• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.455-464
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• 2009

Lee(2009) proposed the boundary-adaptive despeckling method using a Bayesian model which is based on the lognormal distribution for image intensity and a Markov random field(MRF) for image texture. This method employs the Point-Jacobian iteration to obtain a maximum a posteriori(MAP) estimate of despeckled imagery. The boundary-adaptive algorithm is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The boundary-adaptive scheme was comprehensively evaluated using simulation data and the effectiveness of boundary adaption was proved in Lee(2009). This study, as an extension of Lee(2009), has suggested a modified iteration algorithm of MAP estimation to enhance computational efficiency and to combine classification. The experiment of simulation data shows that the boundary-adaption results in yielding clear boundary as well as reducing error in classification. The boundary-adaptive scheme has also been applied to high resolution Terra-SAR data acquired from the west coast of Youngjong-do, and the results imply that it can improve analytical accuracy in SAR application.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.39-46
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• 2019

This paper proposes an adaptive threshold watershed algorithm, which is the method used for image segmentation and boundary detection, which extends the region on the basis of regional minimum point. First, apply adaptive thresholds to determine regional minimum points. Second, it extends the region by applying adaptive thresholds based on determined regional minimum points. Traditional watershed algorithms create over-segmentation, resulting in the disadvantages of breaking boundaries between regions. These segmentation results mainly from the boundary of the object, creating an inaccurate region. To solve these problems, this paper applies an improved watershed algorithm applied with adaptive threshold in regional minimum point search and region expansion in order to reduce over-segmentation and breaking the boundary of region. This resulted in over-segmentation suppression and the result of having the boundary of precisely divided regions. The experimental results show that the proposed algorithm can apply adaptive thresholds to reduce the number of segmented regions and see that the segmented boundary parts are correct.

• Structural Engineering and Mechanics
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• v.4 no.2
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• pp.191-202
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• 1996

This paper presents a construction of adaptive boundary element for the problem with mixed boundary conditions such as heat transfer between heated body surface and surrounding medium. The scheme is based on the sample point error analysis and on the extended error indicator, proposed earlier by the authors for the potential and elastostatic problems, and extended successfully to multidomain and thermoelastic analyses. Since the field variable is connected with its derivative on the boundary, their errors are also interconnected by the specified condition. The extended error indicator on each boundary element is modified to meet with the situation. Two numerical examples are shown to indicate the differences due to the prescribed boundary conditions.

• Structural Engineering and Mechanics
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• v.6 no.1
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• pp.115-124
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• 1998

A novel boundary stress resolution method is suggested in this paper, which is based upon the displacements of finite element analysis and of high precision with stress boundary condition strictly satisfied. The method is used to modify the Zienkiewicz-Zhu ($Z^2$) a posteriori error estimator and for the h-version adaptive finite element analysis of crack problems. Successful results are obtained.

• Bulletin of the Korean Mathematical Society
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• v.51 no.4
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• pp.1087-1100
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• 2014

We present an accurate and efficient numerical method for solving the Black-Scholes equation. The method uses an adaptive grid technique which is based on a far-field boundary position and the Peclet condition. We present the algorithm for the automatic adaptive grid generation: First, we determine a priori suitable far-field boundary location using the mathematical model parameters. Second, generate the uniform fine grid around the non-smooth point of the payoff and a non-uniform grid in the remaining regions. Numerical tests are presented to demonstrate the accuracy and efficiency of the proposed method. The results show that the computational time is reduced substantially with the accuracy being maintained.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.12-14
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• 2005

In this paper, we proposed an temporal error concealment (EC) using the proposed boundary matching method and the adaptive block matching method. The proposed boundary matching method improves the spatial correlation of the macroblocks (MBs) by reusing the pixels of the concealed MB to estimate a motion vector of a error MB. The adaptive block matching method inspects the horizontal edge and the vertical edge feature of a error MB surroundings, and it conceals the error MBs in reference to more stronger edge feature. This improves video quality by raising edge connection feature of the error MBs and the neighborhood MBs. In particular, we restore a lost MB as the unit of 8${\times}$16 block or 16${\times}$8 block by using edge feature from the surrounding macroblocks. Experimental results show that the proposed algorithm gives better results than the conventional algorithms from a subjective and an objective viewpoint.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.270-273
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• 2007

In this paper, a SAR-despeck1ing approach of adaptive iteration based a Bayesian model using the lognormal distribution for image intensity and a Gibbs random field (GRF) for image texture is proposed for noise removal of the images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. The iterative approach based on MRF is very effective for the inner areas of regions in the observed scene, but may result in yielding false reconstruction around the boundaries due to using wrong information of adjacent regions with different characteristics. The proposed method suggests an adaptive approach using variable parameters depending on the location of reconstructed area, that is, how near to the boundary. The proximity of boundary is estimated by the statistics based on edge value, standard deviation, entropy, and the 4th moment of intensity distribution.

• ETRI Journal
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• v.37 no.5
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• pp.1023-1031
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• 2015

In infrared (IR) images, near targets have a transient distribution at the boundary region, as opposed to a steady one at the inner region. Based on this fact, this paper proposes a novel IR target extraction method that uses both a weighted information entropy (WIE) and an adaptive opening filter to extract near finely shaped targets in IR images. Firstly, the boundary region of a target is detected using a local variance WIE of an original image. Next, a coarse target region is estimated via a labeling process used on the boundary region of the target. From the estimated coarse target region, a fine target shape is extracted by means of an opening filter having an adaptive structure element. The size of the structure element is decided in accordance with the width information of the target boundary and mean WIE values of windows of varying size. Our experimental results show that the proposed method obtains a better extraction performance than existing algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.8-14
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• 2000

In this paper, three adaptive sliding mode control algorithms, which self-tune both the sliding mode gain and the boundary layer thickness, are proposed. The first algorithm uses a gain adaptation rule is combined with the boundary layer thickness adaptatioin rule to satisfy the sliding condition. In the third algorithm, the computation burden of the second algorithm is reduced further, and therefore no extra cost is required for real-time implementation. Due to the mixed sliding mode gain and the boundary layer thickness adaptation scheme, the tracking error and the chattering of the control input can be reduced greatly.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.295-309
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• 2009

In this study, an iterative maximum a posteriori (MAP) approach using a Bayesian model of Markovrandom field (MRF) was proposed for despeckling images that contains speckle. Image process is assumed to combine the random fields associated with the observed intensity process and the image texture process respectively. The objective measure for determining the optimal restoration of this "double compound stochastic" image process is based on Bayes' theorem, and the MAP estimation employs the Point-Jacobian iteration to obtain the optimal solution. In the proposed algorithm, MRF is used to quantify the spatial interaction probabilistically, that is, to provide a type of prior information on the image texture and the neighbor window of any size is defined for contextual information on a local region. However, the window of a certain size would result in using wrong information for the estimation from adjacent regions with different characteristics at the pixels close to or on boundary. To overcome this problem, the new method is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The proximity to boundary is estimated using a non-uniformity measurement based on standard deviation of local region. The new scheme has been extensively evaluated using simulation data, and the experimental results show a considerable improvement in despeckling the images that contain speckle.