• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.5
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• pp.59-67
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• 1998

This paper propose a new vector-quantizer design method for coefficients of wavelet transformed images. In conventional wavelet transform, it is quite often to employ wavelet transformed coefficients, not containing images to be encoded, as training sequences for designing a vector-quantizer. This method has a serious drawback ; it is not known how to find a proper set of training images. This paper investigates characteristics of images that should be considered in the design of vector-quantizers for wavelet transformed images. Besides the statistical parameters such as correlation and standard deviation, edge components are shown to characterise wavelet transform images. Training sequences established in accordance with the above knowledge are used in the design of quantizers having guaranteed range of applicable images. Results of computer simulations are shown to demonstrate the effectiveness of the proposed method.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.587-596
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• 2022

Sea levels are rising as a result of climate change, and low-lying areas along the coast are at risk of flooding. Therefore, we tried to investigate the relationship between sea level change and climate indices using satellite altimeter data (Topex/Poseidon, Jason-1/2/3) and southern oscillation index (SOI) and the Pacific decadal oscillation (PDO) data. If time domain data were converted to frequency domain, the original data can be analyzed in terms of the periodic components. Fourier transform and Wavelet transform are representative periodic analysis methods. Fourier transform can provide only the periodic signals, whereas wavelet transform can obtain both the periodic signals and their corresponding time location. The cross-wavelet transformation and the wavelet coherence are ideal for analyzing the common periods, correlation and phase difference for two time domain datasets. Our cross-wavelet transform analysis shows that two climate indices (SOI, PDO) and sea level height was a significant in 1-year period. PDO and sea level height were anti-phase. Also, our wavelet coherence analysis reveals when sea level height and climate indices were correlated in short (less than one year) and long periods, which did not appear in the cross wavelet transform. The two wavelet analyses provide the frequency domains of two different time domain datasets but also characterize the periodic components and relative phase difference. Therefore, our research results demonstrates that the wavelet analyses are useful to analyze the periodic component of climatic data and monitor the various oceanic phenomena that are difficult to find in time series analysis.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.923-926
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• 2000

In this paper we address the problem of detecting and estimating an unknown narrow band signal in a noise interference environment A new practical band estimation method, yielding good performance even in case of finite-length data, is presented. More specifically, wavelet packet transform is utilized to detect the more accurate time-variant band, then we estimate the power from wavelet filter-coefficients of the respective band. Also, third-order cumulants, and projection cross-correlation (PCC) criterion are utilized to achieve an effective SNR improvement for the time-variant band estimation. In case of time variant band estimation, the PCC method yields better performance than the correlation method.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.733-736
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• 1998

In this paper, we propose a new method for content-based retrieval system using wavelet transform and correlation, which has were used in signal processing and image compressing. The matching method is used not perfect matching but similar matching. Used feature vector is the lowest frequency(LL) itself, energy value, and edge information of 4-layer, after computng a 4-layer 2-D fast wavelet transform on image. By the proosed algorithm, we got the result that was faste rand more accurate than the traditional algorithm. Because used feature vector was compressed 256:1 over original image, retrieval speed was highly improved. By using correlation, moving object with size variation was reterieved without additional feature information.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.98.5-98
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• 2001

An efficient adaptive nonlinear compensator, based on a wavelet transform domain adaptive Volterra filter along with a modified escalator algorithm, is proposed to speed up the convergence rate of an adaptive LMS algorithm. In particular, it is well known that the e.g., slow convergence speed of an adaptive LMS algorithm depends on the statistical characteristics (e.g., large eigenvalue spread) of the corresponding auto-correlation matrix of the input vector. To solve such a convergence problem, the proposed approach utilizes a modified escalator algorithm and a wavelet transform domain adaptive LMS Volterra filtering technique, which leads to diagonalization of the auto-correlation matrix of the ...

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9B
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• pp.1596-1603
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• 2000

In this paper an image coding scheme using the correlation of neighboring VQ indices in wavelet domain is proposed. The codewords in each sub-codebook are reordered in ascending order according to their energy in order to inmcrease the dependency of the indices. And the relative dresses of the reordered indices are transmitted to a receiver instead of to absolute addresses. LBG algorithm is used for obtaining a multiresolution codebool and PNN using k-d tress used for generating its initial values. Our experimental results show that the proposed coding scheme outperforms JPEG and an ordinary wavelet-VQ method at low-bit rates in terms of PSNR.

• Journal of Electrical Engineering and Technology
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• v.4 no.4
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• pp.552-558
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• 2009

We proposed a semi-blind digital image watermarking technique for copyright protection. The proposed algorithm embedded a binary sequence watermark into significant wavelet coefficients by using a quantization method. The main idea of the quantization method was to quantize a middle coefficient of the triplet of a significant wavelet coefficient according to the watermark's value. Unlike an existing algorithm, which used a random location table to find a coefficient in which the watermark bit will be embedded: the proposed algorithm used quad-tree decomposition to find a significant wavelet coefficient for embedding. For watermark detection, an original host image was not required. Thanks to the usage of significant wavelet coefficients, the proposed algorithm improved the correlation value, up to 0.43, in comparison with the existing algorithm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.766-771
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• 2008

In this paper, the vibration of high speed trains and the irregularity of railway are examined using a wavelet-based frequency response function. To investigate their characteristics, non-stationary acceleration data are acquired and processed using the wavelet transform. Also, the railway irregularity is examined by acquiring the data from the on-board laser-based measurement system. The correlation between the train vibration and the railway irregularity has been investigated. From the analysis, the wavelet-based frequency response function is a promised method for the dynamic characteristics of high speed trains.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.36-41
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• 2015

This paper is proposed a wavelet-based MCDT(Mask Coefficient Differential and Threshold) method of image registration of Multi-images contaminated with visible image and infrared image. The method for ensure reliability of the image registration is to the increase statistical corelation as getting the common feature points between two images. The method of threshold the wavelet coefficients using derivatives of the wavelet coefficients of the detail subbands was proposed to effectively registration images with distortion. And it can define that the edge map. Particularly, in order to increase statistical corelation the method of the normalized mutual information. as similarity measure common feature between two images was selected. The proposed method is totally verified by comparing with the several other multi-image and the proposed image registration.

• Smart Structures and Systems
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• v.1 no.2
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• pp.185-215
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• 2005

Advanced signal processing techniques have been long introduced and widely used in structural health monitoring (SHM) and nondestructive evaluation (NDE). In our research, we applied several signal processing approaches for our embedded ultrasonic structural radar (EUSR) system to obtain improved damage detection results. The EUSR algorithm was developed to detect defects within a large area of a thin-plate specimen using a piezoelectric wafer active sensor (PWAS) array. In the EUSR, the discrete wavelet transform (DWT) was first applied for signal de-noising. Secondly, after constructing the EUSR data, the short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were used for the time-frequency analysis. Then the results were compared thereafter. We eventually chose continuous wavelet transform to filter out from the original signal the component with the excitation signal's frequency. Third, cross correlation method and Hilbert transform were applied to A-scan signals to extract the time of flight (TOF) of the wave packets from the crack. Finally, the Hilbert transform was again applied to the EUSR data to extract the envelopes for final inspection result visualization. The EUSR system was implemented in LabVIEW. Several laboratory experiments have been conducted and have verified that, with the advanced signal processing approaches, the EUSR has enhanced damage detection ability.