• Journal of information and communication convergence engineering
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• 제9권5호
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• pp.591-596
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• 2011

Image denoising is a key issue in all image processing researches. Generally, the quality of an image could be corrupted by a lot of noise due to the undesired conditions of image acquisition phase or during the transmission. Many approaches to image restoration are aimed at removing either Gaussian or impulse noise. Nevertheless, it is possible to find them operating on the same image, which is called mixed noise and it produces a hard damage. In this paper, we proposed noise type classification method and a mixed nonlinear filter for mixed noise suppression. The proposed filtering scheme applies a modified adaptive switching median filter to impulse noise suppression and an efficient nonlinear filer was carried out to remove Gaussian noise. The simulation results based on Matlab show that the proposed method can remove mixed Gaussian and impulse noise efficiently and it can preserve the integrity of edge and keep the detailed information.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제26권3호
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• pp.156-184
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• 2022

In this article, we propose a novel variational model for restoring color images corrupted by mixed multiplicative Gamma noise and additive Gaussian noise. The model involves a data-fidelity term that characterizes the mixed noise as an infimal convolution of two noise distributions and the saturation-value total variation (SVTV) regularization. The data-fidelity term facilitates suitable separation of the multiplicative Gamma and Gaussian noise components, promoting simultaneous elimination of the mixed noise. Furthermore, the SVTV regularization enables adequate denoising of homogeneous regions, while maintaining edges and details and diminishing the color artifacts induced by noise. To solve the proposed nonconvex model, we exploit an alternating minimization approach, and then the alternating direction method of multipliers is adopted for solving subproblems. This contributes to an efficient iterative algorithm. The experimental results demonstrate the superior performance of the proposed model compared to other existing or related models, with regard to visual inspection and image quality measurements.

• Journal of Information Processing Systems
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• 제14권2호
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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.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2011년도 추계학술대회
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• pp.379-381
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• 2011

The image signal is often affected by the existence of noise, noise can occur during image capture, transmission or processing phases. noises caused the degradation phenomenon and demage the original signal information. Many studies are being accomplished to restore those signals which corrupted by mixed noise. In this paper, we proposed mixed weighted filter for removing Gaussian and impulse noise. we first charge the noise type, then, Gaussian is removed by a weighted mean filter and impulse noise is removed by self-adaptive weighted median filter that can not only remove mixed noise but also preserve the details. And through the simulation, we compared with the conventional algorithms and indicated that proposed method significant improvement over many other existing algorithms and can preserve image details efficiently.

• Journal of information and communication convergence engineering
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• 제14권4호
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• pp.268-271
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• 2016

An efficient inductive switching noise suppression technique for mixed-signal integrated circuits (ICs) using standard CMOS digital technology is proposed. The proposed design technique uses a parallel RC circuit, which provides a damping path for the switching noise. The proposed design technique is used for designing a mixed-signal circuit composed of a ring oscillator, a digital output buffer, and an analog noise sensor node for $0.13-{\mu}m$ CMOS digital IC technology. Simulation results show a 47% reduction in the on-chip inductive switching noise coupling from the noisy digital to the analog blocks in the same substrate without an additional propagation delay. The increased power consumption due to the damping resistor is only 67% of that of the conventional source damping technique. This design can be widely used for any kind of analog and high frequency digital mixed-signal circuits in CMOS technology

• Industrial Engineering and Management Systems
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• 제4권2호
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• pp.165-175
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• 2005

Two extreme and one mixed procedures for designing a noise hazard prevention program are discussed in this paper. The two extreme design procedures (engineering-based and HPD-based) yield upper and lower bounds of the total noise control cost, respectively; while the mixed design procedure provides an optimal noise hazard prevention program within a given total budget. The upper bound of the workforce size for job rotation is approximated using a heuristic procedure. Six optimization models are developed and utilized by the mixed procedure to eliminate or reduce excessive noise levels (or noise exposures) in an industrial workplace. The mixed procedure also follows the OSHA’s hierarchy of noise control. A numerical example is given to demonstrate the application of the proposed design procedures.

• 융합신호처리학회논문지
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• 제13권2호
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• pp.63-69
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• 2012

Noise is regarded as an unwanted component of the image because it significantly reduces image quality. And image is often corrupted by mixed noise. In this paper an efficient modified weighted filter algorithm which combines spatial weight and intensity weight is proposed for removing mixed noise. In the proposed method, the filtering mask is separated into the four sub-windows and the parameters of the weights are confirmed by calculating local standard deviation and the mean of four sub-windows' standard deviations. Considering the spatial information and intensity information, the proposed method has good performance on not only noise elimination but also preservation of details. Simulation results demonstrate that the proposed method performs better than conventional algorithms.

• 한국음향학회지
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• 제29권3호
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• pp.200-208
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• 2010

본 논문에서는 배경잡음에 강인한 잡음제거 알고리즘 설계를 위해서 minimum statistics (MS) 기법을 codebook driven short-term predictor parameter estimation (CDSTP) 기법에 접목하는 방법을 제안한다. MS는 stationary 배경잡음에는 강인하지만, non-stationary 배경잡음에는 상대적으로 취약하다. CDSTP는 non-stationary 배경잡음에 강인한 특성을 보이지만, 코드북에 없는 배경잡음 환경에는 취약하다. 따라서 non-stationary 배경잡음에 강인한 CDSTP 방법과 별도의 코드북 학습 과정이 필요 없는 MS를 결합해서 다양한 배경잡음에 강인한 알고리즘을 제안한다. 제안방법은 MS나 CDSTP 방법에 비해서 전체적으로 향상된 perceptual evaluation of speech quality (PESQ) 성능을 나타냈으며, 특히 stationary 배경잡음과 non-stationary 배경잡음이 섞여 있는 mixed 배경잡음 환경에서 강인한 특성을 보였다.

• Journal of information and communication convergence engineering
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• 제9권3호
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• pp.336-340
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• 2011

Many approaches to image restoration are aimed at removing either gauss or impulse noise. This is because both types of degradation processes are distinct in nature, and hence they are easier to manage when considered separately. Nevertheless, it is possible to find them operating on the same image, which produces a hard damage. This happens when an image, already contaminated by Gaussian noise in the image acquisition procedure, undergoes impulsive corruption during its digital transmission. Here we proposed an algorithm first judge the type of the noise according to the difference values of pixel's neighborhood region and impulse noise's characteristic. Then removes the gauss noise by modified weighted mean filter and removes the impulse noise by modified nonlinear filter. The result of computer simulation on test images indicates that the proposed method is superior to traditional filtering algorithms. The proposed method can not only remove mixed noise effectively, but also preserve image details.

• 한국정보통신학회논문지
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• 제23권3호
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• pp.254-260
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• 2019

최근 다양한 분야에서 영상매체의 사용 빈도가 증가함에 따라 신호처리의 중요성이 높아지고 있다. 하지만 송수신 과정에서 많은 종류의 잡음이 발생하며 신호의 정보에 영향을 미치고 있으며, 이러한 이유로 잡음 제거를 전처리 과정으로서 필수적으로 행한다. 본 논문에서는 임펄스 잡음과 AWGN이 혼합된 잡음을 제거하기 위한 알고리즘을 제안하였다. 제안한 알고리즘은 복합 잡음 환경에서 효율적인 잡음 제거를 위해 잡음 판단을 통해 영상 복원을 진행하며, 공간적 특성과 화소 변화를 고려하여 잡음을 제거한다. 시뮬레이션 결과 제안한 알고리즘은 기존 방법과 달리 두 잡음의 영향을 모두 최소화하여 잡음을 제거하여 우수한 잡음제거 특성을 나타내었으며, 객관적인 판단을 위해 PSNR 및 프로파일 등을 이용하여 비교 및 분석하였다.