• Title/Summary/Keyword: Noise robustness

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Gamma correction FCM algorithm with conditional spatial information for image segmentation

  • Liu, Yang;Chen, Haipeng;Shen, Xuanjing;Huang, Yongping
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.9
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    • pp.4336-4354
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    • 2018
  • Fuzzy C-means (FCM) algorithm is a most usually technique for medical image segmentation. But conventional FCM fails to perform well enough on magnetic resonance imaging (MRI) data with the noise and intensity inhomogeneity (IIH). In the paper, we propose a Gamma correction conditional FCM algorithm with spatial information (GcsFCM) to solve this problem. Firstly, the pre-processing, Gamma correction, is introduced to enhance the details of images. Secondly, the spatial information is introduced to reduce the effect of noise. Then we introduce the effective neighborhood mechanism into the local space information to improve the robustness for the noise and inhomogeneity. And the mechanism describes the degree of participation in generating local membership values and building clusters. Finally, the adjustment mechanism and the spatial information are combined into the weighted membership function. Experimental results on four image volumes with noise and IIH indicate that the proposed GcsFCM algorithm is more effective and robust to noise and IIH than the FCM, sFCM and csFCM algorithms.

A Parametric Voice Activity Detection Based on the SPD-TE for Nonstationary Noises (비정체성 잡음을 위한 SPD-TE 기반 계수형 음성 활동 탐지)

  • Koo, Boneung
    • The Journal of the Acoustical Society of Korea
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    • v.34 no.4
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    • pp.310-315
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    • 2015
  • A single channel VAD (Voice Activity Detection) algorithm for nonstationary noise environment is proposed in this paper. Threshold values of the feature parameter for VAD decision are updated adaptively based on estimates of means and standard deviations of past non-speech frames. The feature parameter, SPD-TE (Spectral Power Difference-Teager Energy), is obtained by applying the Teager energy to the WPD (Wavelet Packet Decomposition) coefficients. It was reported previously that the SPD-TE is robust to noise as a feature for VAD. Experimental results by using TIMIT speech and NOISEX-92 noise databases show that decision accuracy of the proposed algorithm is comparable to several typical VAD algorithms including standards for SNR values ranging from 10 to -10 dB.

OFDM Frequency Offset Estimation Schemes Robust to the Non-Gaussian Noise (비정규 잡음에 강인한 OFDM 주파수 옵셋 추정 기법)

  • Park, Jong-Hun;Yu, Chang-Ha;Yoon, Seok-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.5A
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    • pp.298-304
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    • 2012
  • In this paper, we propose robust estimators for the frequency offset of orthogonal frequency division multiplexing in non-Gaussian noise environments. We first propose a maximum-likelihood (ML) estimator in non-Gaussian noise modeled as a complex isotropic Cauchy process, and then, we present a simpler suboptimal estimator based on the ML estimator. From numerical results, it is demonstrated that the proposed estimators not only outperform the conventional estimators, but also have a robustness in non-Gaussian noise environments.

A PDF-distance minimization algorithm for blind equalization for underwater communication channels with multipath and impulsive noise (다중경로와 임펄스 잡음이 있는 수중 통신 채널의 블라인드 등화를 위한 확률분포-거리 최소화 알고리듬)

  • Kim, Nam-Yong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.2
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    • pp.299-306
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    • 2011
  • In this paper, a blind adaptive equalization algorithm based on PDF-distance minimization and a set of Delta functions is introduced and its superior robustness against impulsive noise and multipath characteristics of underwater communication channels is proved. The conventional CMA based on MSE has shown to be incapable of coping with impulsive noise, and correntropy blind algorithm has also revealed to yield not satisfying performance for the mission. On the other hand, the blind adaptive equalization algorithm based on PDF-distance minimization and a set of Delta functions has been proved to solve effectively the problem of impulsive noise and multipath characteristics of underwater communication channels through theoretical and simulation analysis.

A Robustness Improvement of Adjoint-LMS Algorithms for Active Noise Control (능동소음제어를 위한 Adjoint-LMS 알고리즘의 강인성 개선)

  • Moon, Hak-ryong;Shon, Jin-geun
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.65 no.3
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    • pp.171-177
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    • 2016
  • Noise problem that occurs in living environment is a big trouble in the economic, social and environmental aspects. In this paper, the filtered-X LMS algorithms, the adjoint LMS algorithms, and the robust adjoint LMS algorithms will be introduced for applications in active noise control(ANC). The filtered-X LMS algorithms is currently the most popular method for adapting a filter when the filter exits a transfer function in the error path. The adjoint LMS algorithms, that prefilter the error signals instead of divided reference signals in frequency band, is also used for adaptive filter algorithms to reduce the computational burden of multi-channel ANC systems such as the 3D space. To improve performance of the adjoint LMS ANC system, an off-line measured transfer function is connected parallel to the LMS filter. This parallel-fixed filter acts as a noise controller only when the LMS filter is abnormal condition. The superior performance of the proposed system was compared through simulation with the adjoint LMS ANC system when the adaptive filter is in normal and abnormal condition.

Evolutionary Neural Network based on Quantum Elephant Herding Algorithm for Modulation Recognition in Impulse Noise

  • Gao, Hongyuan;Wang, Shihao;Su, Yumeng;Sun, Helin;Zhang, Zhiwei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.7
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    • pp.2356-2376
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    • 2021
  • In this paper, we proposed a novel modulation recognition method based on quantum elephant herding algorithm (QEHA) evolving neural network under impulse noise environment. We use the adaptive weight myriad filter to preprocess the received digital modulation signals which passing through the impulsive noise channel, and then the instantaneous characteristics and high order cumulant features of digital modulation signals are extracted as classification feature set, finally, the BP neural network (BPNN) model as a classifier for automatic digital modulation recognition. Besides, based on the elephant herding optimization (EHO) algorithm and quantum computing mechanism, we design a quantum elephant herding algorithm (QEHA) to optimize the initial thresholds and weights of the BPNN, which solves the problem that traditional BPNN is easy into local minimum values and poor robustness. The experimental results prove that the adaptive weight myriad filter we used can remove the impulsive noise effectively, and the proposed QEHA-BPNN classifier has better recognition performance than other conventional pattern recognition classifiers. Compared with other global optimization algorithms, the QEHA designed in this paper has a faster convergence speed and higher convergence accuracy. Furthermore, the effect of symbol shape has been considered, which can satisfy the need for engineering.

Wireless Communication Quality Improvement Through DSES Alarmed Noise Image Restoration

  • Ki-Hwan, Kim;HyunHo, Kim;HoonJae, Lee
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.2
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    • pp.55-62
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    • 2023
  • Radio waves must pass through the unstable atmosphere for successful wireless data transmission from space to ground stations. Data link algorithms required by the International Space Data Systems Advisory Committee (CCSDS) must be capable of detecting and resynchronizing cryptographic and receiver-side errors. However, error recovery is not part of the CCSDS requirements. This paper proposes an algorithm that enables robustness and error recovery against various noises. We experimented with environments such as Gaussian, Salt, Pepper, and S&P noise through noise reduction filters, filters that improve sharpness, and EDSR. In addition, we compare similar algorithms SES Alarmed and DSES Alarmed.

Application and Evaluation of Vector Map Watermarking Algorithm for Robustness Enhancement (강인성 향상을 위한 벡터 맵 워터마킹 알고리즘의 적용과 평가)

  • Won, Sung Min;Park, Soo Hong
    • Spatial Information Research
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    • v.21 no.3
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    • pp.31-43
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    • 2013
  • Although the vector map data possesses much higher values than other types of multimedia, the data copyright and the protection against illegal duplication are still far away from the attention. This paper proposes a novel watermarking technique which is both robust to diverse attacks and optimized to a vector map structure. Six approaches are proposed for the design of the watermarking algorithm: point-based approach, building a minimum perimeter triangle, watermark embedding in the length ratio, referencing to the pixel position of the watermark image, grouping, and using the one-way function. Our method preserves the characteristics of watermarking such as embedding effectiveness, fidelity, and false positive rate, while maintaining robustness to all types of attack except a noise attack. Furthermore, our method is a blind scheme in which robustness is independent of the map data. Finally, our method provides a solution to the challenging issue of degraded robustness under severe simplification attacks.

Invisible Watermarking for Improved Security of Digital Video Application (디지털 동영상 어플리케이션의 향상된 보안성을 위한 비시각적인 워터마킹)

  • Seo, Jung-Hee;Park, Hung-Bog
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.10
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    • pp.175-183
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    • 2011
  • Performance of digital video watermarking is an assessment that hides a lot of information in digital videos. Therefore, it is required to find a way that enables to store lots of bits of data into a high quality video of the frequency area of digital contents. Hence, this paper designs a watermarking system improving security with an enhancing watermarking based on invisible watermarking and embedding an watermarking on LH and HL subband and its subband by transforming wavelet after the extraction of luminance component from the frames of video by compromising robustness and invisible of watermarking elements. The performance analysis of security of watermarking is carried out with a statistic method, and makes an assessment of robustness against variety of attacks to invisible watermarking. We can verify the security of watermarking against variety of attacks by testing robustness and invisible through carrying out general signal processing like noise addition, lossy compression, and Low-Pass filtering.

Nonvisibility and robustness evaluation of image watermarking mixed Key and Logo method (키와 로고 방식을 혼합한 이미지 워터마킹의 비가시성과 강인성 평가)

  • Park, Young;Song, Hag-Hyun;Choi, Se-Ha;Lee, Myong-Kil;Kim, Yoon-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.3
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    • pp.464-469
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    • 2002
  • In this research, nonvisibility and robustness of image watermarking mixed Key and Logo method were evaluated. The role of the Key was performed by a personal ID of a copyrighter and the logo images were used as the watermark. The standard image of Lena was used for experimental image and binary images of `Park'with size 32${\times}$32 and 64${\times}$64 were used for the watermark, respectively In order to evaluate nonvisibility of the proposed watermarking scheme, PSNR(Peak Signal to Noise Ratio) of the watermarked image was obtained and for robustness reconstructive rates of the reconstructed watermark were obtained from the watermarked image with image transformation of JPEG lossy compression. The experimental results show that nonvisibility is excellent as PSNR of the watermarked image is 93.75dB and the reconstructive rates of the case of 322${\times}$32 watermark was better than the case of the 64${\times}$64 watermark; average 5.9%, 13.9%, 6.5%, and 4.2% in the case of scale-down rates, rotational rates, impulse noise power density, and JPEG lossy compression rates, respectively.