• Title, Summary, Keyword: Discrete stationary wavelet transform

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SWT -based Wavelet Filter Application for De-noising of Remotely Sensed Imageries

  • Yoo Hee-Young;Lee Kiwon;Kwon Byung-Doo
    • Proceedings of the KSRS Conference
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    • pp.505-508
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    • 2005
  • Wavelet scheme can be applied to the various remote sensing problems: conventional multi-resolution image analysis, compression of large image sets, fusion of heterogeneous sensor image and segmentation of features. In this study, we attempted wavelet-based filtering and its analysis. Traditionally, statistical methods and adaptive filter are used to manipulate noises in the image processing procedure. While we tried to filter random noise from optical image and radar image using Discrete Wavelet Transform (DW1) and Stationary Wavelet Transform (SW1) and compared with existing methods such as median filter and adaptive filter. In result, SWT preserved boundaries and reduced noises most effectively. If appropriate thresholds are used, wavelet filtering will be applied to detect road boundaries, buildings, cars and other complex features from high-resolution imagery in an urban environment as well as noise filtering

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SWT (Stationary Wavelet Transform)을 이용한 영상 잡음 제거

  • Yu, Hye-Rim;Jo, Hyeon-Suk;Lee, Hyeong;Lee, In-Jeong
    • Proceedings of the Korea Society of Information Technology Applications Conference
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    • pp.9-28
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    • 2007
  • It is well known that wavelet transform is a signal processing technique which can display the signals on in both time and frequency domain. In this paper, we proposed a new approach based on stationary wavelet transform to provide an enhanced approach for eliminating noise. A 'stationary wavelet transform', where the coefficient sequences are not decimated at each stage, is described. The testing result on sample iris images has shown an enhanced image quality and also show that it has a superior performance than traditional discrete wavelet transform.

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Performance Improvement of Aerial Images Taken by UAV Using Daubechies Stationary Wavelet (Daubechies 정상 웨이블릿을 이용한 무인항공기 촬영 영상 성능 개선)

  • Kim, Sung-Hoon;Hong, Gyo-Young
    • The Journal of Advanced Navigation Technology
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    • v.20 no.6
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    • pp.539-543
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    • 2016
  • In this paper, we study the technique to improve the performance of the aerial images taken by UAV using daubechies stationary wavelet transform. When aerial images taken by UAV were damaged by gaussian noise very commonly applied, the experiment for image performance improvement was performed. It was known that stationary wavelet transform is the transferring solution to the problem occurred by down sampling from DWT also more efficient to remove noise than DWT. Also haar wavelet is discontinuous function so not efficient for smooth signal and image processing. Therefore, this study is confirmed that the noise can be removed by daubechies stationary wavelet and the performance is improved by haar stationary wavelet.

An Application of the Undecimated Discrete Wavelet Transform (Undecimated 웨이블릿 변환응용)

  • Lee, Chang-Soo;Yoo, Kyung-Yul
    • Proceedings of the IEEK Conference
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    • pp.605-608
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    • 2000
  • This paper introduces a new structure for the undecimated discrete wavelet transform (UDWT). This structure combines the stationary wavelet transform with a lifting scheme and its design is based on a polyphase structure .where the downsampling and split stage are removed. The suggested structure inherits the simplicity of the lifting scheme, such that the inverse transform is easily implemented. The performanace of the proposed undecimated lifting is verified on a signal denoising application.

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Noise Attenuation of Marine Seismic Data with a 2-D Wavelet Transform (2-D 웨이브릿 변환을 이용한 해양 탄성파탐사 자료의 잡음 감쇠)

  • Kim, Jin-Hoo;Kim, Sung-Bo;Kim, Hyun-Do;Kim, Chan-Soo
    • Journal of the Korean Society of Marine Engineering
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    • v.32 no.8
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    • pp.1309-1314
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    • 2008
  • Seismic data is often contaminated with high-energy, spatially aliased noise, which has proven impractical to attenuate using Fourier techniques. Wavelet filtering, however, has proven capable of attacking several types of localized noise simultaneously regardless of their frequencies. In this study a 2-D stationary wavelet transform is used to decompose seismic data into its wavelet components. A threshold is applied to these coefficients to attenuate high amplitude noise, followed by an inverse transform to reconstruct the seismic trace. The stationary wavelet transform minimizes the phase-shift errors induced by thresholding that occur when the conventional discrete wavelet transform is used.

Tunable Q-factor 2-D Discrete Wavelet Transformation Filter Design And Performance Analysis (Q인자 조절 가능 2차원 이산 웨이브렛 변환 필터의 설계와 성능분석)

  • Shin, Jonghong
    • Journal of the Korea Society of Digital Industry and Information Management
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    • v.11 no.1
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    • pp.171-182
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    • 2015
  • The general wavelet transform has profitable property in non-stationary signal analysis specially. The tunable Q-factor wavelet transform is a fully-discrete wavelet transform for which the Q-factor Q and the asymptotic redundancy r, of the transform are easily and independently specified. In particular, the specified parameters Q and r can be real-valued. Therefore, by tuning Q, the oscillatory behavior of the wavelet can be chosen to match the oscillatory behavior of the signal of interest, so as to enhance the sparsity of a sparse signal representation. The TQWT is well suited to fast algorithms for sparsity-based inverse problems because it is a Parseval frame, easily invertible, and can be efficiently implemented. The transform is based on a real valued scaling factor and is implemented using a perfect reconstruction over-sampled filter bank with real-valued sampling factors. The transform is parameterized by its Q-factor and its over-sampling rate, with modest over-sampling rates being sufficient for the analysis/synthesis functions to be well localized. This paper describes filter design of 2D discrete-time wavelet transform for which the Q-factor is easily specified. With the advantage of this transform, perfect reconstruction filter design and implementation for performance improvement are focused in this paper. Hence, the 2D transform can be tuned according to the oscillatory behavior of the image signal to which it is applied. Therefore, application for performance improvement in multimedia communication field was evaluated.

Fault Location Using Noise Cancellation Technique on Underground Power Cable Systems (노이지 제거기법을 이용한 지중송전계통 고장점 추정)

  • Jung, Chae-Kyun;Lee, Jong-Beom
    • Proceedings of the KIEE Conference
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    • pp.440-441
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    • 2006
  • The fault location algorithm based on wavelet transform was developed to locate the fault more accuracy after the operation of relay. The stationary wavelet transform(SWT) was introduced instead of conventional discrete wavelet transform(DWT) because SWT has redundancy properties which is more useful in noise signal processing. The algorithm was based on the correlation of wavelet coefficients at multi-scales. Fault location algorithm was tested by simulation on real power cable system. From these results, the fault can be located even in very difficult situations, such as at different inception angle and fault resistance.

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Electron Beam Welding Diagnosis Using Wavelet Transform (웨이브렛 변환을 이용한 전자빔 용접 진단)

  • 윤충섭
    • Journal of Welding and Joining
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    • v.21 no.6
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    • pp.33-39
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    • 2003
  • Wavelet transform analysis results show a spectrum energy distribution of CWT along scale factors distinguish the partial, full and over penetration in a electron beam welding by analyzing the curve of spectrum energy at small scale, middle and large scale range, respectively. Two types of signals collected by Ion collector and x-ray sensors and analyzed. The acquired signals from sensors are very complicated since these signals are very closely related the dynamics of keyhole which interact the very high density energy with materials during welding. The results show the wavelet transform is more effective to diagnosis than Fourier Transform, further for the general welding defects which are not a periodic based, but a transient, non-stationary and time-varying phenomena.

Robust Image Fusion Using Stationary Wavelet Transform (정상 웨이블렛 변환을 이용한 로버스트 영상 융합)

  • Kim, Hee-Hoon;Kang, Seung-Hyo;Park, Jea-Hyun;Ha, Hyun-Ho;Lim, Jin-Soo;Lim, Dong-Hoon
    • The Korean Journal of Applied Statistics
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    • v.24 no.6
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    • pp.1181-1196
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    • 2011
  • Image fusion is the process of combining information from two or more source images of a scene into a single composite image with application to many fields, such as remote sensing, computer vision, robotics, medical imaging and defense. The most common wavelet-based fusion is discrete wavelet transform fusion in which the high frequency sub-bands and low frequency sub-bands are combined on activity measures of local windows such standard deviation and mean, respectively. However, discrete wavelet transform is not translation-invariant and it often yields block artifacts in a fused image. In this paper, we propose a robust image fusion based on the stationary wavelet transform to overcome the drawback of discrete wavelet transform. We use the activity measure of interquartile range as the robust estimator of variance in high frequency sub-bands and combine the low frequency sub-band based on the interquartile range information present in the high frequency sub-bands. We evaluate our proposed method quantitatively and qualitatively for image fusion, and compare it to some existing fusion methods. Experimental results indicate that the proposed method is more effective and can provide satisfactory fusion results.

Development of Fault Location Method Using SWT and Travelling Wave on Underground Power Cable Systems (SWT와 진행파를 이용한 지중송전계통 고장점 추정 기법 개발)

  • Jung, Chae-Kyun;Lee, Jong-Beom
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.2
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    • pp.184-190
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    • 2008
  • The fault location algorithm based on stationary wavelet transform was developed to locate the fault point more accurately. The stationary wavelet transform(SWT) was introduced instead of conventional discrete wavelet transform(DWT) because SWT has redundancy properties which is more useful in noise signal processing. In previous paper, noise cancellation technique based on the correlation of wavelet coefficients at multi-scales was introduced, and the efficiency was also proved in full. In this paper, fault section discrimination and fault location algorithm using noise cancellation technique were tested by ATP simulation on real power cable systems. From these results, the fault can be located even in very difficult and complicated situations such as different inception angle and fault resistance.