Impulsive Modelling of Noise for OFDM Systems in Power Line Communication: A Necessity or a Redundant Task?

Selva Muratoğlu Çürük 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.1

In Power Line Communication, variations in the characteristics of power lines and additive noise reduce the efciency of Orthogonal Frequency Division Multiplexing (OFDM), and that makes channel estimation essential. The earlier estimation techniques in the literature assume channel noise is Gaussian as in the wireless communication, whereas the recent ones model the corrupted noise more realistic, impulsive, which results in complicated receivers. This study judges the need of impulsive noise modelling and complex receivers. The performances of two Maximum A-Posteriori (MAP) channel estimators proposed for additive Gaussian noise and impulsive noise are compared under impulsive noise. The channel data used in the simulations is taken from the literature and impulsive noise is modelled by Middleton Class A distribution. The results show that the MAP estimator, which assumes Gaussian noise instead of impulsive, has better performance. The MAP estimator which assumes impulsive noise has a satisfactory performance under weak impulsive noise and low Signal to Noise Ratio (SNR) only, otherwise its performance is low, close to Maximum Likelihood estimator performance. The estimator designed for Gaussian noise has a better performance even under heavy impulsive noise and this distinction is clearer for low SNR cases.

A Study on Image Restoration Algorithm in Random-Valued Impulse Noise Environment

Yinyu, Gao,Kim, Nam-Ho The Korea Institute of Information and Commucation 2011 Journal of information and communication convergen Vol.9 No.3

Digital images are often corrupted by impulse noise, and it is very important to remove random-valued impulse noise. Cleaning such noise is far more difficult than cleaning salt and pepper impulse noise. In this paper, we proposed an efficient way to remove random-valued impulse noise from digital images. This novel method comprises two stages. The first stage is to detect the random-valued impulse noise in the image and the pixels are roughly divided into two classes, which are "noise-free pixel" and "noise pixel". Then, the second stage is to eliminate the random-valued impulse noise from the image. In this stage, only the "noise pixels" are processed. The "noise-free pixels" are copied directly to the output image. Simulation results indicated that our method provides a significant improvement over many other existing algorithms.

잡음 검출기와 총변량 최적화를 이용한 영상의 임펄스 잡음제거

이임건 한국콘텐츠학회 2006 한국콘텐츠학회논문지 Vol.6 No.4

A new algorithm for removing salt and pepper impulse noise in image using impulse noise detector and total variation optimization is presented. The proposed two types of noise detectors which are based on the adaptive median filter, can detect impulse noise with high accuracy while reducing the probability of detecting image details as impulses. And the detectors maintain its performance independent of noise density. For removing impulses, total variation optimization is applied only to those detected noise candidate to reduces unnecessary computation. The proposed approach successfully remove impulse noise while preserving image details. 본 논문에서는 두 가지 새로운 임펄스 잡음 검출기를 설계하고 총변량(total variation) 최적화를 통하여 영상에 존재하는 임펄스 잡음을 제거하는 방법을 제안한다. 설계된 임펄스 잡음 검출기는 적응 미디언 필터(AMF:Adaptive Median Filter)를 기반으로 하고 있으며 기존의 검출기에 비해 잡음검출의 정확도가 높고 영상의 디테일 정보를 잡음으로 오인하는 확률을 줄였다. 또한 제안하는 검출기는 잡음발생 확률에 무관하게 우수한 성능을 유지한다. 영상에서의 잡음제거는 제안된 검출기에 의해 얻어진 잡음후보 화소에 대해서만 총변량 최적화를 적용하므로 불필요한 계산을 줄이고 영상의 경계선을 잘 보존하면서 잡음을 제거할 수 있다. 실험결과 제안하는 2단 구조의 잡음제거 알고리즘은 다양한 형태의 잡음 밀도에 대해서 기존의 알고리즘에 비해 약 2dB 정도의 화질개선 효과를 얻었다.

A Mixed Nonlinear Filter for Image Restoration under AWGN and Impulse Noise Environment

Gao, Yinyu,Kim, Nam-Ho The Korea Institute of Information and Commucation 2011 Journal of information and communication convergen Vol.9 No.5

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.

Neural-network-based Impulse Noise Removal Using Group-based Weighted Couple Sparse Representation

( Yongwoo Lee ),( Toan Duc Bui ),( Jitae Shin ),( Byung Tae Oh ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.8

In this paper, we propose a novel method to recover images corrupted by impulse noise. The proposed method uses two stages: noise detection and filtering. In the first stage, we use pixel values, rank-ordered logarithmic difference values, and median values to train a neural-network-based impulse noise detector. After training, we apply the network to detect noisy pixels in images. In the next stage, we use group-based weighted couple sparse representation to filter the noisy pixels. During this second stage, conventional methods generally use only clean pixels to recover corrupted pixels, which can yield unsuccessful dictionary learning if the noise density is high and the number of useful clean pixels is inadequate. Therefore, we use reconstructed pixels to balance the deficiency. Experimental results show that the proposed noise detector has better performance than the conventional noise detectors. Also, with the information of noisy pixel location, the proposed impulse-noise removal method performs better than the conventional methods, through the recovered images resulting in better quality.

에지정보를 고려한 복합잡음 제거를 위한 영상복원에 관한 연구

김남호,Kim, Nam-Ho 한국정보통신학회 2011 한국정보통신학회논문지 Vol.15 No.10

영상신호를 처리하는 과정에서 잡음에 의해 영상의 열화가 발생하고 있으며, 가우시안 잡음과 임펄스 잡음이 중첩되어 생성된 복합잡음에 의해 훼손되는 경우가 많다. 따라서 본 논문에서는 에지정보를 고려하며 임펄스 잡음과 AWGN(additive white gaussian noise) 잡음이 중첩된 복합잡음을 제거하는 알고리즘을 제안하였다. 제안한 알고리즘은 먼저 잡음의 종류를 판단과정을 거친 후, 그 결과가 AWGN이라고 하면 self-adaptive weighted mean 필터를 사용하여 구하여진 값과 마스크 내의 중간값 사이의 평균을 출력으로 한다. 만약 임펄스 잡음이라고 판단 될 경우, 변형된 비선형 필터를 이용하여 처리한다. 그리고 시뮬레이션을 통해 기존의 방법들과 그 성능을 비교하였고 판단 기준으로 PSNR(peak signal to noise ratio)을 사용하였다. 테스트 영상들에 대한 시뮬레이션 결과로부터 제안한 방법은 기존의 방법들보다 잡음제거나 에지보존 등 방면에서 우수한 성능을 나타내었다. In image signal processing, image signal is corrupted by various noises and caused the degradation phenomenon. And Images often corrupted by AWGN(additive white gaussian noise) and impulse noise which called mixed noise. In this paper, the algorithm is proposed to remove mixed noise while keeping edge information. The proposed algorithm first classifies the noise type, if the classify result is AWGN, then the mean of the output after using self-adaptive weighted mean filter and median value will be the outfiltering value. And if the noise type is impulse noise, then the noise is removed by a modified nonlinear filter. Also we compare existing methods through the simulation and using PSNR(peak signal to noise ratio) as the standard of judgement of improvement effect. The result of computer simulation on test images indicates that the proposed method is superior to traditional filtering algorithms.

Efficient Methodology with Grid Configurations for HSI Noise Prediction in Hover

김기로,박수형,박민준,정성남,김창주 한국항공우주학회 2021 International Journal of Aeronautical and Space Sc Vol.22 No.3

Complex and unsteady flow patterns occur around rotating rotor blades owing to the generation of shock waves at the blade tip and interference between the blade and tip wake when the blade rotates at high speeds, thereby resulting in specific noise characteristics. Furthermore, these noise characteristics cause noise pollution in private areas and degrade detectability of helicopters in military applications. Therefore, it is important to accurately analyze noise characteristics around rotor blades. In this study, a novel computational methodology with a chimera wake grid was proposed to efficiently and accurately predict high-speed impulsive (HSI) noise due to the shock wave at the blade tip. The proposed method enables accurate analysis of a complex flow region by overlapping a wake grid in the vicinity of shock waves. A 1/7-scaled UH-1H rotor blade was used to compare and verify the accuracy of HSI noise prediction and computational efficiency. The chimera grid method was applied to the present simulation for considering the blade motion and moving effects. A permeable surface for wrapping the surface of the physical blade was constructed to include quadrupole noise source generated from the control volume, thickness noise source, and loading noise source. Furthermore, the permeable Ffowcs Williams and Hawkings (FW–H) equations were used with the Kirchhoff approach to realize efficient far-field noise prediction. The proposed HSI noise analysis via chimera wake grid indicated that the strength of the shock wave is more precisely predicted, thereby resulting in improved prediction of the HSI noise. The proposed chimera methodology allows efficient noise prediction using a much coarser background grid system.

A New Hybrid Filtering Technique Based on Neighboring Pixels to Remove Impulse Noise from Digital Images

Nirvair Neeru,Lakhwinder Kaur 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.9

This paper proposes a hybrid technique to remove impulse noise from digital images. In this approach the filtering operation is based on 33 neighborhood of pixel under consideration. During filtering, the properties of neighborhood are considered to check whether it is highly corrupted with noise, medium or only itself act as impulse. Based upon these properties a new hybrid technique has been proposed to process the pixel which further uses different schemes. The experiments have been performed at various noise levels on standard images as well as on real images. The results have been evaluated on the basis of metrics like Signal to noise ratio (SNR), Edge preservation index ( EPI), Structure similarity index measure (SSIM), Multi scale structure similarity index measure (MS-SSIM) and Peak signal to noise ratio ( PSNR). From the results, it has been observed that proposed technique has worked efficiently by preserving the edges and fine lines. To demonstrate the effectiveness of proposed technique, the results have also been compared with other well accepted denoising techniques

A New Efficient Impulse Noise Detection based on Rank Estimation

오진성,김유남,Oh, Jin-Sung,Kim, You-Nam The Korea Institute of Convergence Signal Processi 2008 융합신호처리학회 논문지 (JISPS) Vol.9 No.3

In this paper, we present a new impulsive noise detection technique. To remove the impulse noise without detail loss, only corrupted pixels must be filtered. In order to identify the corrupted pixels, a new impulse detector based on rank and value estimations of the current pixel is proposed. Based on the rank and value estimations of the current pixel, the new proposed method provides excellent statistics for detecting an impulse noise while reducing the probability of detecting image details as impulses. The proposed detection is efficient and can be used with any noise removal filter. Simulation results show that the proposed method significantly outperforms many other well-known detection techniques in terms of image restoration and noise detection.

임펄스 잡음 환경에서 고주파 성분을 보존하기 위한 영상 복원 필터

천봉원,김남호 한국정보통신학회 2019 한국정보통신학회논문지 Vol.23 No.4

Noise removal is one of the required step in processing digital video and there are many researches to develop algorithm that fits with its purpose and environment. However, present impulse noise removal methods are lacking in its function in terms of removing noise in edge and high frequency factors. Therefore, this research has Extended range of masks depending on density to determine noise so that high frequency factors can be preserved. The range of resolution is set based on median and standard deviation of inside resolution after removing impulse noise. afterwards, those resolution within the range are calculated by adding weight to have the final output value. The suggested algorithm has an enhanced function in removing noise in various areas with many edge and high frequency factors than present methods and their functions are compared through simulation. 잡음 제거는 디지털 영상처리 과정에서 필수적으로 이루어지며, 다양한 분야에서 그 목적과 환경에 맞는 알고리즘을 개발하기 위해 많은 연구가 진행되고 있다. 그러나 기존 임펄스 잡음 제거 방법들은 영상의 에지 성분 및 고주파 성분의 잡음 제거에 다소 미흡한 성능을 보이고 있다. 따라서 본 논문에서는 고주파 성분을 보존하기 위해 잡음 판단에 따른 잡음 밀도에 따라 마스크의 범위를 확장하였다. 선택된 마스크는 임펄스 잡음을 제외한 내부 화소의 메디안 값과 표준편차를 기준으로 화소 범위가 설정된다. 그리고 화소 범위에 존재하는 화소는 거리에 따른 가중치를 적용하여 최종 출력 계산에 사용하였다. 제안한 알고리즘은 기존 방법에 비해 영상의 에지 부분 및 고주파 성분이 많은 영역에서 잡음 제거성능이 우수하였으며, 시뮬레이션을 통해 성능을 비교하였다.