• Journal of the Korea Computer Industry Society
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• v.5 no.5
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• pp.737-746
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• 2004

Two-channel multiwavelet system is investigated for image compression application in this paper. Generally, multiwavelets are known for their superb capability of compressing non-stationary signals like voice. However, multivavelet system have a critical problem in processing and compressing image data due to mesh-grid visual artifacts. In our two-channel multiwavelet system we have investigated incorporation of pre and post filtering to the multiwavelet transform and compression system for alleviating those ingerent visual artifacts due to multiwavelet effect. In addition, to quantify the image data compression performance of proposed multiwavelet system, computer simulations have been performed using various image data. For bit allocation and quantization, the Lagrange multiplier technique considering data rate vs. distortion rate along with a nonlinear companding method are applied equallly to all systems considered, here. The simulation results have yielded 1 ~ 2 dB compression enhancement over the scalar savelet systems. If the more advanced compression methods like SPIHT and run-length channel coding were adopted for the proposed multiwavelet system, a much higher compression gain could be obtained.

• Journal of applied mathematics & informatics
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• v.28 no.3_4
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• pp.723-737
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• 2010

In this paper, we investigate the sampling theorem for frame in multiwavelet subspaces. By the frame satisfying some special conditions, we obtain its dual frame with explicit expression. Then, we give an equivalent condition for the sampling theorem to hold in multiwavelet subspaces. Finally, a sufficient condition under which the sampling theorem holds is established. Some typical examples illustrate our results.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.58-66
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• 2003

In this paper. an image compression of embedded zerotree structure using multiwavelet filter banks is proposed. Multiwavelet is used DGHM(Donovan, Geronimo, Hardin, and Massopust) scaling functions and wavelet functions of a new method with two channel fillet banks. The important properties of the DGHM multiwavelet are orthogonality and approximation order. The DCHM muitiwavelet using the this paper preserves the approximation order=2 for better energy compaction and perfect reconstruction. Image compression using the preposed DGHM multiwavelet is better PSNR for compression ratio than single Daubechies wavelet(D4), Biorthogoanl wavelet, and GHM(Geronimo, Hardin, and Massopust) multi wavelet.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.209-212
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• 2003

In this paper, we have analyzed a multiwavelet filter bank architecture which have several bases. The filter bank composed of multiwavelets bases is matrix-valued. Multiwavelets offer simultaneous orthogonality, symmetry, and short support, which is not possible for the scalar wavelet system, hence multiwavelet system can obtain excellent performance in signal analysis and compress. Also the multiwavelet differs from the scalar wavelet system in requiring two or more input streams to the multiwavelet filter bank. In this paper, we describe methods for obtaining such a input stream and how apply the actual data.

• Bulletin of the Korean Mathematical Society
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• v.48 no.6
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• pp.1157-1167
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• 2011

We consider totally interpolating biorthogonal multiwavelet systems with finite impulse response two-band multifilter banks, a study balancing order conditions of such systems. Based on FIR and interpolating properties, we show that approximation order condition is completely equivalent to balancing order condition. Consequently, a prefiltering can be avoided if a totally interpolating biorthogonal multiwavelet system satisfies suitable approximation order conditions. An example with approximation order 4 is provided to illustrate the result.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.4
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• pp.255-265
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• 2007

In case of wavelet coefficients have correlation, in image signal denoising using wavelet shrinkage denoising method, the denoising effect for the image signal is reduced when the wavelet shrinkage denoising method is used. The coefficients of multiwavelet transform have correlation by pre-filters. To solve the degradation problem in multiwavelet transform, V Sterela suggested a new pre-filter for the Universal threshold or weighting factors to the threshold. In this paper, to improve the denoising effect in the multiwavelet transform, the coefficient normalizing method that the coefficient are divided by estimated noise deviation is adopted to the transformed multiwavelet coefficients in the course of wavelet shrinkage technique. And the thresholds of universal, SURE and GCV are estimated using normalized coefficients and tried to denoise by the wavelet shrinkage technique. We compared PSNRs of denoised images for each thresholds and confirmed the efficiency of the proposed method.

• Korean Journal of Mathematics
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• v.21 no.3
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• pp.247-263
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• 2013

By analyzing one-parameter families of totally interpolating multiwavelet systems of minimal total length with low approximation orders, whose explicit formulas were obtained with the aid of well-known relations of filters, we demonstrate the infinitude of such systems.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1511-1514
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• 2002

This paper presents content adaptive image watermark embedding using stochastic visual model based on multiwavelet transform. To embedding watermark, the original image is decomposed into 4 levels using a discrete multiwavelet transform, then a watermark is embedded into the JND(just noticeable differences) of the image each subband. The perceptual model is applied with a stochastic approach fer watermark embedding. This is based on the computation of a NVF(noise visibility function) that have local image properties. The perceptual model with content adaptive watermarking algorithm embed at the texture and edge region for more strongly embedded watermark by the JND. This method uses stationary Generalized Gaussian model characteristic because watermark has noise properties. The experiment results of simulation of the proposed watermark embedding method using stochastic visual model based on multiwavelet transform techniques was found to be excellent invisibility and robustness.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1149-1158
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• 2003

Content adaptive watermark embedding algorithm using a stochastic image model in the multiwavelet transform is proposed in this paper. A watermark is embedded into the perceptually significant coefficients (PSCs) of each subband using multiwavelet transform. The PSCs in high frequency subband are selected by SSQ, that is, by setting the thresholds as the one half of the largest coefficient in each subband. The perceptual model is applied with a stochastic approach based on noise visibility function (NVF) that has local image properties for watermark embedding. This model uses stationary Generalized Gaussian model characteristic because watermark has noise properties. The watermark estimation use shape parameter and variance of subband region. it is derive content adaptive criteria according to edge and texture, and flat region. The experiment results of the proposed watermark embedding method based on multiwavelet transform techniques were found to be excellent invisibility and robustness.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.783-789
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• 2005

This paper is proposed a watermarking technique for copyright protection of multimedia contents. We proposed adaptive watermark detection algorithm using stochastic perceptual model and statistical decision method in DMWT(discrete multi wavelet transform) domain. The stochastic perceptual model calculates NVF(noise visibility function) based on statistical characteristic in the DMWT. Watermark detection algorithm used the likelihood ratio depend on Bayes' decision theory by reliable detection measure and Neyman-Pearson criterion. To reduce visual artifact of image, in this paper, adaptively decide the embedding number of watermark based on DMWT, and then the watermark embedding strength differently at edge and texture region and flat region embedded when watermark embedding minimize distortion of image. In experiment results, the proposed statistical decision method based on multiwavelet domain could decide watermark detection.