• 전자공학회논문지S
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• 제34S권3호
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• pp.55-62
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• 1997

For the effective removal of artifacts and the extraction of an improved evoked potential response, we propose the averaging method usin gthe shrinkag eof wavelet coefficients. The wavelet analysis decomposes the measured evoked potentials into scale coefficients with low frequency components and wavelet coefficients with high ones as a resolution level, respectively. and in the course of synthesis evoked potentials, the presented method shrinks the wavelet coefficients, and then reproduces the evoked potentials, and lastly averages it. We measured visual evoked potentials to simulate the averaging method using the shrinkage of wavelet coefficients, and compared it with aveaged signal. As a result of simulations, the proposed method gets improved VEP about 0.2-1.6dB in comparison with the averaging method with daubechies wavelet in the resolution level four.

• The Journal of the Acoustical Society of Korea
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• 제18권1E호
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• pp.13-19
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• 1999

This paper introduces an adaptive wavelet transform based on the lifting scheme, which is applied to signal denoising. The wavelet representation using orthogonal wavelet bases has received widespread attention. Recently the lifting scheme has been developed for the construction of biorthogonal wavelets in the spatial domain. Wavelet transforms are performed through three stages: the first stage or Lazy wavelet splits the data into two subsets, even and odd, the second stage calculates the wavelet coefficients (highpass) as the failure to interpolate or predict the odd set using the even, and the third stage updates the even set using neighboring odd points (wavelet coefficients) to compute the scaling function coefficients (lowpass). In this paper, we adaptively find some of the prediction coefficients for better representation of signals and this customizes wavelet transforms to provide an efficient framework for denoising. Special care has been given to the boundaries, where we design a set of different prediction coefficients to reduce the prediction error.

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.109-115
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• 2001

Wavelet coefficients are known to have decorrelating properties, since wavelet is orthonormal transformation. but empirically, those wavelet coefficients of images, like edges, are not statistically independent. Jansen and Bultheel(1999) developed the empirical Bayes approach to improve the classical threshold algorithm using local characterization in Markov random field. They consider the clustering of significant wavelet coefficients with uniform distribution. In this paper, we developed wavelet thresholding algorithm using Laplacian distribution which is more realistic model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권2호
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• pp.412-434
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• 2023

This study discusses the high-order diffusion method in the wavelet domain. It aims to improve the edge protection capability of the high-order diffusion method using wavelet coefficients that can reflect image information. During the first step of the proposed diffusion method, the wavelet packet decomposition is a more refined decomposition method that can extract the texture and structure information of the image at different resolution levels. The high-frequency wavelet coefficients are then used to construct the edge detection function. Subsequently, because accurate wavelet coefficients can more accurately reflect the edges and details of the image information, by introducing the idea of state weight, a scheme for recovering wavelet coefficients is proposed. Finally, the edge detection function is constructed by the module of the wavelet coefficients to guide high-order diffusion, the denoised image is obtained. The experimental results showed that the method presented in this study improves the denoising ability of the high-order diffusion model, and the edge protection index (SSIM) outperforms the main methods, including the block matching and 3D collaborative filtering (BM3D) and the deep learning-based image processing methods. For images with rich textural details, the present method improves the clarity of the obtained images and the completeness of the edges, demonstrating its advantages in denoising and edge protection.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.1875-1878
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• 2003

This paper Proposes a wavelet-based video compression method to improve compressed images using modification of wavelet coefficients. In conventional wavelet-based compression methods, bigger coefficients are transmitted early according to the significance of the coefficients. In this reason, when some coefficients which have more significance but are not bigger are not transmitted, image degradation occurs. The Proposed method considered two human visual characteristics. First, human eyes are more sensitive to the change of middle frequency which represents abrupt change of brightness than that of high frequency which expresses fine region. Second, human eyes are more dull to color component than luminance respectively. By adjusting the coefficients of wavelet transformed signals and allocating more bits for compression to the luminance signal, higher compression could be achieved.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2006년도 가을 학술발표논문집 Vol.33 No.2 (D)
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• pp.302-305
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• 2006

In this paper, we have proposed a novel method using quantization of wavelet coefficients for secret data communication. First, speech signal is partitioned into small time frames and the frames are transformed into frequency domain using a WT(Wavelet Transform). We quantize the wavelet coefficients and embedded secret data into the quantized wavelet coefficients. The destination regard quantization errors of received speech as seceret dat. As most speech watermark techniques have a trade off between noise robustness and speech quality, our method also have. However we solve the problem with a partial quantization and a noise level dependent threshold. In additional, we improve the speech quality with de-noising method using wavelet transform. Since the signal is processed in the wavelet domain, we can easily adapt the de-noising method based on wavelet transform. Simulation results in the various noisy environments show that the proposed method is reliable for secret communication.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1996년도 추계학술대회
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• pp.229-232
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• 1996

we propose the shrinkage of wavelet coefficients and the averaging method. The wavelet analysis decomposes the measured evoked potentials into scale coefficients and wavelet coefficients as a resolution level, respectively. And in the course of synthesis of evoked potentials, the presented method shrinks the wavelet coefficients, and then reproduces the evoked potentials and lastly averages it. we measured VEP signal to simulate the presented method, and compared it with averaged signal and LMS algorithm. As a result of simulations, the proposed method gets improved VEP about 0.2-1.6db in comparison with the result of averaging method.

• 한국산업정보학회논문지
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• 제16권3호
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• pp.23-33
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• 2011

본 논문에서는 웨이블릿 계수의 비트 레벨 정보를 사용한 영상 부호화 기법을 제안한다. 제안한 방법은 수정된 EZW 알고리즘과 부호화 과정 시 요구되는 메모리 사용량을 줄이기 위해 웨이블릿 계수들의 비트 레벨 정보를 가지는 중요 계수 배열을 사용한다. 중요 계수 배열은 웨이블릿 계수의 비트 레벨 정보를 저장하는 이차원 자료 구조로서, 제안된 알고리즘은 이것을 이용하여 중요한 계수에 대한 부호화 과정과 계수들의 비트 레벨 정보의 부호화 과정을 한 번에 수행할 수 있다. 실험 결과 기존의 부호화 방법보다 화질 면에서 비슷하거나 우수한 성능을 보인다. 특히 중요 계수 배열은 이용한 최소의 메모리 사용으로 다양한 비트율에서 영상의 일그러짐 없이 안정적으로 동작함을 확인하였다.

• 융합신호처리학회논문지
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• 제2권1호
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• pp.63-70
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• 2001

EZW(Embedded Image Coding Using Zerotrees of Wavelet Coefficients) 알고리즘의 경우는 해상도를 높이기 위해 임계값을 낮출 때 중요계수의 위치를 나타내기 위해 필요 없는 zero 값을 많이 코딩을 해야 하는 문제가 있다. 본 논문에서는 이러한 문제점을 해결하기 위하여 쿼드 트리(quad tree)방법을 이용하여 위치정보를 나나내었다. 그리고 그 계수들의 크기는 EZW 에서 사용한 방법과 유사한 메트릭스(matrix) 방법을 사용하였다. 본 논문에서 제안한 알고리즘으로 영상을 압축하게 되면 EZW와 MRWD(Morphological Representation of Wavelet Data)의 방법을 동시에 이용하는 효과가 있어 압축 효율이 증가함을 알 수 있었다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2003년도 추계종합학술대회
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• pp.260-263
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• 2003

본 논문은 그레이 영상에 웨이블릿 필터계수를 적용하여 의사컬러 이미지를 향상한 연구이다. 의사컬러 향상은 웨이블릿 변환을 사용해 분해능을 상승시켰고, 웨이블릿 필터계수를 사용하여 RGB 영상을 추출한 후 의사변환 하였다. 웨이블릿 필터계수를 사용한 의사컬러 변환은 일반적인 웨이블릿 변환에 비해 30dB이상 향상 되었다.