• Title/Summary/Keyword: Discrete Wavelet Transform

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Data Hiding Algorithm for Images Using Discrete Wavelet Transform and Arnold Transform

  • Kasana, Geeta;Singh, Kulbir;Bhatia, Satvinder Singh
    • Journal of Information Processing Systems
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    • v.13 no.5
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    • pp.1331-1344
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    • 2017
  • In this paper, data hiding algorithm using Discrete Wavelet Transform (DWT) and Arnold Transform is proposed. The secret data is scrambled using Arnold Transform to make it secure. Wavelet subbands of a cover image are obtained using DWT. The scrambled secret data is embedded into significant wavelet coefficients of subbands of a cover image. The proposed algorithm is robust to a variety of attacks like JPEG and JPEG2000 compression, image cropping and median filtering. Experimental results show that the PSNR of the composite image is 1.05 dB higher than the PSNR of existing algorithms and capacity is 25% higher than the capacity of existing algorithms.

Application of discrete wavelet transform to prediction of ram stuck phenomena

  • Byun, Seung-Hyun;Cho, Byung-Hak;Shin, Chang-Hoon;Park, Joon-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1445-1449
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    • 2005
  • The ram assembly is important equipment in fueling machine of PHWR(Pressurized Heavy Water Reactor) plant where fuel replacement is possible while the plant is in service. Troubles in the ram assembly can cause lots of difficulties in power plant operation. The ram assembly is typically composed of the B-ram, the L-Ram and the C-Ram. The B-ram is focused in this paper because it plays the most important role in the ram assembly. Among the ram fault phenomena, ram stuck phenomena are the most frequent cases in the B-ram, which has a ball screw mechanism driven by a hydraulic motor. Ram stuck phenomena are due to ball wear and damage in ball nut that increase in proportion to the number of fuel replacement. It is required to predict ram stuck phenomena before they occur. In this paper, a method is proposed for predicting ram stuck phenomena using a discrete wavelet transform. The discrete wavelet transform provides information on both the time and frequency characteristics of the input signals. The proposed method uses the frequency bandwidths of coefficients of discrete wavelet decompositions and detail coefficients of discrete wavelet transform to predict ram stuck phenomena. The signal used in this paper is a torque-related signal such as a hydraulic service outlet pressure signal in a hydraulic driving system or a current signal in a DC motor driving system. Finally, the validity of the proposed method is shown via experiment using ball nut characteristic test equipment that simulates ram stuck phenomena due to increased ball friction in ball nut.

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A Pattern Recognition System Using 2D Wavelets and Second-Order Neural Networks (2D wavelet과 이차신경망을 이용한 패턴인식 시스템)

  • Lee, Bong-Kyu
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.50 no.10
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    • pp.473-478
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    • 2001
  • Image processings using the two-dimensional wavelet transform (2DWT) have been a very active research area in recent years because the 2DWT possess many good properties. However, the discrete 2DWT can not be used for pattern recognition directly because it does not have the translation property. In this paper, we show why conventional discrete two-dimensional wavelet transforms cannot be used for pattern recognitions directly. Then, we propose a new method that makes it possible to use discrete 2DWT to pattern recognition without modification of standard pyramidal algorithms. The main idea of our method is to postprocess the wavelet transformed images using the second-order neural network. To justify the validity of the method, evaluations with test images were performed. The effectiveness of the method can be shown by the evaluation results.

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Bayesian Curve Clustering in Microarray

  • Lee, Kyeong-Eun;Mallick, Bani K.
    • 한국데이터정보과학회:학술대회논문집
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    • 2006.04a
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    • pp.39-42
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    • 2006
  • We propose a Bayesian model-based approach using a mixture of Dirichlet processes model with discrete wavelet transform, for curve clustering in the microarray data with time-course gene expressions.

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The Analysis of Partial Discharges Pattern using Discrete Wavelet Transform (이산 웨이브렛변환에 의한 부분방전패턴 분석)

  • 이현동;김충년;지승욱;박광서;이광식;이동인
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2000.11a
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    • pp.183-187
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    • 2000
  • This paper deals with multiresolution analysis of wavelet transform for partial discharge(PD), both corona and surface discharge. Multiresolution analysis was used for performing discrete wavelet transform. PD signals was decomposed into "approximation" and "detail" components until 4 levels by using discrete wavelet analysis. In this paper, daubechies family is adopted for the research of the characteristics of PD signals. The results show that in corona discharge the segment 7, 8, 9, 10, 11 values of defined variable is increased with discharge process, so phase distribution is characterized by 210~330 ranges. In case surface discharge in expoxy insulator inserted, defined variable values is fairly symmetric discharge pattern because coupled both corona and dielectric bounded discharges. We can confirmly discriminate the type PD source. the type PD source.

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A Study of Shorted-Turn Detection in the Cylindrical Synchronous Generator Rotor Windings via Discrete Wavelet Transform (이산 웨이브렛 변환을 이용한 동기발전기 회전자 층간단락 진단에 관한 연구)

  • Kim, Y.J.;Kim, J.M.
    • Proceedings of the KIPE Conference
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    • 2005.07a
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    • pp.476-478
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    • 2005
  • This paper describes a method for the detection of shorted-turn in the cylindrical synchronous generator rotor windings based on the discrete wavelet transform. Multi-resolution analysis(MRA) based on discrete wavelet transform provides a set of decomposed signals in independent frequency bands. In the proposed method, shorted-turn detection in rotor windings is based on the decomposition of the rotor currents, where wavelet coefficients of these signals have been extracted. Comparing these extracted coefficients is used for diagnosing the healthy machine from faulty machine. Experimental results show the effectiveness of the proposed method for shorted-turn detection in the cylindrical synchronous generator rotor windings.

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Fractal image compression based on discrete wavelet transform domain (이산 웨이브렛 변환 영역에 기반한 프랙탈 영상 압축)

  • 배성호;박길흠
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.7
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    • pp.1654-1667
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    • 1996
  • The conventional fractal image compression methods have high computational complexity at encoding reduce PSNR at low bit rate and havehighly visible blocking effects in a reconstructed image. In this paper we propose a fractal image compression method based on disctete wavelet transform domain, which takes the absolute value of discrete wavelet transform coefficient, and assembles the discrete wavelet tranform coefficients of different highpass subbands corresponding to the same spatial block and then applies "0" encoding according to the energy of each range blocks. The proposed method improved PSNR at low bit rate and reduced computational complexity at encoding distinctly. Also, this method can achieve a blockless reconstructed image and perform hierarchical decoding without recursive constractive transformation. Computer simulations with several test images show that the proposed method shows better performance than convnetional fractal coding methods for encoding still pictures. pictures.

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A Study on the Sonar Data Processing by Using a Discrete Wavelet Transform (이산 웨이브릿 변환을 이용한 소나 자료처리에 관한 연구)

  • Kim, Jin-Hoo;Kim, Hyun-Do
    • Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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    • 2003.05a
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    • pp.324-329
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    • 2003
  • Spectral analysis is an important signal processing tool for time series data. The transformation of a time series into the frequency domain is the basis for a significant number of processing algorithms and interpretive methods. Recently developed transforms based on the new mathematical field of wavelet analysis bypass the resolution limitation and offer superior spectral decomposition. The discrete wavelet transform of Sonar data provides spectral localization of noises, hence noises can be filtered out successfully.

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Wavelet-Based Variable Block Size Fractal Image Coding (웨이브렛 기반 가변 블록 크기 플랙탈 영상 부호화)

  • 문영숙;전병민
    • Journal of Broadcast Engineering
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    • v.4 no.2
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    • pp.127-133
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    • 1999
  • The conventional fractal image compression based on discrete wavelet transform uses the fixed block size in fractal coding and reduces PSNR at low bit rate. This paper proposes a fractal image coding based on discrete wavelet transform which improves PSNR by using variable block size in fractal coding. In the proposed method. the absolute values of discrete wavelet transform coefficients are computed. and the discrete wavelet transform coefficients of different highpass subbands corresponding to the same spatial block are assembled. and the fractal code for the range block of each range block level is assigned. and then a decision tree C. the set of choices among fractal coding. "0" encoding. and scalar quantization is generated and a set of scalar quantizers q is chosen. And then the wavelet coefficients. fractal codes. and the choice items in the decision tree are entropy coded by using an adaptive arithmetic coder. This proposed method improved PSNR at low bit rate and could achieve a blockless reconstructed image. As the results of experiment. the proposed method obtained better PSNR and higher compression ratio than the conventional fractal coding method and wavelet transform coding.rm coding.

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Texture Image Fusion on Wavelet Scheme with Space Borne High Resolution Imagery: An Experimental Study

  • Yoo, Hee-Young;Lee , Ki-Won
    • Korean Journal of Remote Sensing
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    • v.21 no.3
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    • pp.243-252
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    • 2005
  • Wavelet transform and its inverse processing provide the effective framework for data fusion. The purpose of this study is to investigate applicability of wavelet transform using texture images for the urban remote sensing application. We tried several experiments regarding image fusion by wavelet transform and texture imaging using high resolution images such as IKONOS and KOMPSAT EOC. As for texture images, we used homogeneity and ASM (Angular Second Moment) images according that these two types of texture images reveal detailed information of complex features of urban environment well. To find out the useful combination scheme for further applications, we performed DWT(Discrete Wavelet Transform) and IDWT(Inverse Discrete Wavelet Transform) using texture images and original images, with adding edge information on the fused images to display texture-wavelet information within edge boundaries. The edge images were obtained by the LoG (Laplacian of Gaussian) processing of original image. As the qualitative result by the visual interpretation of these experiments, the resultant image by each fusion scheme will be utilized to extract unique details of surface characterization on urban features around edge boundaries.