT Keypoints Localization Algorithm for SoC Hardware Design (SoC 하드웨어 설계를 위한 SIFT 특징점 위치 결정 알고리즘의 고정 소수점 모델링 및 성능 분석)

  • Park, Chan-Ill;Lee, Su-Hyun;Jeong, Yong-Jin
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.45 no.6
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    • pp.49-59
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    • 2008
  • SIFT(Scale Invariant Feature Transform) is an algorithm to extract vectors at pixels around keypoints, in which the pixel colors are very different from neighbors, such as vortices and edges of an object. The SIFT algorithm is being actively researched for various image processing applications including 3-D image constructions, and its most computation-intensive stage is a keypoint localization. In this paper, we develope a fixed-point model of the keypoint localization and propose its efficient hardware architecture for embedded applications. The bit-length of key variables are determined based on two performance measures: localization accuracy and error rate. Comparing with the original algorithm (implemented in Matlab), the accuracy and error rate of the proposed fixed point model are 93.57% and 2.72% respectively. In addition, we found that most of missing keypoints appeared at the edges of an object which are not very important in the case of keypoints matching. We estimate that the hardware implementation will give processing speed of $10{\sim}15\;frame/sec$, while its fixed point implementation on Pentium Core2Duo (2.13 GHz) and ARM9 (400 MHz) takes 10 seconds and one hour each to process a frame.