• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2928-2947
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• 2015

Adaptive Gaussian filter (AGF) is a recently developed switching filter to remove salt and pepper noise. AGF first directly identifies pixels of gray levels 0 and 255 as noise pixels, and then only restored noise pixels using a Gaussian filter with adaptive variance based on the estimated noise density. AGF usually achieves better denoising effect in comparison with other filters. However, AGF still fails to obtain good denoising effect on images with noise-free pixels of gray levels 0 and 255, due to its severe false alarm in its noise detection stage. To alleviate this issue, a modified version of AGF is proposed in this paper. Specifically, the proposed filter first performs noise detection via an image block based noise density estimation and sequential noise density guided rectification on the noise detection result of AGF. Then, a modified Gaussian filter with adaptive variance and window size is used to restore the detected noise pixels. The proposed filter has been extensively evaluated on two representative grayscale images and the Berkeley image dataset BSDS300 with 300 images. Experimental results showed that the proposed filter achieved better denoising effect over the state-of-the-art filters, especially on images with noise-free pixels of gray levels 0 and 255.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.27-33
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• 2016

In this paper, we propose the bilateral filter based on median value that can reduce random noise and impulse noise with minimal loss of contour information. In general, EO / IR camera to generate a random or impulse noise due to a number of reasons. This noise reduces the performance of detecting and tracking by signal processing. To reduce noise, our proposed bilateral filter sorts the values of the target pixel and the peripheral pixels, and extracts a median filter coefficients of the Gaussian type. Then to extract the Gaussian filter coefficient involved with the distance between the center pixel and the surrounding pixels. As using those filter coefficients, our proposed method can remove the various noise effectively while minimizing the loss of the contour information. To validate our proposed method, we present experimental results for several IR images.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.50 no.3
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• pp.130-137
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• 2001

In this paper, we propose a new Active Noise Filter Control System which operate as a control performance when a adaptive filter fault. In this system, half-fixed filter which is new filter, connected to parallel with adaptive filter. An adaptive filler use to continuous parameter estimating, but adaptive filter is fault, half-fixed filter update newly data which is continuous estimating date each during sampling period. We simulate and apply the proposed active noise filter system to in the cylinder type duct. Experimental results show that proposed Active Noise Filter Control System has better control performance than existing filter which Eriksson's or Parallel Filter System in term of noise reduction.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.308-318
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• 2022

Noise is a serious issue. While sending images via electronic communication, Impulse noise, which is created by unsteady voltage, is one of the most common noises in digital communication. During the acquisition process, pictures were collected. It is possible to obtain accurate diagnosis images by removing these noises without affecting the edges and tiny features. The New Average High Noise Density Median Filter. (HNDMF) was proposed in this paper, and it operates in two steps for each pixel. Filter can decide whether the test pixels is degraded by SPN. In the first stage, a detector identifies corrupted pixels, in the second stage, an algorithm replaced by noise free processed pixel, the New average suggested Filter produced for this window. The paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. In this paper the comparison of known image denoising is discussed and a new decision based weighted median filter used to remove impulse noise. Using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structure Similarity Index Method (SSIM) metrics, the paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. A detailed simulation process is performed to ensure the betterment of the presented model on the Mini-MIAS dataset. The obtained experimental values stated that the HNDMF model has reached to a better performance with the maximum picture quality. images affected by various amounts of pretend salt and paper noise, as well as speckle noise, are calculated and provided as experimental results. According to quality metrics, the HNDMF Method produces a superior result than the existing filter method. Accurately detect and replace salt and pepper noise pixel values with mean and median value in images. The proposed method is to improve the median filter with a significant change.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.135-140
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• 2013

Noise estimation and detection algorithm to adapt quickly to changing noise environment using the LMS Filter. However, the LMS Filter for noise estimation for a certain period of time and need time to adapt. If the signal changes occur, have the disadvantage of being more adaptive time-consuming. Therefore, noise removal method is proposed to a frame basis AELMS Filter to compensate. In this paper, we split the input signal on a frame basis in noisy environments. Remove the LMS Filter by configuring noise predictions using the mean and variance. Noise, even if the environment changes fast adaptation time to remove the noise. Remove noise and environmental noise and speech input signal is mixed to maintain the unique characteristics of the voice is a way to reduce the damage of voice information. Noise removal method using a frame basis AELMS Filter To evaluate the performance of the noise removal. Experimental results, the attenuation obtained by removing the noise of the changing environment was improved by an average of 6.8dB.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.133-139
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• 2011

In this paper, we propose a hybrid filter for noise reduction. The proposed method adjusts rational filtering direction according to an edge in the image using median filtered data. Rational filter modulates the coefficients of a linear lowpass filter to limit its action in presence of image details. By the ratio of polynomials in the input variables, rational filter reduces noise adaptively. Median filter is widely used to reduce impulse noise, but removes some details for highly corrupted images. Also, desirable details are removed when the window size is large. Our proposed algorithm combines rational filter and median filter. Thus, proposed method not only preserves edge, but also reduces noise in uniform region. Experimental results show that our proposed method has better quality than those by existing median and rational filtering methods.

• Journal of radiological science and technology
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• v.30 no.4
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• pp.329-334
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• 2007

This paper is for investigation of the noise reduction effect all 20 filters by combining Low Pass Filter(LPF) 5 kinds, High Pass Filter(HPF) 4 kinds, Median Filter(MF) 11 kinds. Noise is added to reduce noise and minimize the quality degradation in medical imaging system. We also compared Peak Signal to Noise Ratio(PSNR), Mean Square Error(MSE) for all the combinations of different filters. As a result, noise decrease appeared in the LPF3*3#1 + HPF3*3#1 + Vertical3*1 of highest filter. We confirmed noise reduction effect by applying the proposed filter combination in many fields of medical imaging applications.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.379-396
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• 2018

Purpose: The purpose of this study was to propose a standard form of noise filter drawing, which is widely used in the field of weapon systems, to define the essential specification which is not standardized at the existing drawings and to employ the reference for manufacturing and qualification test. Methods: To do that, it identifies the improvements to analyze 19 noise filter drawings, studies the principle of noise filtering to find the essential part of the spec. and reviews the MIL-STD-220C and KS IEC 60939, which is the widely used as a formal spec. pertaining to the noise filter. Throughout the study, a standard form is developed to standardize the attenuation characteristics and find eight crucial metrics to specify the noise filter. Results: The results of this study are as follows; The standardized drawings can be used as the qualification test of the item and the manufacturing and engineering documents to make the noise filter, which are also applicable to the reference document to review KDS(Korea Defense Standard) drawings.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.233-236
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• 2005

Phase noise in a phase-locked-loop (PLL) is unwanted and unavoidable. It is a main concern in oscillation system especially PLL. The phase noise is derived in term of power spectrum density by using a reliable phase noise model. There are four noise sources being considered in this paper, which are generated by reference oscillator, voltage controlled oscillator, filter, and main divider. The major concern for this paper is the noise from the filter. Two types of second order low pass filter are used in the PLL system. Applying the mathematical phase noise model, the output noises are compared. The total noise from the passive filter is lower than the active filter at the offset frequency range between 1 Hz to 33 kHz.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.173-180
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• 2003

The modified Wiener filtering method is proposed for effective noise suppression in edge region of images corrupted by additive white gaussian noise. Although the pixels classified as a edge region in the conventional Wiener filter have lots of noise components, the conventional Wiener filler cannot remove noise effectively due to the preserving of edges. To reduce noise well in edge region, we modify filter coefficients of the conventional Wiener filter The modified filter coefficients increase in noise suppression effect In edge region, while they preserve edges for strong edge region. From simulation $(256{\time}256$ size, 256 graylevel images) filtered images by the proposed method show much improved subjective image quality with some improved peak signal-to-noise ratio compared to those by the conventional Wiener filtering.