• Title/Summary/Keyword: 공간적 스무딩

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Spatial Smoothing for Temporal Error Concealment (시간적 에러 은폐를 위한 공간적 스무딩)

  • 김동욱;김진태
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.10a
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    • pp.594-597
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    • 2003
  • In this paper, we propose a new temporal error concealment method for recovery of video packet loss. Error concealment for each loss block is performed by temporal motion compensation and a smoothing operation of boundary pixels between the compensated block and its surrounding blocks. In the simulation results, performance improvement for the proposed technique is on the average 2 dB in comparison with the conventional technique.

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Spatial Smoothing for Temporal Error Concealment (시간적 에러 은폐를 위한 공간적 스무딩)

  • 김동욱;김진태
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.8
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    • pp.1708-1713
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    • 2003
  • In this paper, we propose a new temporal error concealment method for video packet loss. Error concealment for each loss block is performed by temporal motion compensation and a spatial smoothing operation of boundary pixels between the compensated block and its surrounding blocks. In the simulation results, performance improvement for the proposed technique is on the average 2㏈ in comparison with conventional techniques.

A Finite Memory Structure Smoothing Filter and Its Equivalent Relationship with Existing Filters (유한기억구조 스무딩 필터와 기존 필터와의 등가 관계)

  • Kim, Min Hui;Kim, Pyung Soo
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.2
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    • pp.53-58
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    • 2021
  • In this paper, an alternative finite memory structure(FMS) smoothing filter is developed for discrete-time state-space model with a control input. To obtain the FMS smoothing filter, unbiasedness will be required beforehand in addition to a performance criteria of minimum variance. The FMS smoothing filter is obtained by directly solving an optimization problem with the unbiasedness constraint using only finite measurements and inputs on the most recent window. The proposed FMS smoothing filter is shown to have intrinsic good properties such as deadbeat and time-invariance. In addition, the proposed FMS smoothing filter is shown to be equivalent to existing FMS filters according to the delay length between the measurement and the availability of its estimate. Finally, to verify intrinsic robustness of the proposed FMS smoothing filter, computer simulations are performed for a temporary model uncertainty. Simulation results show that the proposed FMS smoothing filter can be better than the standard FMS filter and Kalman filter.

Spatiotemporal Saliency-Based Video Abstract on a Smartphone (스마트폰에서의 시공간적 중요도기반 비디오 요약)

  • Lee, Won Beom;Park, In Kyu
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2012.07a
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    • pp.388-389
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    • 2012
  • 본 논문에서는 동영상을 시공간적 중요도 기반으로 요약하는 기법을 제안한다. 동영상 내에서 각 프레임의 중요도를 평가하여 높은 우선순위를 가지는 구간들의 집합으로 요약을 수행한다. 화면내의 얼굴면적의 비율, 영상의 복잡도를 통하여 각 프레임이 가지는 공간적 중요도를 분석하고 인접한 프레임간의 비교를 통해 밝기 히스토그램과 움직임(motion)의 양을 추정함으로써 시간적 중요도를 구한다. 에지 보존 스무딩 필터를 밝기 히스토그램에 적용하여 장면 전환을 검출한다. 분리된 장면들로 과분할 구조를 가지는 계층적 트리를 생성하여 사용자가 요구한 재생길이를 가지는 동영상을 자동으로 저작한다. 본 논문에서는 동영상 분석 및 저작을 제한적인 환경인 스마트폰에서 효과적으로 작동하도록 구현 및 최적화를 수행하였다.

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Range Estimating Performance Evaluation of the Underwater Broadband Source by Array Invariant (Array Invariant를 이용한 수중 광대역 음원의 거리 추정성능 분석)

  • Kim Se-Young;Chun Seung-Yong;Kim Boo-Il;Kim Ki-Man
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.6
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    • pp.305-311
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    • 2006
  • In this paper the performance of a array invariant method is evaluated for source-range estimation in horizontally stratified shallow water ocean waveguide. The method has advantage of little computationally effort over existing source-localization methods. such as matched field processing or the waveguide invariant and array gain is fully exploited. And. no knowledge of the environment is required except that the received field should not be dominated by purely interference This simple and instantaneous method is applied to simulated acoustic propagation filed for testing range estimation performance. The result of range estimation according to the SNR for the underwater impulsive source with broadband spectrum is demonstrated. The spatial smoothing method is applied to suppress the effect of mutipath propagation by high frequency signal. The result of performance test for range estimation shows that the error rate is within 20% at the SNR above 10dB.

New Adaptive Interpolation Based on Edge Direction extracted from the DCT Coefficient Distribution (DCT 계수 분포를 이용해 추출한 edge 방향성에 기반한 새로운 적응적 보간 기법)

  • Kim, Jaehun;Kim, Kibaek;Jeon, Gwanggil;Jeong, Jechang
    • Journal of Broadcast Engineering
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    • v.18 no.1
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    • pp.10-20
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    • 2013
  • Nowadays, video technology has been successfully improved creating tremendous results. As video technology improve, multimedia devices and demands from users are diversified. Therefore, a video codec used in these devices should support various displays with different resolutions. The technology to generate a higher resolution image from the associated low-resolution image is called interpolation. Interpolation is generally performed in either the spatial domain or the DCT domain. To use the advantages of both domains, we have proposed the new adaptive interpolation algorithm based on edge direction, which adaptively exploits the advantages of both domains. The experimental results demonstrate that our algorithm performs well in terms of PSNR and reduces the blocking artifacts.

Density Estimation Technique for Effective Representation of Light In-scattering (빛의 내부산란의 효과적인 표현을 위한 밀도 추정기법)

  • Min, Seung-Ki;Ihm, In-Sung
    • Journal of the Korea Computer Graphics Society
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    • v.16 no.1
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    • pp.9-20
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    • 2010
  • In order to visualize participating media in 3D space, they usually calculate the incoming radiance by subdividing the ray path into small subintervals, and accumulating their respective light energy due to direct illumination, scattering, absorption, and emission. Among these light phenomena, scattering behaves in very complicated manner in 3D space, often requiring a great deal of simulation efforts. To effectively simulate the light scattering effect, several approximation techniques have been proposed. Volume photon mapping takes a simple approach where the light scattering phenomenon is represented in volume photon map through a stochastic simulation, and the stored information is explored in the rendering stage. While effective, this method has a problem that the number of necessary photons increases very fast when a higher variance reduction is needed. In an attempt to resolve such problem, we propose a different approach for rendering particle-based volume data where kernel smoothing, one of several density estimation methods, is explored to represent and reconstruct the light in-scattering effect. The effectiveness of the presented technique is demonstrated with several examples of volume data.

Face Image Illumination Normalization based on Illumination-Separated Eigenface Subspace (조명분리 고유얼굴 부분공간 기반 얼굴 이미지 조명 정규화)

  • Seol, Tae-in;Chung, Sun-Tae;Ki, Sunho;Cho, Seongwon
    • Proceedings of the Korea Contents Association Conference
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    • 2009.05a
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    • pp.179-184
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    • 2009
  • Robust face recognition under various illumination environments is difficult to achieve. For face recognition robust to illumination changes, usually face images are normalized with respect to illumination as a preprocessing step before face recognition. The anisotropic smoothing-based illumination normalization method, known to be one of the best illumination normalization methods, cannot handle casting shadows. In this paper, we present an efficient illumination normalization method for face recognition. The proposed illumination normalization method separates the effect of illumination from eigenfaces and constructs an illumination-separated eigenface subspace. Then, an incoming face image is projected into the subspace and the obtained projected face image is rendered so that illumination effects including casting shadows are reduced as much as possible. Application to real face images shows the proposed illumination normalization method.

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Estimation of Aboveground Forest Biomass Carbon Stock by Satellite Remote Sensing - A Comparison between k-Nearest Neighbor and Regression Tree Analysis - (위성영상을 활용한 지상부 산림바이오매스 탄소량 추정 - k-Nearest Neighbor 및 Regression Tree Analysis 방법의 비교 분석 -)

  • Jung, Jaehoon;Nguyen, Hieu Cong;Heo, Joon;Kim, Kyoungmin;Im, Jungho
    • Korean Journal of Remote Sensing
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    • v.30 no.5
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    • pp.651-664
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    • 2014
  • Recently, the demands of accurate forest carbon stock estimation and mapping are increasing in Korea. This study investigates the feasibility of two methods, k-Nearest Neighbor (kNN) and Regression Tree Analysis (RTA), for carbon stock estimation of pilot areas, Gongju and Sejong cities. The 3rd and 5th ~ 6th NFI data were collected together with Landsat TM acquired in 1992, 2010 and Aster in 2009. Additionally, various vegetation indices and tasseled cap transformation were created for better estimation. Comparison between two methods was conducted by evaluating carbon statistics and visualizing carbon distributions on the map. The comparisons indicated clear strengths and weaknesses of two methods: kNN method has produced more consistent estimates regardless of types of satellite images, but its carbon maps were somewhat smooth to represent the dense carbon areas, particularly for Aster 2009 case. Meanwhile, RTA method has produced better performance on mean bias results and representation of dense carbon areas, but they were more subject to types of satellite images, representing high variability in spatial patterns of carbon maps. Finally, in order to identify the increases in carbon stock of study area, we created the difference maps by subtracting the 1992 carbon map from the 2009 and 2010 carbon maps. Consequently, it was found that the total carbon stock in Gongju and Sejong cities was drastically increased during that period.

Comparison of Forest Carbon Stocks Estimation Methods Using Forest Type Map and Landsat TM Satellite Imagery (임상도와 Landsat TM 위성영상을 이용한 산림탄소저장량 추정 방법 비교 연구)

  • Kim, Kyoung-Min;Lee, Jung-Bin;Jung, Jaehoon
    • Korean Journal of Remote Sensing
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    • v.31 no.5
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    • pp.449-459
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    • 2015
  • The conventional National Forest Inventory(NFI)-based forest carbon stock estimation method is suitable for national-scale estimation, but is not for regional-scale estimation due to the lack of NFI plots. In this study, for the purpose of regional-scale carbon stock estimation, we created grid-based forest carbon stock maps using spatial ancillary data and two types of up-scaling methods. Chungnam province was chosen to represent the study area and for which the $5^{th}$ NFI (2006~2009) data was collected. The first method (method 1) selects forest type map as ancillary data and uses regression model for forest carbon stock estimation, whereas the second method (method 2) uses satellite imagery and k-Nearest Neighbor(k-NN) algorithm. Additionally, in order to consider uncertainty effects, the final AGB carbon stock maps were generated by performing 200 iterative processes with Monte Carlo simulation. As a result, compared to the NFI-based estimation(21,136,911 tonC), the total carbon stock was over-estimated by method 1(22,948,151 tonC), but was under-estimated by method 2(19,750,315 tonC). In the paired T-test with 186 independent data, the average carbon stock estimation by the NFI-based method was statistically different from method2(p<0.01), but was not different from method1(p>0.01). In particular, by means of Monte Carlo simulation, it was found that the smoothing effect of k-NN algorithm and mis-registration error between NFI plots and satellite image can lead to large uncertainty in carbon stock estimation. Although method 1 was found suitable for carbon stock estimation of forest stands that feature heterogeneous trees in Korea, satellite-based method is still in demand to provide periodic estimates of un-investigated, large forest area. In these respects, future work will focus on spatial and temporal extent of study area and robust carbon stock estimation with various satellite images and estimation methods.