• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.113-117
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• 2003

In this paper, have necessity of PACS (Picture Archiving and Communication System) at hospital but hereafter by economical problem PACS apply this to medical treatment image enhancing image quality applying histogram equalization for improvement of light and darkness after reconstruct because make image that pretreatment filtering has wild picture and is processed in wave lets dissolution and wave lets area using weight median filter because could not buy expensive equipment at hospital which introduction is difficulty do inversion and extracted characteristic.

• Journal of IKEEE
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• v.21 no.1
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• pp.39-45
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• 2017

Image compression is now essential for applications such as transmission and storage in data bases. For video and digital image applications the use of long tap filters, while not providing any significant coding gain, may increase the hardware complexity. We use a wavelet transform in order to obtain a set of bi-orthogonal sub-classes of images; First, the design of short kernel symmetric analysis is presented in 1-dimensional case. Second, the original image is decomposed at different scales using a subband filter banks. Third, this paper is presented a technique for obtaining 2-dimensional bi-orthogonal filters using McClellan transform. It is shown that suggested wavelet bases is well used on wavelet transform for image compression. From performance comparison of bi-orthogonal filter, we actually use filters close to ortho-normal filters on application of wavelet bases to image analysis.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.269-278
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• 1998

This paper describes a development of efficient stress ECG signal analysis algorithm. The algorithm consists of wavelet adaptive filter(WAF), QRS detector and ST segment detector. The WAF consists of a wavelet transform and an adaptive filter. The wavelet transform decomposed the ECG signal into seven levels using wavelet function for each high frequency bank and low frequency bank. The adaptive filter used the signal of the seventh lowest frequency band among the wavelet transformed signals as primary input. For detection of QRS complex, we made summed signals that are composed of high frequency bands including frequency component of QRS complex and applied the adaptive threshold method changing the amplitude of threshold according to RR interval. For evaluation of the performance of the WAF, we used two baseline wandering elimination filters including a standard filter and a general adaptive filter. WAF showed a better performance than compared filters in the noise elimination characteristics and signal distortion. For evaluation of WAF showed a better performance than compared filters in the noise elimination characteristics and signal distortion. For evaluation of results of QRS complex detection, we compared our algorithm with existing algorithms using MIT/BIH database. Our algorithm using summed signals showed the accuracy of 99.67% and the higher performance of QRS detection than existing algorithms. Also, we used European ST-T database and patient data to evaluate measurement of the ST segment and could measure the ST segment adaptively according to change of heart rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1098-1110
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• 2003

In this paper, we propose a homomorphic wavelet-based MMSE filter with edge detection to restore images degraded by speckle noise. In the proposed method, a noisy image is first transformed into logarithmic domain. Each pixel in the transformed image is then classified into flat and edge regions by applying DIP operator to the image restored by homomorphic directional MMSE filter. Each pixel in flat region is restored by homomorphic wavelet-based MMSE filter. Each pixel in edge region is restored by the weighted sum of the output of homomorphic wavelet-based MMSE filtering and that of homomorphic directional MMSE filtering. The restored image in spatial domain is finally obtained by applying the exponential function to the restored image in logarithmic domain. Experimental results show that the restored images by the proposed method have ISNR improvement of 3.3-4.0 ㏈ and ${\beta}$, a measurement parameter on edge preservation, improvement of 0.0103-0.0126 and superior subjective image quality over those by conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.22 no.2
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• pp.153-161
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• 2003

In this paper, we propose a wavelet-based detection method to identify efficiently the time-delay or multipath channel of ocean acoustic signals due to complex ocean medium and boundary layers. Our proposed method employs wavelet packet transform to analyze the received broadband acoustic signals and applies the matched filter to determine the time region of interest. Also, we present numerical testing that results on both the simulated and real data revealed the efficiency of this method in time-delay estimation and moreover its capability in estimating the time-delay of individual path in multipath channel, in which the arrival patterns are too close to be separated by the matched filter method.

• 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.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.181-184
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• 1998

웨이브렛 변환은 신호나 영상을 분석하기 위한 다해상도 분해기법으로 사용되어 왔다. 웨이브렛 변환영역에서 신호는 스케일과 위치상의 크기로 표현된다. 이 변환영역에서는 신호나 영상의 주파수 성분들이 각각의 스케일에 따라서 분리되어 나타난다. 또한 각 변환영역은 신호나 영상의 공간적인 특성을 상당부분 포함하고 있다. 이러한 웨이브렛 변환의 특성은 푸리에 변화에 기초한 방법과는 달리, 에지와 잡음성분을 효과적으로 분리할 수 있는 정보를 우리에게 제공해 준다. 본 논문에서는 웨이브렛 변환영역의 각 스케일 특성과 공간적인 특성을 이용하여 영상의 잡음성분을 제거하였다. 잡음제거 기법의 성능평가를 위해 Wiener 필터링 방법과 비교하였다.

• The Journal of the Acoustical Society of Korea
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• v.17 no.1
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• pp.98-106
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• 1998

본 논문은 두 부류의 오디오 원에 대해 각각 다른 구조를 가지는 필터뱅크를 설계 하고 스위칭 기준을 제안한다. 균일한 필터뱅크로는 MDCT 필터뱅크를 사용하고 필터 뱅크 로는 웨이브렛 패킷 필터뱅크를 사용하였으며 오디오 신호의 시변 특성에 기초하여 두 필터 뱅크를 스위칭한다. MDCT 필터뱅크는 정상신호 표현에 적절하지만 급격한 변화를 포함하 는 오디오 신호를 표현하는데는 적절하지 못한다. 따라서, 본 연구에서 사용한 웨이브렛 패 킷 필터뱅크는 인간의 청각 특성을 고려한 임계대역(critical band)과 유사하게 설계하였으며 스위칭 기준엣는 에너지-엔트로피(energy-entropy), 영교차(zero-crossing)법 그리고 차분 (difference)기준을 사용하였다. 입력되는 오디오 신호의 통계적 특성에 기안하여 두 필터뱅 크를 스위칭하는 방식의 오디오 부호화기에 대해서 새로운 스위칭 기준을 제안하였다. 여러 가지 오디오 신호에 대한 주관적 평가(MOS)를 수행한 결과, 기존의 부호화기보다 좋은 성 능을 보였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.1095-1100
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• 2003

The wavelet transform pair used simultaneously when two wavelets are designed to form an approximate Hilbert transform pair provide excellent property than present DWT(discrete wavelet transform), especially in field that detect wide-band signals like pulse and increase the bit rate at the same bandwidth. In this paper, the two dyadic wavelet bases which form an approximate Hilbert transform pair were designed, and flat delay filter which has the truncated coefficient vector is used in order that the two filters can form Hilbert transform relation in the process of design.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.144-154
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• 1999

The binomial sequences are family of orthogonal sequences that can be generated with remarkable simplicity-no multiplications are necessary. This paper introduces a class of non-recursive multidimensional filters for frequency-selective image processing without multiplication operations. The magnitude responses are narrow-band. approximately gaussian-shaped with center frequencies which can be positioned to yield low-pass. band-pass. or high-pass filtering. Algorithms for the efficient implementation of these filters in software or in hardware are described. Also. we show that the binomial QMFs are the maximally flat magnitude square Perfect Reconstruction paraunitary filters with good compression capability and these are shown to be wavelet filters as well. In wavelet transform the original image is decomposed at different scales using a pyramidal algorithm architecture. The decomposition is along the vertical and horizontal direction and maintains constant the number of pixels required to describe the images. An efficient perfect reconstruction binomial QMF-Wavelet signal decomposition structure is proposed. The technique provides a set of filter solutions with very good amplitude responses and band split. The proposed binomial QMF-filter structure is efficient, simple to implement on VLSl. and suitable for multi-resolution signal decomposition and coding applications.