• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.7-12
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• 2003

This paper propose the 1-pass spatially adaptive wavelet thresholding for image denosing. The method of wavelet thresholding for denosing, has been concentrated on finding the best uniform threshold or best basis. However, not much has been done to make this method adaptive to spatially changing statistics which is typical of a large class of images. This spatially adaptive thresholding is extended to the overcomplete wavelet expansion, which yields better results than the orthogonal transform. Experiments show that this proposed method does indeed remove noise significantly, especially for large noise power. Experimental results show that the proposed method outperforms level dependent thresholding techniques and is comparable to spatial Wiener filtering method, 2-pass spatially adaptive wavelet thresholding method in matlab.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2343-2346
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• 2003

The spatial resolution of multispectral images can be improved by merging them with higher resolution image data. A fundamental problem frequently occurred in existing fusion processes, is the distortion of spectral information. This paper presents a spatially adaptive image fusion algorithm which produces visually natural images and retains the quality of local spectral information as well. High frequency information of the high resolution image to be inserted to the resampled multispectral images is controlled by adaptive gains to incorporate the difference of local spectral characteristics between the high and the low resolution images into the fusion. Each gain is estimated to minimize the l$_2$-norm of the error between the original and the estimated pixel values defined in a spatially adaptive window of which the weight are proportional to the spectral correlation measurements of the corresponding regions. This method is applied to a set of co-registered Landsat7 ETM＋ panchromatic and multispectral image data.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.163-167
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• 2002

This paper propose the new spatially adaptive wavelet thresholding for image denosing. The method of wavelet thresholding for denosing, has been concentrated on finding the best uniform threshold or best basis. However, not much has been done to make this method adaptive to spatially changing statistics which is typical of a large class of images. Experimental results show that the proposed method outperforms level dependent thresholding techniques and is comparable to spatial Wiener filtering method in matlab.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.116-122
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• 1998

We propose a spatially adaptive image interpolation algorithm, which can restore high frequency details in the original high resolution image. In order to apply the regularization approach to the interpolation procedure, we first present a two-dimensional separable image degradation model for a low resolution imaging system. According to the model, we propose a regularized spatially adaptive interpolation algorithm by using five different constraints. We also analyze convergence of the proposed algorithm, and provide some experimental results to compare the proposed algorithm with its nonadaptive version.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.10
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• pp.2541-2551
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• 1996

Human visual systems are sensitive to noise on the flat intensity area. But it becomes less sensitive on the edge area. Recently, many types of spatially adaptive image restoration methods have been proposed, which employ the above mentioned huan visual characteristics. The present paper presents an adaptive image restoration method, which increases sharpness of the edge region, and smooths noise on the flat intensity area. For edge detection, the proposed method uses the visibility function based on the local variance on each pixel. And it adaptively changes the regularization parameter. More specifically, the image to be restored is divided into a number of steps from the flat area to the edge regio, and then restored by using the finite impulse response constrained least squares filter.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.24 no.4
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• pp.351-362
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• 2020

Adaptive behaviors are one of ubiquitous features in evolutionary dynamics of populations, and certain adaptive behaviors can be witnessed by individuals' movements which are generally affected by local environments. In this paper, by revisiting the previous work, we investigate the sensitivity of species coexistence in the system of cyclic competition where species movement can be affected by local environments. By measuring the extinction probability through Monte-Carlo simulations, we find the relativistic effect of weights of local fitness and exchange rate for adaptive movement on species biodiversity which promotes species coexistence as the relativistic effect is intensified. In addition, by means of basins of initial conditions, we also found that adaptive movement can also affect species biodiversity with respect to the choice of initial conditions. The strong adaptive movement can eventually lead the coexistence as a globally stable state in the spatially extended system regardless of mobility.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.5
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• pp.455-463
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• 2003

Adaptive noise cancellation techniques are ideally suitable for reducing spatially varying noise due to the grain structure of material in ultrasonic nondestructive evaluation. Grain noises have an un-correlation property, while flaw echoes are correlated. Thus, adaptive filtering algorithms use the correlation properties of signals to enhance the signal-to-noise ratio (SNR) of the output signal. In this paper, a multi-stage adaptive noise cancellation (MANC) method using adaptive least mean square error (LMSE) filter for enhancing flaw detection in ultrasonic signals is proposed.

• 한국전산유체공학회:학술대회논문집
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• 2011.05a
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• pp.294-301
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• 2011

A two-dimensional hybrid flaw solver has been developed for the accurate and efficient simulation of steady and unsteady flaw fields. The flow solver was cast to accommodate two different topologies of computational meshes. Triangular meshes are adopted in the near-body region such that complex geometric configurations can be easily modeled, while adaptive Cartesian meshes are, utilized in the off-body region to resolve the flaw more accurately with less numerical dissipation by adopting a spatially high-order accurate scheme and solution-adaptive mesh refinement technique. A chimera mesh technique has been employed to link the two flow regimes adopting each mesh topology. Validations were made for the unsteady inviscid vol1ex convection am the unsteady turbulent flaws over an NACA0012 airfoil, and the results were compared with experimental and other computational results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6C
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• pp.506-515
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• 2010

In this paper, we compare and analyze the spectral efficiency of representative adaptive MIMO algorithms in indoor environments. We first briefly investigate the modulation and demodulation schemes of MIMO algorithms to be compared and then implement adaptive algorithms by using BPSK and square QAM schemes up to 256QAM. We finally compare the spectral efficiency of adaptive MIMO algorithms employing (2$\times$2) or (4$\times$4) antenna array through the computer simulation in indoor environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.39-42
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• 1999

Adaptive array is using the array of antenna elements spatially and its output is the sum of each antenna elements output signal which is multiplied by the controlled weight coefficients corresponding to each elements. In this paper, for the BPSK and BFSK signals with S/I=2, S/N=10 is applied to the linear array antenna using the LMS & the Kalman filter algorithm. For the 4 elements equidistance linear array antenna system LMS and Kalman filter algorithm was used as the adaptive instruction principles and the application results to the constant amplitude envelope signals such as BPSK or BFSK can be seen that the computer simulation results are very fast in the convergence characteristics of directional patterns and the signal following characteristics.