• 대한공간정보학회지
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• 제1권1호
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• pp.181-192
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• 1993

영상은 어떤 현상이나 대상물의 종류와 현상조건에 대한 정보를 포함하고 있는 화소값으로 구성되며, 화소값은 전처리 과정인 기하보정으로 변화된다. 이러한 화소값의 변화는 토지피복 분류 결과에 영향을 미친다. 본 논문에서는 기하보정으로 재구성된 영상을 이용하여 토지피복 분류를 함으로서 재배열의 영향을 알고자 한다. 연구대상 지역은 북한강 수계 중에서 가장 다양한 피복형태를 가지고 있는 춘천시를 중심으로 하는 춘천유역을 선정하였고, 전처리과정에서 재배열된 RESTEC 데이타가 이용되었다. 토지피복 분류는 최대우도법을 사용하여 LEVEL I 수준인 여섯개의 분류항목으로 분류되었다. 본 연구에서 두 가지 방법으로 재배열된 영상을 이용하여 토지피복 분류를 실시하였다. 각각의 분류항목을 지형도와 비교한 결과 Bilinear Interpolation법이 나지(BARE-LAND)를 제외한 다섯개의 분류항목에서 정확도가 좋았다. 결론적으로 기하보정의 영상 재배열은 어떤 분류항목에 중점을 두고 분류를 행하느냐에 따라서 재배열 방법을 선택해야 하며 논과 밭의 경우와 같은 분류항목간의 혼돈은 사계절 영상을 이용하면 더욱 더 정확하게 분류할 수 있을 것이다.

• 대한원격탐사학회지
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• 제26권4호
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• pp.439-449
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• 2010

이 논문에서는 KOMPSAT-2 스테레오 영상의 PAN밴드에 존재하는 미세한 크기의 Y시차가 발생하는 원인을 규명하고 이를 개선하기 위한 일련의 실험 및 분석과정을 보고한다. 분석결과, Y시차가 발생하는 원인이 KOMPSAT-2 영상을 생성할 때 PAN밴드를 MS밴드와 일치하도록 Warping처리하는 과정에서 발생한 Resampling 오차 때문인 것으로 판단할 수 있었다. 또한 엄밀한 PAN밴드의 Warping 방식을 적용하여 Resampling 오차를 제거함으로써 Y 시차문제가 상당부분 개선될 수 있음을 확인하였다. 또한 KOMPSAT-2 영상 PAN밴드에서 관측된 밝기값 밀림현상도 엄밀한 Warping처리를 통해서 개선될 수 있음을 확인하였다. 따라서, 보다 엄밀한 Warping기법이 KOMPSAT-2 영상처리과정에 적용될 수 있다면 KOMPSAT-2 영상의 기하정확도 및 복사정확도가 많이 개선될 수 있을 것으로 기대한다.

• 한국수산과학회지
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• 제45권5호
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• pp.499-506
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• 2012

We estimated the population size and fishing mortality of Pacific cod Gadus macrocephalus during the spawning season in waters off Woipo, Geoje Island, Korea, using a mark-recapture method. We marked and released 51 cod>50 cm in total length; six were recaptured by local fishermen during the period from December 15 to 31, 2009. The estimated population size was ca. 180,000 and the fishing mortality of the exploitable cod was 26%. Although we could assume a closed population due to the short survey period, we evaluated the uncertainty in the estimates by applying bootstrap resampling because the sample size was small. The estimated 95% confidence interval was 94,000-568,000 for the population size and 8-49% for fishing mortality. Our study demonstrated that the application of mark-recapture methods and bootstrap resampling can be useful in stock assessment for fisheries management in Korea, but requires a larger sample size, spatially extensive coverage, and sophisticated mark-recapture models based on a refined sampling design for reliable stock assessment and biological reference points in sustainable cod management.

• 제어로봇시스템학회논문지
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• 제19권10호
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• pp.907-914
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• 2013

A FastSLAM is an algorithm for SLAM (Simultaneous Localization and Mapping) using a Rao-Blackwellized particle filter and its performance is known to degenerate over time due to the loss of particle diversity, mainly caused by the particle depletion problem in the resampling phase. In this paper, the GeSPIR (Geographically Stratified Particle Information-based Resampling) technique is proposed to solve the particle depletion problem. The proposed algorithm consists of the following four steps : the first step involves the grouping of particles divided into K regions, the second obtaining the normal weight of each region, the third specifying the protected areas, and the fourth resampling using regional equalization weight. Simulations show that the proposed algorithm obtains lower RMS errors in both robot and feature positions than the conventional FastSLAM algorithm.

• 치과방사선
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• 제28권2호
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• pp.387-413
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• 1998

Image resampling is of particular interest in digital radiology. When resampling an image to a new set of coordinate, there appears blocking artifacts and image changes. To enhance image quality, interpolation algorithms have been used. Resampling is used to increase the number of points in an image to improve its appearance for display. The process of interpolation is fitting a continuous function to the discrete points in the digital image. The purpose of this study was to determine the effects of the seven interpolation functions when image resampling in digital periapical images. The images were obtained by Digora, CDR and scanning of Ektaspeed plus periapical radiograms on the dry skull and human subject. The subjects were exposed to intraoral X-ray machine at 60kVp and 70 kVp with exposure time varying between 0.01 and 0.50 second. To determine which interpolation method would provide the better image, seven functions were compared; (1) nearest neighbor (2) linear (3) non-linear (4) facet model (5) cubic convolution (6) cubic spline (7) gray segment expansion. And resampled images were compared in terms of SNR(Signal to Noise Ratio) and MTF(Modulation Transfer Function) coefficient value. The obtained results were as follows ; 1. The highest SNR value(75.96dB) was obtained with cubic convolution method and the lowest SNR value(72.44dB) was obtained with facet model method among seven interpolation methods. 2. There were significant differences of SNR values among CDR, Digora and film scan(P<0.05). 3. There were significant differences of SNR values between 60kVp and 70kVp in seven interpolation methods. There were significant differences of SNR values between facet model method and those of the other methods at 60kVp(P<0.05), but there were not significant differences of SNR values among seven interpolation methods at 70kVp(P>0.05). 4. There were significant differences of MTF coefficient values between linear interpolation method and the other six interpolation methods (P< 0.05). 5. The speed of computation time was the fastest with nearest -neighbor method and the slowest with non-linear method. 6. The better image was obtained with cubic convolution, cubic spline and gray segment method in ROC analysis. 7. The better sharpness of edge was obtained with gray segment expansion method among seven interpolation methods.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1994년도 춘계공동학술대회논문집; 창원대학교; 08월 09일 Apr. 1994
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• pp.436-436
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• 1994

• Journal of applied mathematics & informatics
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• 제25권1_2호
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• pp.183-199
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• 2007

In this paper we research the problem in which the objective is to minimize the sum of squared deviations of job expected completion times from the due date, and the job processing times are stochastic. In the problem the machine is subject to stochastic breakdowns and all jobs are preempt-repeat. In order to show that the replacing ESSD by SSDE is reasonable, we discuss difference between ESSD function and SSDE function. We first give an express of the expected completion times for both cases without resampling and with resampling. Then we show that the optimal sequence of the problem V-shaped with respect to expected occupying time. A dynamic programming algorithm based on the V-shape property of the optimal sequence is suggested. The time complexity of the algorithm is pseudopolynomial.

• Journal of the Korean Data and Information Science Society
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• 제16권3호
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• pp.665-682
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• 2005

The sample reuse bootstrap technique has been successful to attract both applied and theoretical statisticians since its origination. In recent years a good deal of attention has been focused on the applications of bootstrap methods in regression analysis. It is easier but more accurate computation methods heavily depend on high-speed computers and warrant tough mathematical justification for their validity. It is now evident that the presence of multiple unusual observations could make a great deal of damage to the inferential procedure. We suspect that bootstrap methods may not be free from this problem. We at first present few examples in favour of our suspicion and propose a new method diagnostic-before-bootstrap method for regression purpose. The usefulness of our newly proposed method is investigated through few well-known examples and a Monte Carlo simulation under a variety of error and leverage structures.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1990년도 추계학술대회
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• pp.38-41
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• 1990

A new spline function for resampling discrete signal adaptively is proposed. In general, B-spline function is used for an image interpolation because of its smoothness and continuity, but accompanies a large amount of blurring effect. Hence, we developed a new spline function to remedy this effect, with two procedures ; deblurring of Gaussian blurring and diminishing of aliasing effect caused by deblurring procedure. The proposed function has a parametric expression with $\alpha$ which is related to the variance of Gaussian blurring model. Locally adaptive resampling scheme is obtained by changing a according to statistical characteristics of an image. The proposed, interpolation function shows edge-sharpening effect as well as noise smoothing, with comparison to the conventional schemes.

• ETRI Journal
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• 제27권2호
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• pp.172-180
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• 2005

Image resampling according to epipolar geometry is an important prerequisite for a variety of photogrammetric tasks. Established procedures for resampling frame images according to epipolar geometry are not suitable for scenes captured by line cameras. In this paper, the mathematical model describing epipolar lines in scenes captured by line cameras moving with constant velocity and attitude is established and analyzed. The choice of this trajectory is motivated by the fact that many line cameras can be assumed to follow such a flight path during the short duration of a scene capture (especially when considering space-borne imaging platforms). Experimental results from synthetic along-track and across-track stereo-scenes are presented. For these scenes, the deviations of the resulting epipolar lines from straightness, as the camera's angular field of view decreases, are quantified and presented.