• Title/Summary/Keyword: Recover noise

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IMAGE DENOISING BASED ON MIXTURE DISTRIBUTIONS IN WAVELET DOMAIN

  • Bae, Byoung-Suk;Lee, Jong-In;Kang, Moon-Gi
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.246-249
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    • 2009
  • Due to the additive white Gaussian noise (AWGN), images are often corrupted. In recent days, Bayesian estimation techniques to recover noisy images in the wavelet domain have been studied. The probability density function (PDF) of an image in wavelet domain can be described using highly-sharp head and long-tailed shapes. If a priori probability density function having the above properties would be applied well adaptively, better results could be obtained. There were some frequently proposed PDFs such as Gaussian, Laplace distributions, and so on. These functions model the wavelet coefficients satisfactorily and have its own of characteristics. In this paper, mixture distributions of Gaussian and Laplace distribution are proposed, which attempt to corporate these distributions' merits. Such mixture model will be used to remove the noise in images by adopting Maximum a Posteriori (MAP) estimation method. With respect to visual quality, numerical performance and computational complexity, the proposed technique gained better results.

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Adaptive line Enhancement by Using Adaptive Observer (적응 관측자를 사용한 ALE)

  • 최종호;이하정;이상욱
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.36 no.11
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    • pp.819-825
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    • 1987
  • The ALE problem, which tries to recover a sinusoidal signal corrupted by noise, has been solved using FIR filters. Recently several methods have been proposed using a norch filter of IIR type. In this study, the notch filter was represented with a parameter and auxiliary signals were generated by using an adaptive observer. A simple method is proposed to estimate the parameter. This method is tested under various circumstances by changing the input frequency, S/N ratio, and the type of the noise. The simulation shows that this method gives much better results than the other known methods with respect to the input S/N ratio and converging times. This method is simple and does not require much conputation, so it can be easily implemented in real time applications.

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A Relative for Finite Element Nonlinear Structural Analysis (상대절점좌표를 이용한 비선형 유한요소해석법)

  • Kang, Ki-Rang;Cho, Heui-Je;Bae, Dae-Sung
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.11a
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    • pp.788-791
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    • 2005
  • Nodal displacements are referred to the Initial configuration in the total Lagrangian formulation and to the last converged configuration in the updated Lagrangian formulation. This research proposes a relative nodal displacement method to represent the position and orientation for a node in truss structures. Since the proposed method measures the relative nodal displacements relative to its adjacent nodal reference frame, they are still small for a truss structure undergoing large deformations for the small size elements. As a consequence, element formulations developed under the small deformation assumption are still valid fer structures undergoing large deformations, which significantly simplifies the equations of equilibrium. A structural system is represented by a graph to systematically develop the governing equations of equilibrium for general systems. A node and an element are represented by a node and an edge in graph representation, respectively. Closed loops are opened to form a spanning tree by cutting edges. Two computational sequences are defined in the graph representation. One is the forward path sequence that is used to recover the Cartesian nodal displacements from relative nodal displacements and traverses a graph from the base node towards the terminal nodes. The other is the backward path sequence that is used to recover the nodal forces in the relative coordinate system from the known nodal forces in the absolute coordinate system and traverses from the terminal nodes towards the base node. One closed loop structure undergoing large deformations is analyzed to demonstrate the efficiency and validity of the proposed method.

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High Density Impulse Noise Reduction Filter Algorithm using Effective Pixels (유효 화소를 이용한 고밀도 임펄스 잡음 제거 필터 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.10
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    • pp.1320-1326
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    • 2018
  • Digital video equipment is important in the 4th industrial revolution and is widely used in different fields for various purpose. Data of digital video equipment is exposed to noise due to different reasons including user environment and processing and such noise affect output and processing method. This can even cause error, resulting in decreased reliability of the equipment. In this research, it offers algorithm to effectively recover video by removing noise and impulse noise occurring during the process of channel delivery. This proposed algorithm recovers video by exploring valid pixel using directional local mask and noise determination. Then, valid pixel calculated goes through the final output calculation through comparative analysis on estimation. For comparing suggested method and algorithm, simulation is carried out. For checking the function of it, PSNR and profile are analyzed.

PhysioCover: Recovering the Missing Values in Physiological Data of Intensive Care Units

  • Kim, Sun-Hee;Yang, Hyung-Jeong;Kim, Soo-Hyung;Lee, Guee-Sang
    • International Journal of Contents
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    • v.10 no.2
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    • pp.47-58
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    • 2014
  • Physiological signals provide important clues in the diagnosis and prediction of disease. Analyzing these signals is important in health and medicine. In particular, data preprocessing for physiological signal analysis is a vital issue because missing values, noise, and outliers may degrade the analysis performance. In this paper, we propose PhysioCover, a system that can recover missing values of physiological signals that were monitored in real time. PhysioCover integrates a gradual method and EM-based Principle Component Analysis (PCA). This approach can (1) more readily recover long- and short-term missing data than existing methods, such as traditional EM-based PCA, linear interpolation, 5-average and Missing Value Singular Value Decomposition (MSVD), (2) more effectively detect hidden variables than PCA and Independent component analysis (ICA), and (3) offer fast computation time through real-time processing. Experimental results with the physiological data of an intensive care unit show that the proposed method assigns more accurate missing values than previous methods.

Multicasting Multiple Description Coding Using p-cycle Network Coding

  • Farzamnia, Ali;Syed-Yusof, Sharifah K.;Fisal, Norsheila
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.12
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    • pp.3118-3134
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    • 2013
  • This paper deliberates for a multimedia transmission scheme combining multiple description coding (MDC) and network coding (NC). Our goal is to take advantage from the property of MDC to provide quantized and compressed independent and identically distributed (iid) descriptions and also from the benefit of network coding, which uses network resources efficiently to recover lost data in the network. Recently, p-cycle NC has been introduced to recover and protect any lost or distorted descriptions at the receiver part exactly without need of retransmission. So far, MDC have not been explored using this type of NC. Compressed and coded descriptions are transmitted through the network where p-cycle NC is applied. P-cycle based algorithm is proposed for single and multiple descriptions lost. Results show that in the fixed bit rate, the PSNR (Peak Signal to Noise Ratio) of our reconstructed image and also subjective evaluation is improved significantly compared to previous work which is averaging method joint with MDC in order to conceal lost descriptions.

Jointly Learning of Heavy Rain Removal and Super-Resolution in Single Images

  • Vu, Dac Tung;Kim, Munchurl
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2020.11a
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    • pp.113-117
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    • 2020
  • Images were taken under various weather such as rain, haze, snow often show low visibility, which can dramatically decrease accuracy of some tasks in computer vision: object detection, segmentation. Besides, previous work to enhance image usually downsample the image to receive consistency features but have not yet good upsample algorithm to recover original size. So, in this research, we jointly implement removal streak in heavy rain image and super resolution using a deep network. We put forth a 2-stage network: a multi-model network followed by a refinement network. The first stage using rain formula in the single image and two operation layers (addition, multiplication) removes rain streak and noise to get clean image in low resolution. The second stage uses refinement network to recover damaged background information as well as upsample, and receive high resolution image. Our method improves visual quality image, gains accuracy in human action recognition task in datasets. Extensive experiments show that our network outperforms the state of the art (SoTA) methods.

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Application of Blind Deconvolution with Crest Factor for Recovery of Original Rolling Element Bearing Defect Signals (볼 베어링 결함신호 복원을 위한 파고율을 이용한 Blind Deconvolution의 응용)

  • Son, Jong-Duk;Yang, Bo-Suk;Tan, A.C.C.;Mathew, J.
    • Proceedings of the KSME Conference
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    • 2004.11a
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    • pp.585-590
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    • 2004
  • Many machine failures are not detected well in advance due to the masking of background noise and attenuation of the source signal through the transmission mediums. Advanced signal processing techniques using adaptive filters and higher order statistics have been attempted to extract the source signal from the measured data at the machine surface. In this paper, blind deconvolution using the eigenvector algorithm (EVA) technique is used to recover a damaged bearing signal using only the measured signal at the machine surface. A damaged bearing signal corrupted by noise with varying signal-to-noise (s/n) was used to determine the effectiveness of the technique in detecting an incipient signal and the optimum choice of filter length. The results show that the technique is effective in detecting the source signal with an s/n ratio as low as 0.21, but requires a relatively large filter length.

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A Carrier Frequency Synchronization Scheme for modified ATSC Systems (수정된 ATSC 전송 시스템을 위한 반송파 주파수 동기부 설계에 관한 연구)

  • Jeon, Young-Gon;Kim, Joon-Tae
    • Journal of Broadcast Engineering
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    • v.16 no.1
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    • pp.96-107
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    • 2011
  • Recently, studies of 3D HDTV broadcasting technology have been processed actively. Korea is making efforts to modify Advanced Television Systems Committee (ATSC) 8-Vestigial Side Band (8-VSB) systems for terrestrial 3D HDTV broadcasting services. We intend to adopt a new frame structure to use PN (Pseudo-Noise) sequence as frame header, and VSB modulation. PN sequence is used to recover carrier freqeuncy offset, carrier phase error. In this paper, we will describe this system as the modified ATSC systems. The receiver of the modified ATSC system should be able to estimate and recover carrier frequency offset exactly. A existing ATSC systems inserts pilot to recover carrier frequency offset, on the other hand the modified ATSC systems use PN sequence to recovery carrier frequency offset without the use of pilot. In this paper, we introduce carrier frequency recovery (CFR) scheme for the modified ATSC systems. The proposed CFR scheme is composed of coarse CFR scheme using Fitz algorithm and fine CFR scheme using a simple PN sequence correlation algorithm. And, the symbol information of QAM modulated signal is contained in both In-phase (I)channel and Quadrature-phase (Q)channel. However the symbol information of VSB modulated signal is contained in I channel, and Q channel is just Hilbert transform of I channel. For the reason, VSB modulated symbols can not have fixed phase like QAM modulated symbols, and VSB modulated symbols is more sensitive to carrier frequency offset. Therefore we perform phase correction of received PN sequence to improve performance.

Digital Radiography Images Restoration with Wiener Filter in Wavelet Domain (웨이블릿영역에서 위너필터를 이용한 디지털 방사선 영상 복원)

  • Jeong, Jae-Won;Kim, Dong-Youn
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.46 no.6
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    • pp.58-64
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    • 2009
  • Digital radiography (DR) images are corrupted by the additive noise, and also distorted by system impulse response. These unwanted phenomena are obstacles to obtain the desired image. To recover the original image, we applied multiscale Wiener filters in wavelet domain for DR images. The multiscale Wiener filter is first proposed by Chen for the restoration of fractal signals which are distorted by the system impulse response and additive noise. In this paper, we extended the multiscale Wiener filter to the two dimensional data. To compare the performance of ours with others, some simulations are given for a couple of wavelet filters with different wavelet levels, system impulse reponses and various noise power. When the addive noise powers are between 20-32 dB, the signal to noise ratio(SNR) of the proposed system is 0.5-2.0 dB better than that of the traditional Wiener filter method.