• Title/Summary/Keyword: wavelet.

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A Study on the Wavelet Matched Filter Design and Correlation Properties in the Optical Correlator (웨이브릿 정합 필터의 설계와 광상관기 구조에서의 상관특성에 관한 연구)

  • 김주영;김석희
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.4
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    • pp.701-711
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    • 1994
  • In this paper, we design wavelet matched filters using Wavelet Transform available in the field of time-frequency analysis, for the optical patter recognition, and study optical correlation properites according to variations of the dilation factor of wavelet functions, which were compared with conventional matched filter and POF. We have found that the wavelet matched filters depend upon the shapes if used input patterns and dilation factors of the wavelet function in order to have the best dicriminability. Also, we show the edge enhanced effects of 2-D image, which is one of the properities of the wavelet transform. If has been found that the wavelet matched filter can discriminate better than the conventional matched filter and POF owing to their bandpass properties, and found that the proposed wavelet matched filters have more sensitive correlation response than POF.

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A Study on Fuzzy Wavelet Neural Network System Based on ANFIS Applying Bell Type Fuzzy Membership Function (벨형 퍼지 소속함수를 적용한 ANFIS 기반 퍼지 웨이브렛 신경망 시스템의 연구)

  • 변오성;조수형;문성용
    • Journal of the Institute of Electronics Engineers of Korea TE
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    • v.39 no.4
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    • pp.363-369
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    • 2002
  • In this paper, it could improved on the arbitrary nonlinear function learning approximation which have the wavelet neural network based on Adaptive Neuro-Fuzzy Inference System(ANFIS) and the multi-resolution Analysis(MRA) of the wavelet transform. ANFIS structure is composed of a bell type fuzzy membership function, and the wavelet neural network structure become composed of the forward algorithm and the backpropagation neural network algorithm. This wavelet composition has a single size, and it is used the backpropagation algorithm for learning of the wavelet neural network based on ANFIS. It is confirmed to be improved the wavelet base number decrease and the convergence speed performances of the wavelet neural network based on ANFIS Model which is using the wavelet translation parameter learning and bell type membership function of ANFIS than the conventional algorithm from 1 dimension and 2 dimension functions.

Image Restoration by Lifting-Based Wavelet Domain E-Median Filter

  • Koc, Sema;Ercelebi, Ergun
    • ETRI Journal
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    • v.28 no.1
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    • pp.51-58
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    • 2006
  • In this paper, we propose a method of applying a lifting-based wavelet domain e-median filter (LBWDEMF) for image restoration. LBWDEMF helps in reducing the number of computations. An e-median filter is a type of modified median filter that processes each pixel of the output of a standard median filter in a binary manner, keeping the output of the median filter unchanged or replacing it with the original pixel value. Binary decision-making is controlled by comparing the absolute difference of the median filter output and the original image to a preset threshold. In addition, the advantage of LBWDEMF is that probabilities of encountering root images are spread over sub-band images, and therefore the e-median filter is unlikely to encounter root images at an early stage of iterations and generates a better result as iteration increases. The proposed method transforms an image into the wavelet domain using lifting-based wavelet filters, then applies an e-median filter in the wavelet domain, transforms the result into the spatial domain, and finally goes through one spatial domain e-median filter to produce the final restored image. Moreover, in order to validate the effectiveness of the proposed method we compare the result obtained using the proposed method to those using a spatial domain median filter (SDMF), spatial domain e-median filter (SDEMF), and wavelet thresholding method. Experimental results show that the proposed method is superior to SDMF, SDEMF, and wavelet thresholding in terms of image restoration.

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The Three Directional Separable Processing Method for Double-Density Wavelet Transformation Improvement (이중 밀도 웨이브렛 변환의 성능 향상을 위한 3방향 분리 처리 기법)

  • Shin, Jong Hong
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.2
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    • pp.131-143
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    • 2012
  • This paper introduces the double-density discrete wavelet transform using 3 direction separable processing method, which is a discrete wavelet transform that combines the double-density discrete wavelet transform and quincunx sampling method, each of which has its own characteristics and advantages. The double-density discrete wavelet transform is nearly shift-invariant. But there is room for improvement because not all of the wavelets are directional. That is, although the double-density DWT utilizes more wavelets, some lack a dominant spatial orientation, which prevents them from being able to isolate those directions. The dual-tree discrete wavelet transform has a more computationally efficient approach to shift invariance. Also, the dual-tree discrete wavelet transform gives much better directional selectivity when filtering multidimensional signals. But this transformation has more cost complexity Because it needs eight digital filters. Therefor, we need to hybrid transform which has the more directional selection and the lower cost complexity. A solution to this problem is a the double-density discrete wavelet transform using 3 direction separable processing method. The proposed wavelet transformation services good performance in image and video processing fields.

Fast Triangular Mesh Approximation for Terrain Data Using Wavelet Coefficients (Wavelet 변환 계수를 이용한 대용량 지형정보 데이터의 삼각형 메쉬근사에 관한 연구)

  • 유한주;이상지;나종범
    • Journal of Broadcast Engineering
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    • v.2 no.1
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    • pp.65-73
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    • 1997
  • This paper propose a new triangular mesh approximation method using wavelet coefficients for large terrain data. Using spatio-freguency localization characteristics of wavelet coefficients, we determine the complexity of terrain data and approximate the data according to the complexity. This proposed algorithm is simple and requires low computational cost due to its top-down approach. Because of the similarity between the mesh approximation and data compression procedures based on wavelet transform, we combine the mesh approximation scheme with the Embedded Zerotree Wavelet (EZW) coding scheme for the effective management of large terrain data. Computer simulation results demonstrate that the proposed algorithm is very prospective for the 3-D visualization of terrain data.

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A Study on Probability of Bit Error for Wavelet in 4-ary SWSK System (4-ary SWSK 시스템에서 웨이브릿에 대한 비트 에러 확률에 관한 연구)

  • Jeong, Tae-Il
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.1
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    • pp.57-62
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    • 2011
  • This paper presents a study on the performance analysis on probability of bit error for wavelet in 4-ary SWSK system. The formula for the bit error probability in 4-ary SWSK system was derived from the conventional method. This paper experimentally implements the probability of bit error for Daubechies, Biorthogonal, Coiflet and Symlet wavelet using the conventional formula of bit error probability. Additionally, the performance of bit error probability is analyzed for the period and the number of wavelet taps. Based on the results, we confirmed that the performance of Coiflet and Symlet wavelet for the probability of bit error is superior to the other wavelet, and their probability of bit error are similar.

Rectangular prism pressure coherence by modified Morlet continuous wavelet transform

  • Le, Thai-Hoa;Caracoglia, Luca
    • Wind and Structures
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    • v.20 no.5
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    • pp.661-682
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    • 2015
  • This study investigates the use of time-frequency coherence analysis for detecting and evaluating coherent "structures" of surface pressures and wind turbulence components, simultaneously on the time-frequency plane. The continuous wavelet transform-based coherence is employed in this time-frequency examination since it enables multi-resolution analysis of non-stationary signals. The wavelet coherence quantity is used to identify highly coherent "events" and the "coherent structure" of both wind turbulence components and surface pressures on rectangular prisms, which are measured experimentally. The study also examines, by proposing a "modified" complex Morlet wavelet function, the influence of the time-frequency resolution and wavelet parameters (i.e., central frequency and bandwidth) on the wavelet coherence of the surface pressures. It is found that the time-frequency resolution may significantly affect the accuracy of the time-frequency coherence; the selection of the central frequency in the modified complex Morlet wavelet is the key parameter for the time-frequency resolution analysis. Furthermore, the concepts of time-averaged wavelet coherence and wavelet coherence ridge are used to better investigate the time-frequency coherence, the coherently dominant events and the time-varying coherence distribution. Experimental data derived from physical measurements of turbulent flow and surface pressures on rectangular prisms with slenderness ratios B/D=1:1 and B/D=5:1, are analyzed.

Image Cryptographic Algorithm Based on the Property of Wavelet Packet Transform (웨이브렛 패킷 변환의 특성을 이용한 영상 암호화 알고리즘)

  • Shin, Jonghong
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.14 no.2
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    • pp.49-59
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    • 2018
  • Encryption of digital images has been requested various fields. In the meantime, many algorithms based on a text - based encryption algorithm have been proposed. In this paper, we propose a method of encryption in wavelet transform domain to utilize the characteristics of digital image. In particular, wavelet transform is used to reduce the association between the encrypted image and the original image. Wavelet packet transformations can be decomposed into more subband images than wavelet transform, and various position permutation, numerical transformation, and visual transformation are performed on the coefficients of this subband image. As a result, this paper proposes a method that satisfies the characteristics of high encryption strength than the conventional wavelet transform and reversibility. This method also satisfies the lossless symmetric key encryption and decryption algorithm. The performance of the proposed method is confirmed by visual and quantitative. Experimental results show that the visually encrypted image is seen as a completely different signal from the original image. We also confirmed that the proposed method shows lower values of cross correlation than conventional wavelet transform. And PSNR has a sufficiently high value in terms of decoding performance of the proposed method. In this paper, we also proposed that the degree of correlation of the encrypted image can be controlled by adjusting the number of wavelet transform steps according to the characteristics of the image.

Analysis of Hydrologic Time Series Using Wavelet Transform (Wavelet Transform을 이용한 수문시계열 분석)

  • Kwon, Hyun-Han;Moon, Young-Il
    • Journal of Korea Water Resources Association
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    • v.38 no.6 s.155
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    • pp.439-448
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    • 2005
  • This paper introduces the wavelet transform that was improved by the fourier transform to assess periodicities and trends, we assessed propriety with examples of two monthly precipitation data, annual precipitation, SOI index and SST index. The wavelet transform can effectively assess the power spectrum corresponding to frequency as maintaining chronological characteristics. The results of the analysis using the wavelet transform showed that the monthly precipitation have the strongest power spectrum near that of 1 year, and the annual precipitation represent the dominated spectrum in the band of 2-8 years. Also, the SOI index and SST index indicate the strongest power spectrum in the band of 2-8 years.

Adaptive High-order Variation De-noising Method for Edge Detection with Wavelet Coefficients

  • Chenghua Liu;Anhong Wang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.2
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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.