• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.50-59
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• 1996

In this paper, a new hierarchical motion estiamtion scheme using the wavelet transformed multi-resolution image layers is proposed. Compared with the full search motion estimation method, the existing hierarchical methods remarkably reduce the amount of the computation but their efficiencies are depreciated by the local minima problem. In order to solve the local minima problem, the multi-resolution image layers are composed using the wavelet transform and the number of layers participated in the motion estimation for a block is determined by considering of its low band energy and higher band energy on the first wavelet transformed layer. The ratio between higher band energy and low band energy of each block is evaluated and in the case of the blocks which include relatively large higher band energy, the motion estimation is carried out in the high resolution layer. Otherwise, all layers are used. The final motion vectors are obtained in the first wavelet transformed layer. So less bits for motion vectors are transmitted, and the decomposition of received image using inverse wavelet transform decreases the blocking effect.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.351-358
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• 2002

Video compression based on DCT (Discrete Cosine Transform) has weakpoints of blocking artifacts and pixel loss when the resolution is changed. DWT (Discrete Wavelet Transform) based method can overcome such problems. In SAMCoW (Scalable Adaptive Motion Compensation Wavelet), one of wavelet based video coding algorithm, both intra frames and motion compensated error frames are encoded using EZW(Embedded Zerotree Wavelet) algorithm. However the property of wavelets transform coefficients of motion compensated error frames are different from that of still images. Signal energy is not highly concentrated in the lower bands which is true for most still image cases. Signal energy is rather evenly distributed over all frequency bands. This paper suggests a new video coding algorithm utilizing these properties. Spatial band coding which is known to be very effective for encoding images with relative1y high frequency components and not utilizing the interband coefficients correlation is applied instead of EZW to encode both intra and inter frames. In spatial band coding, the position and value of significant wavelet coefficients in each band are progressively transmitted. Unlike EZW, inter band coefficients correlations are not utilized in spatial band coding. It has been shown that spatial band coding gives better performance than EZW when applied to wavelet based video compression.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.3
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• pp.493-505
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• 1997

In this paper, a wavelet image compression method using human visually estimated quantizer is proposed. The quantizer has three components. These are constructed by using effects of frequency band, background luminance, and spatial masking. The first quantization factor is a fixed constant value for each band. The second factor is calculated by averaging four wavelet coefficients in the lowest frequency band. The third factor is determined by the difference between wavelet coefficients in the lowest frequency band. Arithmetic coding is used for encoding quantized wavelet coefficients. Coefficients in the lowest band are transmitted without loss. Therefore the compressed image is decompressed by using three quantization factors which can be calculated in the receiver. Compared with previous image compression methods which adopted human visual system, the proposed method shows improved results with less computational cost.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.776-782
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• 2003

This paper develops an approach to fuse 1-meter resolution spatial panchromatic and 4-meter resolution multi-spectral IKONOS images. The approach is based on the characteristics of four-band wavelet transformation. The experiment shows that the fused images based on four-band wavelet method contain with not only high spatial resolution but also rich spectral characteristic.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.745-748
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• 1998

Recently, image and voice processing part is using wavelet transform. We propose thining algorithm using wavelet tranform. Wavelet transform consists of low frequency and high frequency in the spatial and frequency domain. After the wavelet decomposition, more than 90 percents of energy are contained in lowest frequency band. Therefor, for images with large difference of gray value between foreground and background like character images, we can more accurately in the lowest frequency band. Lowest frequency band has wavelet transform significant coefficient(WTS) that is required for the thinning algorithm we proposed Paper [3][5][7][8] can not separate consonants and vowels of korean characters. Becuase korean characters have structural feature. This paper can separate consonants and vowels. Simulation executed low frequency image and data compression can reduce 1/4$^{n}$ with level n. we can redcue time complexity 3/8.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.415-419
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• 2001

This paper proposes and adaptive nonlinear equalizer based on Volterra Series along with M-band wavelet transform(M-DWT). The proposed wavelet transform-domain approach leads to diagonalization of the input vector auto-correlation matrix, which yields clustering its eigenvalue spread around one, and improving the convergence rate of the corresponding transform-domain LMS algorithm. In particular, the proposed adaptive Volterra equalizer is employed to compensate for the output distortion produced by a weakly nonlinear system. Finally, some simulation results obtained by using a TWT amplifier model are provide to demonstrated the converging performance of the proposed approach.

• Journal of applied mathematics & informatics
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• v.41 no.5
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• pp.1115-1128
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• 2023

In this paper, a novel hybrid method for multi-focus image fusion is proposed. The method combines the advantages of wavelet transform-based methods and focus-measure-based methods to achieve an improved fusion result. The input images are first decomposed into different frequency sub-bands using the discrete wavelet transform (DWT). The focus measure of each sub-band is then calculated using the Laplacian of Gaussian (LoG) operator, and the sub-band with the highest focus measure is selected as the focused sub-band. The focused sub-band is sharpened using an unsharp masking filter to preserve the details in the focused part of the image.Finally, the sharpened focused sub-bands from all input images are fused using the maximum intensity fusion method to preserve the important information from all focus images. The proposed method has been evaluated using standard multi focus image fusion datasets and has shown promising results compared to existing methods.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.1
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• pp.8-18
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• 2008

In this paper, we propose an efficient algorithm using wavelet transform for still image database retrieval. Especially, it uses only the lowest frequency sub-band in multi-level wavelet transform so that a retrieval system uses a smaller quantity of memory and takes a faster processing time. We extract different textured features, statistical information such as mean, variance and histogram, from low frequency sub-band. Then we measure the distances between the query image and the images in a database in terms of these features. To obtain good retrieval performance, we use the first feature (mean and variance of wavelet coefficients) to filter out most of the unlikely images. The rest of the images are considered to be candidate images. Then we apply the second feature (histogram of wavelet coefficient) to rank all the candidate images. To evaluate the algorithm, we create various distorted image databases using MIT VisTex texture images and PICS natural images. Through simulations, we demonstrate that our method can achieve performance satisfactorily in terms of the retrieval accuracy as well as the both memory requirement and computational complexity. Therefore it is expected to provide good retrieval solution for JPEG-2000 using wavelet transform.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.46-55
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• 1995

In this paper, we present a new wavelet transform-based CELP coder, called band selection wavelet transform CELP (BS-WTCELP) operated at 4.8 kbps. The proposed algorithm uses a band selection scheme of frequency bands of wavelet transform and selective vector quantization (VQ). The band selection and selective VQ structure is implemented by using a classified VQ structure. The proposed algorithm has about 0.5-1.0 dB improvement in segmental SNR compared with the conventional CELP that uses the random codebook search, while is has significantly reduced computational and storage complexity. Many experimental results have shown that the proposed algorithm is more suitable for most real-applications than the conventional CELP and wavelet transform CELP.