• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.87-94
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• 2005

In this paper a low-power DWT(Discrete Wavelet Transform) design technique is proposed. As basic low-pass filter for analysis bank, comb filter is utilized, and in order to improve frequency response for the comb filter, a fourth order polynomial is also proposed. Another filters are designed by using perfect reconstruction conditions. The lowpass filter coefficients of the analysis filter bank are optimized based on the cost function and perfect reconstruction condition. The number of the multiplications and MSE(Mean Squared Error) performance of the proposed DWT filter bank are compared with those of the JPEG2000 (9, 7) filter bank. It is shown that number of multiplications of the proposed filter bank are saved with 33.3%, and MSE values of the proposed filter bank are also superior to those of the JPEG2000 (9, 7) filter bank.

• Spatial Information Research
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• v.17 no.4
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• pp.455-462
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• 2009

A method to find the nearly optimal PSNR values for compression was tried to remotely sensed images. There is no rule to find the best wavelet pairs for image processing. The expected wavelet pairs following the suggested algorithm showed the optimal result for various kinds of images. Firstly, the PSNR variations with three wavelet families were analyzed. In many cases the longer wavelet filter shows the higher PSNR value, but the rate is getting less in orthogonal wavelet families. Wavelets with moderate filter length are suggested at the point of computational cost. For biorthogonal families it was hard to predict from the length of filters. Multiresolution wavelet analysis was used up to level 3 with three kinds of wavelet families. Biorthogonal wavelet family showed irregular pattern to get the maximum PSNR values, while orthogonal wavelet families showed regular pattern. In orthogonal wavelet families the nearly optimal wavelet pair can be predicted from the level 1.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.4
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• pp.270-277
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• 2010

The BAMS filter is a kind of wavelet shrinkage filter based on the Bayes estimators with no simulation, therefore it can be used for a real time filter. The denoising efficiency of BAMS filter is seriously affected by the estimated noise variance in each wavelet band. To remove noise in signals in existing BAMS filter, the noise variance is estimated by using the quartile of the finest level of details in the wavelet decomposition, and with this variance, the noise of the level is removed. In this paper, to remove the image noise includingodified quartile of the level of detail is proposed. And by these techniques, the image noises of mid and high frequency bands are removed, and the results showed that the increased PSNR of ab the midband noise, the noise variance estimation method using the monotonic transform and the mout 2[dB] and the effectiveness in denosing of low noise deviation images.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1762-1766
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• 2000

Estimation of reverberant time is one of important factor for the calculation of absorption ration of absorption material. In general the digital filter bank has been used for the, estimation of decay curve of the sound pressure in a reverberant room. However at low frequency, it is not easy to get a good linear decay curve for the estimation of reverberant time. Now, wavelet transform is applied to this difficult task, a good result has been obtained at low frequency. The decay curve using wavelet filter bank is better than that using digital filter bank at low frequency. At higher frequency, both curves are similar.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.893-897
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• 2008

To achieve the challenges of low-cost MEMS gyros for the precise self-localization of mobile robots, this paper examines an effective method of minimizing the drift on the heading angle that relies solely on integration of rate signals from a gyro. The main idea of the proposed approach is to use wavelet de-noising filter in order to reduce random noise which affects short-term performances. The proposed method was applied to Epson XV3500 gyro and the performances are verified by the comparisons with an existing commercial gyro module of vacuum cleaning robots.

• Journal of the Korean Geophysical Society
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• v.9 no.4
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• pp.311-320
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• 2006

Digital filters designed using wavelet theory are applied to bathymetry data acquired from KR5 area of Korea Deepsea Mining Area. The filters used in this study are the linear B-spline wavelet filter and derivative of a Cubic B-spline filter. With proper tuning of the digital filters, we can identify the location and orientation of the abyssal hill and abyssal trough in bathymetry. These features obtained from the digital filters are well correlated with bathymetric image. This quantitative information, which can be used to understand the underlying geophysical processes, can be further processed to obtain the spacing, orientation and distribution of the abyssal hill. This wavelet analysis of bathymetry provides good data to select the mining site.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.6
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• pp.96-103
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• 1999

This paper proposes efficient VLSI architecture for computation of the 1-D discrete wavelet transform (DWT). The proposed VLSI architecture computes the wavelet lowpass and highpass output sequences using the product term anhm, $n,m{\ge}0$, where an and hm denote the imput sequence and the wavelet lowpass filter coefficient, respectively. Whereas the conventional architectures compute the lowpass and highpass output sequences using the product terms anhm and angm, respectively, where gm denotes the wavelet highpass filter coefficient. The proposed architecture is applied to computation of the Daubechies 4-tap wavelet transform using the relationships between the Daubechies wavelet filter coefficients. Performance comparison of various architectures for computation of the 1-D DWT are presented. Note that the proposed architecture does not require extra processing units whereas the conventional architectures need them. Also it is modeled in very high speed integrated circuit hardware description language (VHDL) and simulated to show its functional validity.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.592-594
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• 2003

이 논문에서는 wavelet과 sobel filter를 사용하여 영상의 객관적인 평가 점수를 계산하는 새로운 기법을 제안한다. 이 기법은 orthogonal wavelet 변환을 기초로 하고 있으며 원본 영상과 처리된 영상 데이터가 모두 가용하다는 것을 전제로 한다. Wavelet을 이용해 주파수에 따라 분할된 영상 정보를 이용해 각각의 부영역 별 차영상을 획득하고 이 획득된 영상의 에너지를 이용해 화질 평가 수치를 계산한다. 부영역 별로 획득된 영상은 일정한 크기의 블록으로 분할되어 동일한 블록 내에서 가용한 영상의 특징에 관한 정보(contrast, edge 영역의 분포 정도) 벡터와 내적하여 새로운 특징 벡터로 사용되고, 이 특징 벡터의 가중치를 최적화하여 높은 상관도의 화질평가 점수를 산출하게 된다.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.224-227
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• 2004

From 1980's, the DWT(Discrete Wavelet Transform) is applied to the data/image processing. Many people use the DWT in remote sensing for diversity purposes and they are satisfied with the wavelet theory. Though the algorithm for wavelet is very diverse, many people use the standard wavelet such as Daubechies D4 wavelet and biorthogonal 9/7 wavelet. We will overview the wavelet theory for discrete form which can be applied to the image processing. First, we will introduce the basic DWT algorithm and review the wavelet algorithm: EZW (Embedded Zerotree Wavelet), SPIHT(Set Partitioning in Hierarchical Trees), Lifting scheme, Curvelet, etc. Finally, we will suggest the properties of wavelet algorithm; and wavelet filter for each image processing in remote sensing.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.362-364
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• 2001

This paper presents the establishment of the wavelet transform domain sign algorithm and performance analysis by using wavelet filter such as multiplier-free QMF which don't require multiple computation.