• Title, Summary, Keyword: 잡음제거

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Noise Reduction of Binary Image in Non-Impulse Noise (비임펄스 잡음이 포함된 이진영상의 잡음제거)

  • 김재석;정성옥;오무송
    • Proceedings of the Korean Information Science Society Conference
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    • pp.511-513
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    • 2002
  • 본 논문에서는 영상에 Salt-Pepper와 같은 임펄스 잡음이 존재하는 영상에 대한 잡음 제거는 기존의 잡음제거 방법인 미디언 필터를 이용하여 잡음을 제거할 수 있지만 임펄스 잡음이 아닌 비임펄스 잡음이 포함된 영상에 대해서는 미디언 필터를 이용하여 비임펄스 잡음이 제거되지 않으므로 임펄스 잡음이 아닌 비임펄스 잡음이 존재하는 영상에 대한 잡음 제거를 형태학적 연산을 이용하여 잡음 제거하는 방법을 제안한다.

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Performance Comparison of Noise Reduction Algorithms for Enhancing Voice Quality based on Telematics (텔레메틱스 기반의 통화음질향상을 위한 잡음제거 알고리즘의 성능비교)

  • Kim, Hyoung-Gook;Choi, Hong-Jae
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.11 no.1
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    • pp.86-91
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    • 2012
  • To provide high voice quality of real-time voice communication based on telematics exposed to various noise environments, the noise reduction algorithm with low computing load is required to effectively remove the noise. In this paper, we propose a noise reduction algorithm based on Mel-Filter and illustrate the proposed algorithm comparing with conventional noise reduction algorithms. As a experimental result that evaluates the performance of the noise reduction algorithms under the car and babble noise environments, the proposed noise reduction algorithm has the lower computing load with the similar PESQ score compared to the conventional noise reduction algorithms. It proves that the proposed noise reduction algorithm can efficiently remove the noise in mobile telematics.

Noise reduction Algorithm for CFA Images (컬러 필터 배열 영상에서의 잡음제거 알고리즘)

  • Lee, Min-Seok;Park, Sang-Wook;Kwon, Ji-Yong;Kang, Moon-Gi
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • pp.67-69
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    • 2010
  • 대부분의 디지털 카메라는 컬러 필터 배열(Color Filter Array)을 가진 하나의 영상 획득 센서를 사용한다. 따라서 영상획득 이후에 컬러 보간 알고리즘이 필수적으로 진행된다. 또 영상 획득 과정에서 센서의 열화나 암전류 등과 같은 잡음이 발생하여 영상 잡음 제거 알고리즘이 필요하다. 하지만 기존의 대부분의 영상 잡음 제거 알고리즘은 컬러 필터 배열 영상의 특징인 모자이크 데이터 기반이 아닌 컬러 보간 이후의 풀 컬러영상에(YCbCr) 적용되고 있다. 따라서 잡음이 포함된 영상으로 컬러 보간을 할 경우 잡음의 공간적 상관관계(spatial correlation)가 커짐에 의한 잡음 번짐 때문에 컬러 보간 이후의 잡음제거는 더욱 어렵게 된다. 이와 같은 문제를 해결하기 위해 컬러 필터 배열 영상에 대한 잡음제거 알고리즘이 연구되고 있으며, 본 논문에서도 CMOS/CCD의 이미지 센서에서 획득된 베이어 컬러 필터 배열 영상에서 잡음을 제거하는 알고리즘을 제안한다. 이를 위해서 베이어 컬러 필터 배열 영상 데이터에서 경계(edge)의 방향성을 고려한 LMMSE 방법을 기반으로 한 잡음제거 알고리즘을 제안한다. 제안하는 알고리즘은 영상의 경계를 보존해주며 잡음제거 과정 다음에 진행되는 컬러 보간 과정에서의 잡음 번짐의 문제를 해결할 수 있다. 실험 결과를 통해 향상된 잡음 제거 효과를 확인하였다.

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The Quantization Noise Reducing Effect on Enrage Signals by the Soft-Threshold Technique (Soft-Threshold 기법을 이용한 영상신호의 양자화 잡음 제거 효과)

  • 우창용;박남천
    • Proceedings of the Korea Multimedia Society Conference
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    • pp.393-396
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    • 2003
  • 고압축 영상신호에서 발생된 양자화잡음 제거 효과를 비교하였다. 잡음제거는 Soft-Threshold 기법을 이용하여 각 대역에서 양자화 잡음을 제거하였다. Soft-Threshold 기법에 적용하기 위해 각 대역별 잡음분산을 Monotonic 변환 및 SURE, Visu 방법으로 추정하여 양자화 잡음제거 효과를 PSNR로 비교하였다. 양자화 잡음 제거 결과 영상에 따라 달라지지만 유니폼 양자화 영상에서 약 5~6dB 정도의 영상품질 개선 효과가 있었다.

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Salt and Pepper Noise Removal using Neighborhood Pixels (이웃한 픽셀을 이용한 Salt and Pepper 잡음제거)

  • Baek, Ji-Hyeoun;Kim, Chul-Ki;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.217-219
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    • 2019
  • In response to the increased use of digital video device, more researches are actively made on the image processing technologies. Image processing is practically used on various applied fields such as medical photographic interpretation, and object recognition. The types of image noise include Gaussian Noise, Impulse Noise, and Salt and Pepper. Noise refers to the unnecessary information which damages the video and the noise is mainly removed by a filter. Typical noise removal methods are Median Filter and Average Filter. While Median Filter is effective for removing Salt and Pepper noise, the noise removal performance is relatively lower in the environment with high noise density. To address such issue, this study suggested an algorithm which utilizes neighboring pixels to remove noise.

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Image Restoration Algorithm for Image Noise Removal in Mixed Noise Environment (복합잡음 환경에서 영상 잡음제거를 위한 영상복원 알고리즘)

  • Long, Xu;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.112-114
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    • 2014
  • Generally, images are corrupted by the impulse or AWGN and there are cases where both of these noises are added at once. When it comes to eliminating the noises added to the image, the previous median filter is effective in removing the impulse noise and the average filter is effective for removing AWGN. However, when the complex noises are added, it lacks the noise suppression characteristics, thus in this paper, a non-linear filter algorithm for removing the complex noises was proposed. The simulation results shows the proposed algorithm has excellent de-noising capabilities of compare existing methods.

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Non-Impulse Noise Reduction of Binary Image based on Morphological Arithmetic (형태학적 연산에 기반한 이진영상의 비임펄스 잡음제거)

  • 김재석;정성옥
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.6
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    • pp.909-914
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    • 2002
  • In this thesis, noise reduction of image with impulse noise in circle image removed noise to harness existing median filter for noise reduction from image data of damage by noise when impulse noise is high or noise reduction is low, but it is not made up of noise reduction to harness existing median filter in case of existence of non-impulse noise. Therefore noise reduction of image with non-impulse noise had to remove noise by morphological arithmetic in this thesis's proposition. In contrast to median filtering, result of edge detection is more efficient after remove non-impulse noise by method of thesis's proposition and it compare and demonstrate through this experimentation.

A Study on Translation-Invariant Wavelet De-Noising with Multi-Thresholding Function (다중 임계치 함수의 TI 웨이브렛 잡음제거 기법)

  • Choi, Jae-Yong
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.7
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    • pp.333-338
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    • 2006
  • This paper proposes an improved do-noising method using multi-thresholding function based on translation-invariant (W) wavelet proposed by Donoho et al. for underwater radiated noise measurement. The traditional wavelet thresholding de-noising method causes Pseudo-Gibbs phenomena near singularities due to discrete wavelet transform. In order to suppress Pseudo-Gibbs Phenomena, a do-noising method combining multi-thresholding function with the translation-invariant wavelet transform is proposed in this paper. The multi-thresholding function is a modified soft-thresholding to each node according to the discriminated threshold so as to reject かon external noise and white gaussian noise. It is verified by numerical simulation. And the experimental results are confirmed through sea-trial using multi-single sensors.

Adaptive Denoising for Low Light Level Environment Using Frequency Domain Analysis (주파수 해석에 따른 저조도 환경의 적응적 잡음제거)

  • Yi, Jeong-Youn;Lee, Seong-Won
    • Journal of the Institute of Electronics and Information Engineers
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    • v.49 no.9
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    • pp.128-137
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    • 2012
  • When a CCD camera acquires images in the low light level environment, not only the image signals but also noise components are amplified by the AGC (auto gain control) circuit. Since the noise level in the images acquired in the dark is very high, it is difficult to remove noise with existing denoising algorithms that are targeting the images taken in the normal light condition. In this paper, we proposed an adaptive denoising algorithm that can efficiently remove significant noises caused by the low light level. First, the window including a target pixel is transformed to the frequency domain. Then the algorithm compares the characteristics of equally divided four frequency bands. Finally the noises are adaptively removed according to the frequency characteristics. The proposed algorithm successfully improves the quality of low light level images than the existing algorithms do.

Estimation of the Noise Variance in Image and Noise Reduction (영상에 포함된 잡음의 분산 추정과 잡음제거)

  • Kim, Yeong-Hwa;Nam, Ji-Ho
    • The Korean Journal of Applied Statistics
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    • v.24 no.5
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    • pp.905-914
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    • 2011
  • In the field of image processing, the removal noise contamination from the original image is essential. However, due to various reasons, the occurrence of the noise is practically impossible to prevent completely. Thus, the reduction of the noise contained in images remains important. In this study, we estimate the level of noise variance based on the measurement of the relative strength of the noise, and we propose a noise reduction algorithm that uses a sigma filter. As a result, the proposed statistical noise reduction methodology provides significantly improved results over the usual sigma filtering regardless of the level of the noise variance.