• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.2
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• pp.96-101
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• 2003

Recently, Fractal Image Coding has been studied as a way of efficient data compressing scheme. In the beginning, Fractal Image Coding has been studied for the data compressing in black ＆ white images and linear images. A. E. Jacquin suggested LIFS which expends to Fractal Image Coding for a gray scale image. Currently, YTKT's LIFS scheme which is using Gram-Schmidt is so efficient that enough to compete with the JPEG which is the national standards. This paper investigates the way of greatly reduced calculation for the orthogonalization algorithm.

• The Journal of the Acoustical Society of Korea
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• v.20 no.6
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• pp.17-25
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• 2001

Traditional adaptive noise cancelling methods rely their performance on various interfering parameters, such as convergence speed, tracking ability, numerical stability, relative frequency characteristics between target and reverberation signals, and activity of the target. In this paper, an adaptive noise cancelling method is suggested, which Provides a successful tradeoff mon these factors. It is designed to work on the transform domain, adopts the Gram-Schmidt orthogonalization process, and is implemented by the escalator algorithm. The transform domain approach supports a tradeoff between the convergence speed and numerical cost. The proposed method is verified by applying a real-data collected in the shallow waters off the east coasts of korea. It is shown that it has a good reverberation-rejection capability even for the target signal with adjacent frequency components to those of the reverberation, and its performance is invariant for the activity of the target.

• Journal of Korea Water Resources Association
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• v.49 no.4
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• pp.283-291
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• 2016

As the infrastructures and populations are the condensed in the mega city, urban flood management becomes very important due to the severe loss of lives and properties. For the more accurate calculation of runoff from the urban catchment, hourly or even minute rainfall data have been utilized. However, the time steps of the measured or forecasted data under climate change scenarios are longer than hourly, which causes the difficulty on the application. In this study, daily rainfall data was disaggregated into hourly using the stochastic method. Based on the historical hourly precipitation data, Gram Schmidt orthonormalization process and K-Nearest Neighbor Resampling (KNNR) method were applied to disaggregate daily precipitation into hourly. This method was originally developed to disaggregate yearly runoff data into monthly. Precipitation data has smaller probability density than runoff data, therefore, rainfall patterns considering the previous and next days were proposed as 7 different types. Disaggregated rainfall was resampled from the only same rainfall patterns to improve applicability. The proposed method was applied rainfall data observed at Seoul weather station where has 52 years hourly rainfall data and the disaggregated hourly data were compared to the measured data. The proposed method might be applied to disaggregate the climate change scenarios.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.8
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• pp.1677-1690
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• 1997

Block-transform coding is one of the most popular approaches for image compression. For example, DCT is widely used in the internaltional standards standards such as MPEG-1, MPEG-2, JPEG, and H.261. In the block-based transform coding, blocking artifacts may appear along block boundaries, and they can cause severe image degradation eqpecially when the transform coefficients are coarsely quantized. In this paper, we propose a new method for blocking artifacts reduction in transform-coded images. For blocking artifacts reduction, we add a correction term, on a block basis, composed of a linear combination of 28 basis images that are orthonormal on block boundaries. We select 28 DCT kernel functions of which boundary values are linearly independent, and Gram-Schmidt process is applied to the boundary values in order to obtain 28 boundary-orthonormal basis images. A threshold of bolock discontinuity is introduced for improvement of visual quality by reducing image blurring. We also investigate the number of basis images needed for efficient blocking artifacts reduction when the compression ratio changes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2000.11b
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• pp.161-166
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• 2000

본 논문에서는 영상 데이터의 저작권 보호를 위한 다중 워터마킹 기법을 제안한다. 다중 워터마킹은 하나의 컨텐츠에 복수개의 서로 다른 워터마크를 삽입하는 기법으로 각 워터마크들은 유일한 키로 정확한 추출이 가능해야 한다. 대역확산기법(spread spectrum)을 이용한 다중 워터마킹은 워터마크 삽입시 사용되는 키들간의 직교성(orthogonality)이 보장되어야 추출시 삽입된 워터마크들의 정확한 추출이 가능하게 된다. 따라서, 본 논문에서는 랜덤계열들을 Gram-schmidt 직교화 과정을 수행하여 직교화된 랜덤계열로 워터마크를 삽입하고 추출이 가능한 방법을 제안한다. 또한, 제안기법의 성능을 평가하기 위하여 가우시안 노이즈와 감마변환에 대하여 강인함을 보인다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.90-94
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• 2008

It is well-blown that the convergence rate gets worse when an input signal to an adaptive filter is correlated. In this paper we propose a new adaptive filtering algorithm that makes the convergence rate much improved even for highly correlated input signals. By introducing an orthogonal constraint between successive input signal vectors we overcome the slow convergence problem of the LMS algorithm with the correlated input signal. Simulation results show that the proposed algerian yields fast convergence speed and excellent tracking capability under both time-invariant and time-varying environments, while keeping both computation and implementation simple.