• Title/Summary/Keyword: speckle noise

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Automated Measurement System of Carotid Artery Intima-Media Thickness based on Dynamic Programming (다이나믹 프로그래밍 기반 경동맥 내막-중막 두께 자동측정 시스템)

  • Lee, Yu-Bu;Kim, Myoung-Hee
    • Journal of the Korea Society for Simulation
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    • v.16 no.1
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    • pp.21-29
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    • 2007
  • In this paper, we present a method of detecting the boundary of the intima-media complex for automated measurement based on dynamic programming from carotid artery B-mode ultrasound images and then show the experimental results. We apply the dynamic programming for determining the optimal locations that a cost function is minimized. The cost function includes cost terms which are representing image features such as intensity, intensity gradient and geometrical continuity of the vessel interfaces. Moreover, we improve the boundary continuity by applying the B-spline to smooth the rough boundary due to noise such as speckle, dropout and weak edges. The proposed method has obtained more accurate reproducible results than conventional edge-detection by considering multiple image features and ensures efficient automated measurement by solving the problems of the inter- and intra-observer variability and its inefficiency due to manual measurement.

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Despeckling and Classification of High Resolution SAR Imagery (고해상도 SAR 영상 Speckle 제거 및 분류)

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.25 no.5
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    • pp.455-464
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    • 2009
  • Lee(2009) proposed the boundary-adaptive despeckling method using a Bayesian model which is based on the lognormal distribution for image intensity and a Markov random field(MRF) for image texture. This method employs the Point-Jacobian iteration to obtain a maximum a posteriori(MAP) estimate of despeckled imagery. The boundary-adaptive algorithm is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The boundary-adaptive scheme was comprehensively evaluated using simulation data and the effectiveness of boundary adaption was proved in Lee(2009). This study, as an extension of Lee(2009), has suggested a modified iteration algorithm of MAP estimation to enhance computational efficiency and to combine classification. The experiment of simulation data shows that the boundary-adaption results in yielding clear boundary as well as reducing error in classification. The boundary-adaptive scheme has also been applied to high resolution Terra-SAR data acquired from the west coast of Youngjong-do, and the results imply that it can improve analytical accuracy in SAR application.

GEOLOGICAL LINEAMENTS ANALYSIS BY IFSAR IMAGES

  • Wu Tzong-Dar;Chang Li Chi
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.169-172
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    • 2005
  • Modem SAR interferometry (IFSAR) sensors delivering intensity images and corresponding digital terrain model (DTM) allow for a thorough surface lineament interpretation with the all-weather day-night applicability. In this paper, an automatic linear-feature detection algorithm for high-resolution SAR images acquired in Taiwan is proposed. Methodologies to extract linear features consist of several stages. First, the image denoising techniques are used to remove the speckle noise on the raw image. In this stage, the Lee filter has been chosen because of its superior performance. After denoising, the Coefficient of Variation Detector is performed on the result images for edge enhancements and detection. Dilation and erosion techniques are used to reconnect the fragmented lines. The Hough transform, which is a special case of a more general transform known as Radon transform, is a suitable method for line detection in our analysis. Finally, linear features are extracted from the binary edge image. The last stage contains many substeps such as edge thinning and curve pruning.

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Ganglion Cyst Region Extraction from Ultrasound Images Using Possibilistic C-Means Clustering Method

  • Suryadibrata, Alethea;Kim, Kwang Baek
    • Journal of information and communication convergence engineering
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    • v.15 no.1
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    • pp.49-52
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    • 2017
  • Ganglion cysts are benign soft tissues usually encountered in the wrist. In this paper, we propose a method to extract a ganglion cyst region from ultrasonography images by using image segmentation. The proposed method using the possibilistic c-means (PCM) clustering method is applicable to ganglion cyst extraction. The methods considered in this thesis are fuzzy stretching, median filter, PCM clustering, and connected component labeling. Fuzzy stretching performs well on ultrasonography images and improves the original image. Median filter reduces the speckle noise without decreasing the image sharpness. PCM clustering is used for categorizing pixels into the given cluster centers. Connected component labeling is used for labeling the objects in an image and extracting the cyst region. Further, PCM clustering is more robust in the case of noisy data, and the proposed method can extract a ganglion cyst area with an accuracy of 80% (16 out of 20 images).

Oil Spill Detection from RADARSAT-2 SAR Image Using Non-Local Means Filter

  • Kim, Daeseong;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.33 no.1
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    • pp.61-67
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    • 2017
  • The detection of oil spills using radar image has been studied extensively. However, most of the proposed techniques have been focused on improving detection accuracy through the advancement of algorithms. In this study, research has been conducted to improve the accuracy of oil spill detection by improving the quality of radar images, which are used as input data to detect oil spills. Thresholding algorithms were used to measure the image improvement both before and after processing. The overall accuracy increased by approximately 16%, the producer accuracy increased by 40%, and the user accuracy increased by 1.5%. The kappa coefficient also increased significantly, from 0.48 to 0.92.

Reduction of Seam Line Using an FIR Filter in Spatially Compounded Ultrasonic Diagnostic Images (공간합성된 초음파 의료영상에서 FIR 필터를 이용한 심라인 감소방법)

  • Choi, Myoung Hwan
    • Journal of Industrial Technology
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    • v.28 no.B
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    • pp.129-133
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    • 2008
  • A method to reduce seam line artifact in spatial compounding of ultrasonic images is presented. Spatial compounding is a speckle reducing imaging technique in which a number of ultrasound images of a given target that have been obtained from multiple view angles are combined into a single compounded image by combining the data received from each data point in the compounded image. Since different view angle results in different view area, and the images of different view arms are combined into an image, the compounded image consists of regions with different signal to noise ratio, and the boundary lines between these regions are visible as seam lines in the compounded images. In this paper, we present an algorithm that reduces the visibility of this seam line in the spatially compounded images. Design procedure for a FIH filter is described and the results of applying the filter to in-vivo ultrasonic images are analyzed.

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A Study on the Determination of Displacement by Applied Laser Measurement (레이저응용계측에 의한 변위 정량화에 관한 연구)

  • 김경석;홍진후;강기수;최지은
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2000.11a
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    • pp.93-96
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    • 2000
  • This study discusses a non-contact optical technique, phase shifting electronic speckle pattern interferometry, that is well suited for a deformation measurement. However, the phase shifting method has difficulties for determinating a deformation quantitatively beacuse of the characteristics of arctan function. In order to solve this problem, phase unwrapping methods has been studied during the last few years. In this study, using phase unwrapping based on line by line scanning phase shifted fringe patterns are studied to determinate a deformation quantitatively. Also least square fitting method is applied to reduce noise and improve image resolution.

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A Despeckling Method Using Deep Convolutional Neural Network in Synthetic Aperture Radar Image (깊은 합성곱 신경망을 이용한 Synthetic Aperture Radar 영상 내 반전 잡음 성분 제거 기법)

  • Kim, Moonheum;Lee, Junghyun;Jeong, Jaechang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2017.11a
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    • pp.66-69
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    • 2017
  • 본 논문에서는 깊은 합성 곱 신경망 (Deep Convolutional Neural Network) 를 이용해서 SAR (Synthetic Aperture Radar) 영상의 반전 잡음 (speckle noise) 성분을 제거하는 기법을 제안하고자 한다. Deep Convolutional Neural Network는 이미지의 데이터 특성에 적합한 딥 러닝 방법이고, 이는 SAR 위성영상의 반전 잡음 제거에 사용해도 효과적이다. 반전 잡음 필터 모델 추정을 위한 학습은 임의로 반전 잡음을 합성한 트레이닝 이미지들과 원본 트레이닝 이미지들을 이용한 회귀모델을 통해 진행된다. 학습을 통해 얻은 반전 잡음 필터는 기존 알고리즘에 비해 우수한 외곽선 보존 성능을 나타냄을 확인하였다.

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The analysis of interferometry fringe pattern under shearing quantity and inside pressure change for inspect inside defects using by digital shearography (Digital shearography를 이용한 내부결함 검출에 있어서 전단량과 내부압력 변화에 따른 간섭줄무늬 패턴 분석)

  • 김형택;김경석;홍진후;강기수
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2001.04a
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    • pp.140-143
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    • 2001
  • Digital shearography, a speckle pattern method is based on the superposition of two laterally sheared images. Therefore, object points which are positioned in some distance from each other are superposed in the image plane. This shearography, one of NDT methods without contact, is able to inspect defects in pipelines and pressure vessels that are used in nuclear power plants. This is can inspect whole fields and has a low sensitivity to environmental noise. Because optical setting is very simple, it has a little exhaustion of time, cost and man power. And also it can find a defect position through real time monitoring of a part. This paper, finds out the relationship among shearing quantity image quality and defect size with this method.

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Ideal Phase map Extraction Method and Filtering of Electronic Speckle Pattern Interferometry (ESPI 에서의 이상적인 위상도 추출과 필터링 방법)

  • 유원재;이주성;강영준;채희창
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2001.04a
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    • pp.235-238
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    • 2001
  • Deformation phase can be obtained by using Least-Square Fitting. In extraction of phase values, Least-Square Fitting is superior to usual method like as 2, 3, 4-Bucket Algorithm. That can extract almost noise-free phase and retain 2$\pi$discontinuities. But more fringe in phase map, 2$\pi$ discontinuities is destroyed when that is filtered and reconstruction of deformation is not reliable. So, we adapted Least-Square Fitting using an isotropic window in dense fringe. using Sine-Cosine filter give us perfect 2$\pi$discontinuities information. We showed the process and result of extraction of phase map and filtering in this paper.

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