• 제목, 요약, 키워드: Denoising

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An Effective Denoising Method for Images Contaminated with Mixed Noise Based on Adaptive Median Filtering and Wavelet Threshold Denoising

  • Lin, Lin
    • Journal of Information Processing Systems
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    • v.14 no.2
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    • pp.539-551
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    • 2018
  • Images are unavoidably contaminated with different types of noise during the processes of image acquisition and transmission. The main forms of noise are impulse noise (is also called salt and pepper noise) and Gaussian noise. In this paper, an effective method of removing mixed noise from images is proposed. In general, different types of denoising methods are designed for different types of noise; for example, the median filter displays good performance in removing impulse noise, and the wavelet denoising algorithm displays good performance in removing Gaussian noise. However, images are affected by more than one type of noise in many cases. To reduce both impulse noise and Gaussian noise, this paper proposes a denoising method that combines adaptive median filtering (AMF) based on impulse noise detection with the wavelet threshold denoising method based on a Gaussian mixture model (GMM). The simulation results show that the proposed method achieves much better denoising performance than the median filter or the wavelet denoising method for images contaminated with mixed noise.

A REVIEW ON DENOISING

  • Jung, Yoon Mo
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.18 no.2
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    • pp.143-156
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    • 2014
  • This paper aims to give a quick view on denoising without comprehensive details. Denoising can be understood as removing unwanted parts in signals and images. Noise incorporates intrinsic random fluctuations in the data. Since noise is ubiquitous, denoising methods and models are diverse. Starting from what noise means, we briefly discuss a denoising model as maximum a posteriori estimation and relate it with a variational form or energy model. After that we present a few major branches in image and signal processing; filtering, shrinkage or thresholding, regularization and data adapted methods, although it may not be a general way of classifying denoising methods.

수중 음향 측정을 위한 새로운 임계치 함수에 의한 TI 웨이블렛 잡음제거 기법 (Translation-invariant Wavelet Denoising Method Based on a New Thresholding Function for Underwater Acoustic Measurement)

  • 최재용
    • 한국소음진동공학회논문집
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    • v.16 no.11
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    • pp.1149-1157
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    • 2006
  • Donoho et al. suggested a wavelet thresholding denoising method based on discrete wavelet transform. This paper proposes an improved denoising method using a new thresholding function based on translation-invariant wavelet for underwater acoustic measurement. The conventional wavelet thresholding denoising method causes Pseudo-Gibbs phenomena near singularities due to the lack of translation-invariant of the wavelet basis. To suppress Pseudo-Gibbs phenomena, a denoising method combining a new thresholding function based on the translation-invariant wavelet transform is proposed in this paper. The new thresholding function is a modified hard-thresholding to each node according to the discriminated threshold so as to reject unknown external noise and white gaussian noise. The experimental results show that the proposed method can effectively eliminate noise, extract characteristic information of radiated noise signals.

디모자이킹을 위한 Wiener Filter 기반의 디노이징 알고리듬 (Wiener Filter Based Denoising Algorithm for Demosaicking)

  • 이록규;정제창
    • 한국통신학회논문지
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    • v.36 no.5C
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    • pp.286-294
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    • 2011
  • 다지털 카메라의 mosaicked image는 Bayer CFA 등의 센서를 통해 획득되며 full resolution의 컬러 영상을 얻기 위해서는 demosaicking이라는 과정이 요구된다. 그러나 시그널이 센서를 통과할 때 noise가 더해지게 되기 때문에 이를 제거하기 위한 denoising process는 demosaicking 과정 전단에 반드시 고려되어야 하는 것이다. 본 논문에서는 demosaicking과 denoising을 분석하고 효율적으로 noise를 제거하는 방식을 제안한다. 제안된 알고리듬은 noiseless CFA에서 얻어지는 필터를 수정함으로서 얻어지며, 낮은 연산량과 함께 만족할만한 성능을 보여준다. CPSNR, SCIELAB, FSIM로 대표되는 화질 측정 방식들은 제안하는 알고리듬이 다양한 레벨의 noise를 효율적으로 제거한다는 것을 보여준다.

Wavelet-based Image Denoising with Optimal Filter

  • Lee, Yong-Hwan;Rhee, Sang-Burm
    • Journal of Information Processing Systems
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    • v.1 no.1
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    • pp.32-35
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    • 2005
  • Image denoising is basic work for image processing, analysis and computer vision. This paper proposes a novel algorithm based on wavelet threshold for image denoising, which is combined with the linear CLS (Constrained Least Squares) filtering and thresholding methods in the transform domain. We demonstrated through simulations with images contaminated by white Gaussian noise that our scheme exhibits better performance in both PSNR (Peak Signal-to-Noise Ratio) and visual effect.

Wavelet Denoising Filter를 이용한 측위 정밀도 향상 기법 성능 (A Performance of Positioning Accuracy Improvement Scheme using Wavelet Denoising Filter)

  • 신동수;박지호;박영식;황유민;김진영
    • 한국위성정보통신학회논문지
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    • v.9 no.3
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    • pp.9-14
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    • 2014
  • 최근, 현대전은 GPS 위치측위를 바탕으로 정밀타격체계 및 미사일 방어체계가 핵심이 되어가고 있다. 하지만 군 환경 특성상 산악지형 및 시가전에서의 지형지물로 인한 large/small scale fading, 주파수 간섭 등으로 인해 오차를 가진 위치정보를 얻게 된다. 이는 아군 위치 파악 실패로 인한 지원 지연 및 유도탄 오폭으로 인명피해를 발생시키게 된다. 본 연구는 위치오차를 보정하기 위해 wavelet denoising filter를 이용한 간섭완화 측위기법을 제안한다. 실험 결과는 본 연구실에서 수행한 GPS/QZSS/Wi-Fi밀결합 측위 기법의 실증 테스트 결과와 wavelet denoising filter를 적용한 시스템의 시뮬레이션 결과로 간섭완화 성능을 나타낸다. Wavelet denoising filter를 적용한 시스템의 시뮬레이션 결과는 기존 GPS보다 평균 21.6% 의 정확도 향상을 보이며 제안한 시스템 모델의 우수성을 입증한다.

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

  • 한미경;배건성
    • 한국음향학회지
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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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Design and Implementation of a Boundary Matching System Supporting Partial Denoising for Large Image Databases

  • Kim, Bum-Soo;Kim, Jin-Uk
    • 한국컴퓨터정보학회논문지
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    • v.24 no.5
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    • pp.35-40
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    • 2019
  • In this paper, we design and implement a partial denoising boundary matching system using indexing techniques. Converting boundary images to time-series makes it feasible to perform a fast search using indexes even on a very large image database. Thus, using this converting method we develop a client-server system based on the previous partial denoising research in the GUI(graphical user interface) environment. The client first converts a query image given by a user to a time-series and sends denoising parameters and the tolerance with this time-series to the server. The server identifies similar images from the index by evaluating a range query, which is constructed using inputs given from the client and sends the resulting images to the client. Experimental results show that our system provides many intuitive and accurate matching results.

영상 잡음 제거에서의 디테일 향상을 위한 심층 신경망 (Deep Network for Detail Enhancement in Image Denoising)

  • 김성준;정용주
    • 한국멀티미디어학회논문지
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    • v.22 no.6
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    • pp.646-654
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    • 2019
  • Image denoising is considered as a key factor for capturing high-quality photos in digital cameras. Thus far, several image denoising methods have been proposed in the past decade. In addition, previous studies either relied on deep learning-based approaches or used the hand-crafted filters. Unfortunately, the previous method mostly emphasized on image denoising regardless of preserving or recovering the detail information in result images. This study proposes an detail extraction network to estimate detail information from a noisy input image. Moreover, the extracted detail information is utilized to enhance the final denoised image. Experimental results demonstrate that the proposed method can outperform the existing works by a subjective measurement.

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.