• Title/Summary/Keyword: Denoising

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Image Denoising via Fast and Fuzzy Non-local Means Algorithm

  • Lv, Junrui;Luo, Xuegang
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1108-1118
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    • 2019
  • Non-local means (NLM) algorithm is an effective and successful denoising method, but it is computationally heavy. To deal with this obstacle, we propose a novel NLM algorithm with fuzzy metric (FM-NLM) for image denoising in this paper. A new feature metric of visual features with fuzzy metric is utilized to measure the similarity between image pixels in the presence of Gaussian noise. Similarity measures of luminance and structure information are calculated using a fuzzy metric. A smooth kernel is constructed with the proposed fuzzy metric instead of the Gaussian weighted L2 norm kernel. The fuzzy metric and smooth kernel computationally simplify the NLM algorithm and avoid the filter parameters. Meanwhile, the proposed FM-NLM using visual structure preferably preserves the original undistorted image structures. The performance of the improved method is visually and quantitatively comparable with or better than that of the current state-of-the-art NLM-based denoising algorithms.

A Study on Real-time Data Acquisition System and Denoising for Energy Saving Device (에너지 절약 장치용 실시간 데이터 획득 시스템 구현과 잡음제거에 관한 연구)

  • Huh, Keol;Choi, Yong-Kil;Jeong, Won-Kyo;Hoang, Chan-Ku
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • pp.47-53
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    • 2004
  • The paper shows that the combination of the hardware, NI PCI 6110E board and the software, Fourier and continuous wavelet transform(CWT) can be used to implement for extracting the important features of the real-time signal. The results confirmed that CWT produces the fast computation enough for the application of the real-time signal processing except the negligible time delay. In denoising case, because of the lack of translation invariance of wavelet basis, traditional wavelet thresholding leads to pseudo-Gibbs phenomena in the vicinity of discontinuities of signal. In this paper, in order to reduce the pseudo-Gibbs phenomena, wavelet coefficients are threshold and reconstruction algorithm is implement through shift-invariant gibbs free denoising algorithm based on wavelet transform footprint. The proposed algorithm can potentially be extended to more general signals like piecewise smooth signals and represents an effective solution to problems like signal denoising.

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Denoising Algorithm using Wavelet (웨이브렛을 이용한 잡음 제거 알고리즘)

  • 배상범;김남호
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.8
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    • pp.1139-1145
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    • 2002
  • Wavelet transformed data can filter signal with each frequency band, because it includes detail information about original signal. Therefore, in this paper, important two noises were removed by wavelet. About AWGN environment UDWT(undecimated discrete wavelet transform), applying hard-threshold, was used and about impulse noise environment, it can be possible to recognize edge of original signal as well as superior denoising effect by using two methods, denoising by threshold and slope of signal by wavelet. SNR was used as a judgemental criterion of a denoising effect and Blocks and DTMF(dual tone multi frequency) were used as a test signal.

A Study on Denoising Method using Wavelet in Impulse Noise Environment (임펄스 노이즈 환경에서 웨이브렛을 이용한 노이즈 제거 방법에 관한 연구)

  • 배상범;김남호
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.4
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    • pp.513-518
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    • 2002
  • This paper presents the new method for removing impulse noise using wavelet. Time and frequency-localization capabilities in denoising can provide excellent specialties comparing with the existing methods, because of including detail information of signal. The method in this paper, using denoising by threshold and slope of signal by wavelet, has superior denoising effect and can recognize edge of original signal. For objective judgement, the test signals are used HeaviSine and DTMF and this paper simulated by test signals which have added to impulse noise of different site individually.

Denoising of Speech Signal Using Wavelet Transform (웨이브렛 변환을 이용한 음성신호의 잡음제거)

  • 한미경;배건성
    • The Journal of the Acoustical Society of Korea
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    • v.19 no.5
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    • pp.27-34
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    • 2000
  • This paper deals with speech enhancement methods using the wavelet transform. A cycle-spinning scheme and undecimated wavelet transform are used for denoising of speech signals, and then their results are compared with that of the conventional wavelet transform. We apply soft-thresholding technique for removing additive background noise from noisy speech. The symlets 8-tap wavelet and pyramid algorithm are used for the wavelet transform. Performance assessments based on average SNR, cepstral distance and informal subjective listening test are carried out. Experimental results demonstrate that both cycle-spinning denoising(CSD) method and undecimated wavelet denoising(CWD) method outperform conventional wavelet denoising(UWD) method in objective performance measure as welt as subjective listening test. The two methods also show less "clicks" that usually appears in the neighborhood of signal discontinuities.

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Image Denoising of Human Visual Filter Using GCST (GCST를 이용한 인간시각필터의 영상 잡음 제거)

  • Lee, Juck-Sik
    • Journal of the Institute of Convergence Signal Processing
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    • v.9 no.4
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    • pp.253-260
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    • 2008
  • Image denoising as one of image enhancement methods has been studied a lot in the spatial and transform domain filtering. Recently wavelet transform which has an excellent energy compaction and a property of multiresolution has widely used for image denoising. But a transform based on human visual system is visually useful if an end user is human beings. Therefore, Gabor cosine and sine transform which is considered as human visual filter is applied to image denoising areas in this paper. Denoising performance of the proposed transform is compared with those of the derivatives of Gaussian transform being another human visual filter and of discrete wavelet transform in terms of PSNR. With three levels of various noises, experimental results for real images show that the proposed transform has better PSNR performance of 0.41dB than DWT and 0.14dB than DGT.

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A study on non-local image denoising method based on noise estimation (노이즈 수준 추정에 기반한 비지역적 영상 디노이징 방법 연구)

  • Lim, Jae Sung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.5
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    • pp.518-523
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    • 2017
  • This paper proposes a novel denoising method based on non-local(NL) means. The NL-means algorithm is effective for removing an additive Gaussian noise, but the denoising parameter should be controlled depending on the noise level for proper noise elimination. Therefore, the proposed method optimizes the denoising parameter according to the noise levels. The proposed method consists of two processes: off-line and on-line. In the off-line process, the relations between the noise level and the denoising parameter of the NL-means filter are analyzed. For a given noise level, the various denoising parameters are applied to the NL-means algorithm, and then the qualities of resulting images are quantified using a structural similarity index(SSIM). The parameter with the highest SSIM is chosen as the optimal denoising parameter for the given noise level. In the on-line process, we estimate the noise level for a given noisy image and select the optimal denoising parameter according to the estimated noise level. Finally, NL-means filtering is performed using the selected denoising parameter. As shown in the experimental results, the proposed method accurately estimated the noise level and effectively eliminated noise for various noise levels. The accuracy of noise estimation is 90.0% and the highest Peak Signal-to-noise ratio(PSNR), SSIM value.

Efficient Image Denoising Method Using Non-local Means Method in the Transform Domain (변환 영역에서 Non-local Means 방법을 이용한 효율적인 영상 잡음 제거 기법)

  • Kim, Dong Min;Lee, Chang Woo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.10
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    • pp.69-76
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    • 2016
  • In this paper, an efficient image denoising method using non-local means (NL-means) method in the transform domain is proposed. Survey for various image denoising methods has been given, and the performances of the image denoising method using NL-means method have been analyzed. We propose an efficient implementation method for NL-means method by calculating the weights for NL-means method in the DCT and LiftLT transform domain. By using the proposed method, the computational complexity is reduced, and the image denoising performance improves by using the characteristics of images in the tranform domain efficiently. Moreover, the proposed method can be applied efficiently for performing image denoising and image rescaling simultaneously. Extensive computer simulations show that the proposed method shows superior performance to the conventional methods.

Index-based Boundary Matching Supporting Partial Denoising for Large Image Databases

  • Kim, Bum-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.10
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    • pp.91-99
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    • 2019
  • In this paper, we propose partial denoising boundary matching based on an index for faster matching in very large image databases. Attempts have recently been made to convert boundary images to time-series with the objective of solving the partial denoising problem in boundary matching. In this paper, we deal with the disk I/O overhead problem of boundary matching to support partial denoising in a large image database. Although the solution to the problem superficially appears trivial as it only applies indexing techniques to boundary matching, it is not trivial since multiple indexes are required for every possible denoising parameters. Our solution is an efficient index-based approach to partial denoising using $R^*-tree$ in boundary matching. The results of experiments conducted show that our index-based matching methods improve search performance by orders of magnitude.

An Index-Building Method for Boundary Matching that Supports Arbitrary Partial Denoising (임의의 부분 노이즈제거를 지원하는 윤곽선 매칭의 색인 구축 방법)

  • Kim, Bum-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.11
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    • pp.1343-1350
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    • 2019
  • Converting boundary images to time-series makes it feasible to perform boundary matching even on a very large image database, which is very important for interactive and fast matching. In recent research, there has been an attempt to perform fast matching considering partial denoising by converting the boundary image into time series. In this paper, to improve performance, we propose an index-building method considering all possible arbitrary denoising parameters for removing arbitrary partial noises. This is a challenging problem since the partial denoising boundary matching must be considered for all possible denoising parameters. We propose an efficient single index-building algorithm by constructing a minimum bounding rectangle(MBR) according to all possible denoising parameters. The results of extensive experiments conducted show that our index-based matching method improves the search performance up to 46.6 ~ 4023.6 times.