• Title/Summary/Keyword: 열화 영상

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A Study on Impulse Noise Removal (임펄스 잡음제거에 관한 연구)

  • Kim, Kuk-Seung;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.05a
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    • pp.477-480
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    • 2009
  • In the process of transmitting images, there are several different underlying causes of degradation that have been occuring. The main underlying cause of the degradation has been attributed to the noise. The most representive method of removal noise of image, which is caused by impulse noise, is using the SM filter. At edge the filter has a special feature which has a tendency to decrease. As a result, this paper we proposed the nonlinear filter using the form of mask and the probability of the impulse noise to restore the image considering edge quality in the impulse noise environment. And through the simulation, we compared with the existing methods and capabilties.

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Image Optimization of Fast Non Local Means Noise Reduction Algorithm using Various Filtering Factors with Human Anthropomorphic Phantom : A Simulation Study (인체모사 팬텀 기반 Fast non local means 노이즈 제거 알고리즘의 필터링 인자 변화에 따른 영상 최적화: 시뮬레이션 연구)

  • Choi, Donghyeok;Kim, Jinhong;Choi, Jongho;Kang, Seong-Hyeon;Lee, Youngjin
    • Journal of the Korean Society of Radiology
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    • v.13 no.3
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    • pp.453-458
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    • 2019
  • In this study we analyzed the tendency of the image characteristic by changing filtering factor for the proposed fast non local means (FNLM) noise reduction algorithm with designed Male Adult mesh (MASH) phantom through Geant4 application for tomographic emission (GATE) simulation program. To accomplish this purpose, MASH phantom for human copy was designed through the GATE simulation program. In addition, we acquired degraded image by adding Gaussian noise with a value of 0.005 using the MATALB program in MASH phantom. Moreover, in degraded image, the FNLM noise reduction algorithm was applied by changing the filtering factors, which set to 0.005, 0.01, 0.05, 0.1, 0.5, and 1.0 value, respectively. To quantitatively evaluate, the coefficient of variation (COV), signal to noise ratio (SNR), and contrast to noise ratio (CNR) were calculated in reconstructed images. Results of the COV, SNR and CNR were most improved in image with a filtering factor of 0.05 value. Especially, the COV was decreased with increasing filtering factor, and showed nearly constant values after 0.05 value of the filtering factor. In addition, SNR and CNR were showed that improvement with increasing filtering factor, and deterioration after 0.05 value of the filtering factor. In conclusion, we demonstrated the significance of setting the filtering factor when applying the FNLM noise reduction algorithm in degraded image.

A Study on the Measurement of Respiratory Rate Using Image Alignment and Statistical Pattern Classification (영상 정합 및 통계학적 패턴 분류를 이용한 호흡률 측정에 관한 연구)

  • Moon, Sujin;Lee, Eui Chul
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.8 no.10
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    • pp.63-70
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    • 2018
  • Biomedical signal measurement technology using images has been developed, and researches on respiration signal measurement technology for maintaining life have been continuously carried out. The existing technology measured respiratory signals through a thermal imaging camera that measures heat emitted from a person's body. In addition, research was conducted to measure respiration rate by analyzing human chest movement in real time. However, the image processing using the infrared thermal image may be difficult to detect the respiratory organ due to the external environmental factors (temperature change, noise, etc.), and thus the accuracy of the measurement of the respiration rate is low.In this study, the images were acquired using visible light and infrared thermal camera to enhance the area of the respiratory tract. Then, based on the two images, features of the respiratory tract region are extracted through processes such as face recognition and image matching. The pattern of the respiratory signal is classified through the k-nearest neighbor classifier, which is one of the statistical classification methods. The respiration rate was calculated according to the characteristics of the classified patterns and the possibility of breathing rate measurement was verified by analyzing the measured respiration rate with the actual respiration rate.

Improvement Effects on Lock-in Thermography by Iterative Adaption in Optical Excitation (광학가진의 반복 정합에 의한 위상잠금 열화상 개선 효과)

  • Kim, Won Tae
    • Journal of the Korean Society for Nondestructive Testing
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    • v.33 no.4
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    • pp.376-381
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    • 2013
  • 위상잠금 열화상에서는 일반적으로 변조된 주파수의 광램프를 쓰고 있다. 하지만 램프의 광도 분포는 입력신호가 평단(flat)특성임에 불구하고 심지어 불균일하여 검사 시편내에 측면 열유동을 만들어낸다. 이러한 열유동은 원치 않는 효과로서 측면의 분해능을 감소시키는 등과 같이 관심 결함구조의 영상에 부정적인 영향을 미친다. 본 고에서 검토되는 방식은 열원으로서 LCD 프로젝터와 같은 것을 이용하여 각 가진픽셀에 개별적으로 진동진폭, 광도 오프셋, 위상지연 등을 할당하는 방법에 대한 접근기술이다. 이러한 반복적인 자체학습 과정에 의한 조명 패턴을 통하여 측면 열유동이 제거되고 분해능이 향상되도록 제공하는 것이다.

A Study on the Image Processing for Effective Insulation Material Degradation Testing (효과적인 절연재료 열화검사를 위한 영상처리에 관한 연구)

  • 정기봉;오무송;김태성
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 1999.05a
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    • pp.230-233
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    • 1999
  • Because Insulation material is play an important part for normal work of electricity equipment, the study is advanced, but as the voltage of electricity system is raising, we required that new lnsulation material. They have excellent specific against high stress, namely the study of insulation increase and prevention diagnosis of insulation degradation of Epoxy or XLPE and so on. In this thesis. I utilize image processing technique for effective inspection of insulation material degradation.

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Need of Identity Recognition Using Thermal Image (열화상 카메라를 활용한 얼굴 변장 인식의 필요성)

  • Jun, Young-Min;Cheema, Usman;Moon, Seungbin
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.10a
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    • pp.878-879
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    • 2018
  • 위 본문은 얼굴 변장인식의 필요성에 대해 언급을 하고 있다. 해당 논문은 얼굴 변장 인식의 기존의 연구 소개와 동시에 열화상 카메라로 촬영한 영상이 얼굴 변장 인식에 더욱 적합한 이유를 설명한다.

Development and Possibility Evaluation of Thermal Imaging Camera for Medical Monitoring of Body Temperature (열화상카메라 개발을 통한 의료용 체열진단 가능성 평가)

  • Ryu, Seong Mi;Kim, Hye-Jeong
    • Journal of Korea Society of Industrial Information Systems
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    • v.20 no.1
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    • pp.57-62
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    • 2015
  • Recently, thermography camera have been using for body-temperature monitoring. We report on fabrication of prototype thermography camera using the chalcogenide-glass lens and the camera test by analysis of thermal image. In this work, it was found out that thermography camera discerned body-temperature between 20 and $50^{\circ}C$ with noise equivalent temperature difference(NETD) of 87.7mK. It is confirmed that thermography camera using the chalcogenide-glass lens is applicable to the body-temperature monitoring system.

Ringing Artifact Removal in Image Restoration Using Wavelet Transform (웨이블릿 변환을 이용한 영상복원의 물결현상 제거 방법)

  • Youn, Jin-Young;Yoo, Yoon-Jong;Jun, Sin-Young;Shin, Jeong-Ho;Paik, Joon-Ki
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.6
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    • pp.78-87
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    • 2008
  • Digital image find own level core media in multimedia as image restoration technology fields, which remove degradation factor for image enhancement, have been growing. Linear space-invariant image restoration algorithm often introduce ringing artifacts near sharp intensity transition areas. This paper presents a new adaptive post-filtering algorithm for reducing ringing artifact. The proposed method extracts an edge map of the image using wavelet transform Based on the edge information, ringing artifacts are detected, and removed by an adaptive bilateral filter. Experimental results show that the proposed algorithm can efficiently remove ringing artifacts with edge preservation.

Image Restoration Algorithm Considering Pixel Distribution in AWGN Environments (AWGN 환경에서 화소 분포를 고려한 영상복원 알고리즘)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.7
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    • pp.1687-1693
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    • 2015
  • Recently, demand for digital image processing devices increases rapidly, more clear images have been required. But, in the process of digital image acquisition, processing and transmission, image degradation occurs due to various external reasons and researches about noise reduction are on the rise. Therefore, this study suggested the algorithm to process AWGN(additive white Gaussian noise) by separately processing as three levels according to the pixel distribution in the mask in order to remove AWGN(additive white Gaussian noise) which is added in the image. Regarding the processed results by applying Barbara images which were damaged by AWGN(σ = 15), suggested algorithm showed the improvement by 2.87[dB], 2.95[dB], 2.88[dB], 1.52[dB], 1.49[dB], 1.58[dB] and 1.25[dB] respectively compared with the existing MF(5 × 5), A-TMF(5 × 5), AWMF(5 × 5), MF(3 × 3), A-TMF(3 × 3), AWMF(3 × 3), GF(5 × 5).

Image Restoration Algorithm using Lagrange Interpolation in Mixed Noise Environments (복합잡음 환경에서 Lagrange 보간법을 이용한 영상복원 알고리즘)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.2
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    • pp.455-462
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    • 2015
  • Image media is used for the internet, computers and digital cameras as part of the core services of multimedia. Digital images can be easily acquired and processed, due to the development of digital home appliances and personal computers' application software. However, image degradation occurs by various external causes in the acquisition, processing and transmitting process of digital images, and its main cause is known to be noise. Therefore, this study proposed and conducted the simulation of image restoration filter algorithm that processes impulse noise and Gaussian noise by applying Lagrange interpolation and spatial weighted method according to distance, respectively. The proposed algorithm improved 8.77[dB], 8.83[dB] and 10.02[dB], respectively, compared to existing A-TMF, AWMF and MMF, as a result of processing by applying the damaged Girl images to impulse noise(P=60%) and Gaussian noise(${\sigma}=10$).