• 제목/요약/키워드: Adaptive Reconstruction

검색결과 176건 처리시간 0.024초

Application of On-line System for Monitoring and Forecasting Surface Changes for Korean Peninsula

  • Lee, Sang-Hoon
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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    • pp.268-273
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    • 1998
  • This study applies an on-line system, which employes an adaptive reconstruction technique to monitor and forecast ocean surface changes. The system adaptively generates an appropriate synthetic time series with recovering missing measurements for sequential images. The reconstruction method incorporates temporal variation according to physical properties of targets and anisotropic spatial optical properties into image processing techniques. This adaptive approach allows successive refinement of the structure of objects that are barely detectable in the observed series. The system sequentially collects the estimated results from the adaptive reconstruction and then statistically analyzes them to monitor and forecast the change in surface characteristics.

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최적 적응 보간 커널 기반 2차원 M-채널 완전 복원 Filter Bank를 이용한 이미지 재구성 (Image Reconstruction Using 2D M-ch Perfect Reconstruction Filter Bank with Optimized Adaptive interpolation kernel)

  • 김진영;남상원
    • 전기학회논문지
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    • 제56권4호
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    • pp.795-798
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    • 2007
  • In this paper, we propose an image reconstruction method utilizing an optimized adaptive interpolation kernel along with a 2D M-channel perfect reconstruction filter bank (M-ch PR-FB) structure. In particular, the proposed approach leads to construction of a sharper image than a direct conversion, still preserving high frequency components of the original image through the subband processing of the 2D M-ch PR-FB. Finally, the image quality of the proposed approach is demonstrated by comparing with those of the direct methods using conventional interpolation kernels.

Adaptive Compressed Sensing과 Dictionary Learning을 이용한 프레임 기반 음성신호의 복원에 대한 연구 (A Study on the Reconstruction of a Frame Based Speech Signal through Dictionary Learning and Adaptive Compressed Sensing)

  • 정성문;임동민
    • 한국통신학회논문지
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    • 제37A권12호
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    • pp.1122-1132
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    • 2012
  • 압축센싱은 이미지, 음성신호, 레이더 등 많은 분야에 적용되고 있다. 압축센싱은 주로 통계적 특성이 시불변인 신호에 적용되고 있으며, 측정 데이터를 줄여 압축률을 높일수록 복원에러가 증가한다. 이와 같은 문제점들을 해결하기 위해 음성신호를 프레임 단위로 나누어 병렬로 처리하였으며, dictionary learning을 이용하여 프레임들을 sparse하게 만들고, sparse 계수 벡터와 그 복원값의 차를 이용하여 압축센싱 복원행렬을 적응적으로 만든 적응압축센싱을 적용하였다. 이를 통해 통계적 특성이 시변인 신호도 압축센싱을 이용하여 빠르고 정확한 복원이 가능함을 확인할 수 있었다.

적응적 영역분할법을 이용한 임의의 점군으로부터의 형상 재구성 (Shape Reconstruction from Unorganized Cloud of Points using Adaptive Domain Decomposition Method)

  • 유동진
    • 한국정밀공학회지
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    • 제23권8호
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    • pp.89-99
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    • 2006
  • In this paper a new shape reconstruction method that allows us to construct surface models from very large sets of points is presented. In this method the global domain of interest is divided into smaller domains where the problem can be solved locally. These local solutions of subdivided domains are blended together according to weighting coefficients to obtain a global solution using partition of unity function. The suggested approach gives us considerable flexibility in the choice of local shape functions which depend on the local shape complexity and desired accuracy. At each domain, a quadratic polynomial function is created that fits the points in the domain. If the approximation is not accurate enough, other higher order functions including cubic polynomial function and RBF(Radial Basis Function) are used. This adaptive selection of local shape functions offers robust and efficient solution to a great variety of shape reconstruction problems.

Adaptive Algorithm in Image Reconstruction Based on Information Geometry

  • Wang, Meng;Ning, Zhen Hu;Yu, Jing;Xiao, Chuang Bai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권2호
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    • pp.461-484
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    • 2021
  • Compressed sensing in image reconstruction has attracted attention and many studies are proposed. As we know, adding prior knowledge about the distribution of the support on the original signal to CS can improve the quality of reconstruction. However, it is still difficult for a recovery framework adjusts its strategy for exploiting the prior knowledge efficiently according to the current estimated signals in serial iterations. With the theory of information geometry, we propose an adaptive strategy based on the current estimated signal in each iteration of the recovery. We also improve the performance of existing algorithms through the adaptive strategy for exploiting the prior knowledge according to the current estimated signal. Simulations are presented to validate the results. In the end, we also show the application of the model in the image.

연속 원격탐사 영상자료의 재구축과 변화 탐지 (Reconstruction and Change Analysis for Temporal Series of Remotely-sensed Data)

  • 이상훈
    • 대한원격탐사학회지
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    • 제18권2호
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    • pp.117-125
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    • 2002
  • 연속적으로 상대적으로 짧은 간격으로 관측된 시계열 원격탐사 자료는 관측환경의 악화와 감지 시스템의 기계적 고장과 같은 관측 장애요인에 의해 많은 미관측 및 악성 자료를 가지게 된다. 본 연구는 adaptive 재구축 시스템을 이용하여 동적합성에 의해 미관측 및 악성 자료를 복구하는 문제를 다루고 있다. 제안된 재구축 방법은 관측 대상의 물리적 특성에서의 시간적 변화와 공간적 연속 특성에 근거한 영상처리 기법이며, adaptive 시스템은 관측 값과 지엽적 시간적 경향에 의해 추정된 예측 티의 가중치 합에 의해 합성영상을 생성하는 동적합성을 수행한다. 제안된 동적합성기술의 adaptive 재구축 시스템은 한반도를 관측한 1999년도와 2000년도 2년간의 NOAA AVHRR의 NDVI자료의 재구축에 적용되었다. 실험결과는 재구축된 시리즈는 미관측 및 악성 자료를 포함하고 있는 실제의 관측 영상 시리즈를 위하여 추정된 완전한 자료 값을 갖는 영상 시리즈로 사용될 수 있음을 보여주고 있다. 추가적으로 제안 시스템은 해당 시간에서의 시간적 변화량을 나타내는 gradient 영상을 생성하고, 이러한 영상들의 연속 시리즈에서 관측 대상의 시계열 변화 특성이 관측 자료 값의 영상 시리즈보다 더욱 분명히 나타나고 있다.

종방향 자율주행의 미지 고장 재건을 위한 순환 최소 자승 기반 적응형 슬라이딩 모드 관측기 개발 (Development of a RLS based Adaptive Sliding Mode Observer for Unknown Fault Reconstruction of Longitudinal Autonomous Driving)

  • 오세찬;송태준;이종민;오광석;이경수
    • 자동차안전학회지
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    • 제13권1호
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    • pp.14-25
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    • 2021
  • This paper presents a RLS based adaptive sliding mode observer (A-SMO) for unknown fault reconstruction in longitudinal autonomous driving. Securing the functional safety of autonomous vehicles from unexpected faults of sensors is essential for avoidance of fatal accidents. Because the magnitude and type of the faults cannot be known exactly, the RLS based A-SMO for unknown acceleration fault reconstruction has been designed with relationship function in this study. It is assumed that longitudinal acceleration of preceding vehicle can be obtained by using the V2V (Vehicle to Vehicle) communication. The kinematic model that represents relative relation between subject and preceding vehicles has been used for fault reconstruction. In order to reconstruct fault signal in acceleration, the magnitude of the injection term has been adjusted by adaptation rule designed based on MIT rule. The proposed A-SMO in this study was developed in Matlab/Simulink environment. Performance evaluation has been conducted using the commercial software (CarMaker) with car-following scenario and evaluation results show that maximum reconstruction error ratios exist within range of ±10%.

ADAPTIVE MOMENT-OF-FLUID METHOD : A NEW VOLUME-TRACKING METHOD FOR MULTIPHASE FLOW COMPUTATION

  • Ahn, Hyung-Taek
    • 한국전산유체공학회지
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    • 제14권1호
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    • pp.18-23
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    • 2009
  • A novel adaptive mesh refinement(AMR) strategy based on the Moment-of-Fluid(MOF) method for volume-tracking dynamic interface computation is presented. The Moment-of-Fluid method is a new interface reconstruction and volume advection method using volume fraction as well as material centroid. The adaptive mesh refinement is performed based on the error indicator, the deviation of the actual centroid obtained by interface reconstruction from the reference centroids given by moment advection process. Using the AMR-MOF method, the accuracy of volume-tracking computation with evolving interfaces is improved significantly compared to other published results.

Effective Reconstruction of Stereoscopic Image Pair by using Regularized Adaptive Window Matching Algorithm

  • Ko, Jung-Hwan;Lee, Sang-Tae;Kim, Eun-Soo
    • Journal of Information Display
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    • 제5권4호
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    • pp.31-37
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    • 2004
  • In this paper, an effective method for reconstruction of stereoscopic image pair through the regularized adaptive disparity estimation is proposed. Although the conventional adaptive disparity window matching can sharply improve the PSNR of a reconstructed stereo image, but there still exist some problems of overlapping between the matching windows and disallocation of the matching windows, because the size of the matching window tend to changes adaptively in accordance with the magnitude of the feature values. In the proposed method, the problems relating to the conventional adaptive disparity estimation scheme can be solved and the predicted stereo image can be more effectively reconstructed by regularizing the extimated disparity vector with the neighboring disparity vectors. From the experimental results, it is found that the proposed algorithm show improvements the PSNR of the reconstructed right image by about 2.36${\sim}$2.76 dB, on average, compared with that of conventional algorithms.

Phase Error Reduction for Multi-frequency Fringe Projection Profilometry Using Adaptive Compensation

  • Cho, Choon Sik;Han, Junghee
    • Current Optics and Photonics
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    • 제2권4호
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    • pp.332-339
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    • 2018
  • A new multi-frequency fringe projection method is proposed to reduce the nonlinear phase error in 3-D shape measurements using an adaptive compensation method. The phase error of the traditional fringe projection technique originates from various sources such as lens distortion, the nonlinear imaging system and a nonsinusoidal fringe pattern that can be very difficult to model. Inherent possibility of phase error appearing hinders one from accurate 3-D reconstruction. In this work, an adaptive compensation algorithm is introduced to reduce adaptively the phase error resulting from the fringe projection profilometry. Three different frequencies are used for generating the gratings of projector and conveyed to the four-step phase-shifting procedure to measure the objects of very discontinuous surfaces. The 3-D shape results show that this proposed technique succeeds in reconstructing the 3-D shape of any type of objects.