• 제목/요약/키워드: 잡음 제거 기술

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An Improved Guided Image Filtering Technique based on Sobel Operator for Removing Gaussian Noise (가우시안 잡음 제거를 위한 소벨 연산자 기반의 개선된 가이디드 이미지 필터링 기법)

  • Song, Seongmin;Choi, Hyunho;Jeong, Jechang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2018.11a
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    • pp.104-107
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    • 2018
  • 최근 촬영 기기의 기술발전으로 인해 디지털 영상의 해상도가 증가함에 따라 선명한 디지털 영상에 대한 요구가 증가하고 있다. 이러한 요구에도 불구하고 디지털 영상 내 가우시안 잡음 (gaussian noise)은 촬영기기를 통해 영상 획득 및 처리 과정에서 발생하여 화질을 열화 시킨다. 디지털 이미지에서 발생하는 가우시안 잡음을 제거하기 위해서 기존의 저대역 통과 필터 (low-pass filter: LPF)를 사용하면 잡음은 제거되지만, 블러링 현상 (blurring phenomenon)이 나타난다. 이러한 문제점을 개선하기 위해 소벨 연산자 (sobel operator)를 사용하여 영상 내 에지 맵 (edge-map)을 생성하여 에지 영역과 동질 영역을 구분한다. 에지영역에서는 약한 저역 필터 (weak low-pass filter)를 사용하고, 그 외의 이미지 영역에서는 강한 저역 필터 (strong low-pass filter)를 사용하는 알고리듬을 제안하였다. 그리고 다양한 이미지에 대하여 기존 알고리듬과 제안한 알고리듬의 적용한 결과를 통해 주관적 화질 비교하였고 객관적 지표로 최대 신호 대 잡음비 (peak signal-to noise ratio: PSNR)와 구조 유사성 (structural similarity: SSIM)을 사용하여 성능을 평가하였다. 실험결과를 통해 제안된 알고리듬이 잡음 제거 및 외곽선 보존의 우수함을 확인하였다.

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Salt and Pepper Noise Removal using Effective Pixels and Linear Interpolation (유효화소와 선형보간법을 이용한 Salt and Pepper 잡음제거)

  • Lee, Hwa-Yeong;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.7
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    • pp.989-995
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    • 2022
  • Currently, the demand for image processing is increasing due to the development of IT technology, and active research is being conducted. Since image data generates image noise due to various external causes, and thus degrades the performance of the image, noise removal is essential. Salt and Pepper noise is a representative image noise, and various studies are being conducted to remove it. Existing algorithms include A-TMF, AFMF, LIWF, but these have the disadvantage that their performance is somewhat insufficient. Therefore, in this paper, we propose an algorithm that performs filtering using linear interpolation with effective pixels existing around the central pixel only in case of noise after performing noise judgment in order to efficiently remove salt and pepper noise. In order to judge the performance of the proposed algorithm, it was compared using the processed image of the previously studied algorithm and PSNR.

Performance Improvement on Hearing Aids Via Environmental Noise Reduction (배경 잡음 제거를 통한 보청 시스템의 성능 향상)

  • 박선준;윤대희;김동욱;박영철
    • The Journal of the Acoustical Society of Korea
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    • v.19 no.2
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    • pp.61-67
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    • 2000
  • Recent progress in digital and VLSI technology has offered new possibility fer noticeable advance of hearing aids. Yet, environmental noise remains one of the major problems to hearing aid users. This paper describes results which speech recognition performance and speech discrimination performance was measured for listeners with sensorineural hearing loss, while listeners in speech-band noise. In addition, to ameliorate hearing-aided environments of hearing impaired listeners, environmental noise reduction using speech enhancement techniques are investigated as a front-end of conventional hearing aids. Speech enhancement techniques are implemented in a realtime system equipped with DSP board. The clinical test results suggest that the speech enhancement technique may work in synergy with gain functions fer the greater SNR improvement as the preprocessing algorithm of digital hearing aids.

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Single-Channel Seismic Data Processing via Singular Spectrum Analysis (특이 스펙트럼 분석 기반 단일 채널 탄성파 자료처리 연구)

  • Woodon Jeong;Chanhee Lee;Seung-Goo Kang
    • Geophysics and Geophysical Exploration
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    • v.27 no.2
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    • pp.91-107
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    • 2024
  • Single-channel seismic exploration has proven effective in delineating subsurface geological structures using small-scale survey systems. The seismic data acquired through zero- or near-offset methods directly capture subsurface features along the vertical axis, facilitating the construction of corresponding seismic sections. However, substantial noise in single-channel seismic data hampers precise interpretation because of the low signal-to-noise ratio. This study introduces a novel approach that integrate noise reduction and signal enhancement via matrix rank optimization to address this issue. Unlike conventional rank-reduction methods, which retain selected singular values to mitigate random noise, our method optimizes the entire singular value spectrum, thus effectively tackling both random and erratic noises commonly found in environments with low signal-to-noise ratio. Additionally, to enhance the horizontal continuity of seismic events and mitigate signal loss during noise reduction, we introduced an adaptive weighting factor computed from the eigenimage of the seismic section. To access the robustness of the proposed method, we conducted numerical experiments using single-channel Sparker seismic data from the Chukchi Plateau in the Arctic Ocean. The results demonstrated that the seismic sections had significantly improved signal-to-noise ratios and minimal signal loss. These advancements hold promise for enhancing single-channel and high-resolution seismic surveys and aiding in the identification of marine development and submarine geological hazards in domestic coastal areas.

Weighted Filter based on Standard Deviation for Impulse Noise Removal (임펄스 잡음 제거를 위한 표준편차 기반의 가중치 필터)

  • Cheon, Bong-Won;Kim, Woo-Young;Sagong, Byung-Il;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.213-215
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    • 2021
  • With the development of IoT technology, various technologies such as artificial intelligence and automation are being grafted into industrial sites, and accordingly, the importance of data processing is increasing. In particular, a system based on a digital image may cause a malfunction due to noise in the image due to a sensor defect or a communication environment problem. Therefore, research on image processing has been continued as a pre-processing process, and an effective noise reduction technique is required depending on the type of noise and the characteristics of the image. In this paper, we propose a modified spatial weight filter to protect edge components in the impulse noise reduction process. The proposed algorithm divides the filtering mask into four regions and calculates the standard deviation of each region. The final output was filtered by applying a spatial weight to the region with the lowest standard deviation value. Simulation was conducted to evaluate the performance of the proposed algorithm, and it showed superior impulse noise reduction performance compared to the existing method.

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Implementation of Noise Reduction for Digital Video Camcorder (디지털비디오캠코더 소음 저감 알고리즘 구현)

  • Park Jaeha;Oh Yoonhak;Lee Hyuckjae
    • Proceedings of the Acoustical Society of Korea Conference
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    • autumn
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    • pp.249-252
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    • 2004
  • 본 논문에서는 TeakLite DSP 프로세서를 이용하여 캠코더에서 레코딩을 할 때 모터 소음과 주변 잡음이 입력되어 오디오 신호의 명료도가 떨어지는 문제점을 해결하기 위한 잡음 제거 기법의 실시간 구현에 대해서 기술하고자 한다. 잡음 제거를 위해서는 일반적으로 많이 사용되고 있는 Spectral Subtraction 기법을 사용하였다. 알고리즘 구현시 MIPS 감소에 효과적이었던 최적화 기법들을 적용하여 TeakLite DSP 프로세서에서 최적화되어 동작하도록 하였다. 최적화된 Spectral Subtraction 어셈블리 코드는 TeakLite DSP 프로세서에서 32 kHz, 16 bit 입력에 대해 40 MIPS에서 동작하였다.

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Improved Binarization and Removal of Noises for Effective Extraction of Characters in Color Images (컬러 영상에서 효율적 문자 추출을 위한 개선된 2치화 및 잡음 저거)

  • 이은주;정장호
    • Journal of Information Technology Application
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    • v.3 no.2
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    • pp.133-147
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    • 2001
  • This paper proposed a new algorithm for binarization and removal of noises in color images with characters and pictures. Binarization was performed by threshold which had computed with color-relationship relative to the number of pixel in background and character candidates and pre-threshold for dividing of background and character candidates in input images. The pre-threshold has been computed by the histogram of R, G, B In respect of the images, while background and character candidates of input images are divided by the above pre-threshold. As it is possible that threshold can be dynamically decided by the quantity of the noises, and the character images are maintained and the noises are removed to the maximum. And, in this study, we made the noise pattern table as a result of analysis in noise pattern included in the various color images aiming at removal of the noises from the Images. Noises included in the images can figure out Distribution by way of the noise pattern table and pattern matching itself. And then this Distribution classified difficulty of noises included in the images into the three categories. As removal of noises in the images is processed through different procedure according to the its classified difficulties, time required for process was reduced and efficiency of noise removal was improved. As a result of recognition experiments in respect of extracted characters in color images by way of the proposed algorithm, we conformed that the proposed algorithm is useful in a sense that it obtained the recognition rate in general documents without colors and pictures to the same level.

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Filtering Algorithm using Noise Judgment and Segmentation Mask for Mixed Noise Removal (복합잡음 제거를 위한 잡음판단과 분할마스크를 이용한 필터링 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.434-436
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    • 2022
  • For 4th industrial revolution and the development of various communication media, unmanned and automation are rapidly progressing in various fields. In particular, high-level image processing technology is required in fields such as smart factories, autonomous driving technology, and intelligent CCTV. Accordingly, the importance of preprocessing in a system operating based on an image is increasing, and an algorithm for effectively removing noise from an image is attracting attention. In this paper, we propose a filtering algorithm using noise judgment and a segmentation mask in a complex noise environment. The proposed algorithm calculates the final output by switching the segmentation mask suitable for filtering by performing noise judgment on the pixel values of the input image. Simulation was conducted to verify the performance of the proposed algorithm, and the result image was compared and evaluated with the existing filter algorithm.

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Bilateral Filtering for Image Enhancement using Edge detection and emphasis (경계 검출 및 강조를 이용한 양방향 필터를 통한 화질 개선)

  • Kim, Donghyun;Hwang, Ung;Jeong, Jechang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2014.11a
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    • pp.134-137
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    • 2014
  • 화질의 개선을 위해 잡음을 제거하는 기술이 많이 개발되고 있으며 그 기술들 중에 효과적으로 사용되고 있는 것 하나가 양방향 필터이다. 양방향 필터는 거리에 대한 가중치와 화소 값에 대한 가중치를 모두 고려하기 때문에 경계 부분을 보존하면서 잡음을 제거하는 것이 가능하다. 필터를 적용함으로 잡음이 제거되지만 본 논문에서는 그보다 나은 결과를 위해서 경계 부분을 캐니 에지 검출기로 검출하고 강조함으로써 양방향 필터의 장점을 전보다 부각시켜 이전보다 효과적인 화질개선 방법을 제시하고자 하였다.

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A Study on 2D/3D image Conversion Method using Optical flow of Level Simplified and Noise Reduction (Optical flow의 레벨 간소화와 잡음제거를 이용한 2D/3D 변환기법 연구)

  • Han, Hyeon-Ho;Lee, Gang-Seong;Eun, Jong-Won;Kim, Jin-Soo;Lee, Sang-Hun
    • Proceedings of the KAIS Fall Conference
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    • 2011.12b
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    • pp.441-444
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    • 2011
  • 본 논문은 2D/3D 영상 처리에서 깊이지도 생성을 위한 Optical flow에서 레벨을 간소화하여 연산량을 감소시키고 객체의 고유벡터를 이용하여 영상의 잡음을 제거하는 연구이다. Optical flow는 움직임추정 알고리즘의 하나로 두 프레임간의 픽셀의 변화 벡터 값을 나타내며 블록 매칭과 같은 알고리즘에 비해 정확도가 높다. 그러나 기존의 Optical flow는 긴 연산 시간과 카메라의 이동이나 조명의 변화에 민감한 문제가 있다. 이를 해결하기 위해 연산 시간의 단축을 위한 레벨 간소화 과정을 거치고 영상에서 고유벡터를 갖는 영역에 한해 Optical flow를 적용하여 잡음을 제거하는 방법을 제안하였다. 제안한 방법으로 2차원 영상을 3차원 입체 영상으로 변환하였고 SSIM(Structural SIMilarity Index)으로 최종 생성된 영상의 오차율을 분석하였다.

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