• 제목/요약/키워드: Image reconstruction algorithm

검색결과 494건 처리시간 0.031초

Image Reconstruction Method for Photonic Integrated Interferometric Imaging Based on Deep Learning

  • Qianchen Xu;Weijie Chang;Feng Huang;Wang Zhang
    • Current Optics and Photonics
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    • 제8권4호
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    • pp.391-398
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    • 2024
  • An image reconstruction algorithm is vital for the image quality of a photonic integrated interferometric imaging (PIII) system. However, image reconstruction algorithms have limitations that always lead to degraded image reconstruction. In this paper, a novel image reconstruction algorithm based on deep learning is proposed. Firstly, the principle of optical signal transmission through the PIII system is investigated. A dataset suitable for image reconstruction of the PIII system is constructed. Key aspects such as model and loss functions are compared and constructed to solve the problem of image blurring and noise influence. By comparing it with other algorithms, the proposed algorithm is verified to have good reconstruction results not only qualitatively but also quantitatively.

초음파 회절 토모그라피 영상복원 알고리즘의 분해능 분석 (The Analysis of Resolution on the Image Reconstnlction Algorithms for Ultrasonic Diffraction Tomography)

  • 구길모;황기환
    • 한국음향학회지
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    • 제18권5호
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    • pp.83-90
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    • 1999
  • 본 논문에서는 초음파 회절 토모그라피를 위한 FBP와 BFP 영상복원 알고리즘에 관한 분해능을 연구하였다. 고정좌표계를 사용한 수정된 FBP 영상복원 알고리즘과 평면구조물에 적합한 BFP 영상복원 알고리즘을 이용하여 복원할 수 있는 토모그라픽 영상에 대한 분해능을 분석할 수 있는 모호함수를 유도하고 모의실험을 통하여 얻은 측방향 및 축방향 분해능을 분석하였다. 분석결과, FBP 영상복원 알고리즘에 대한 측방향 및 축방향의 3dB분해능은 각각 0.27파장, 0.70파장을 얻었으며, 또한 BFP 영상복원 알고리즘에 대한 측방향 및 축방향 분해능도 각각 0.39파장과 0.98파장으로 정량적으로 결정하였다. 따라서 본 연구를 통하여 수정된 FBP 영상복원 알고리즘과 BFP 영상복원 알고리즘은 회절 토모그라피를 위한 영상복원에 유용하게 이용할 수 있음을 확인하였다.

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투과형 CT에서 통계적 재구성 알고리즘의 수렴률 향상 방안 (Methods to Improve Convergence Rate of Statistical Reconstruction Algorithm in Transmission CT)

  • 송민구
    • 사물인터넷융복합논문지
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    • 제10권3호
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    • pp.25-33
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    • 2024
  • 토머그래피 영상재구성에서 초점은 높은 이미지 품질을 유지하면서 환자의 방사선 노출을 줄일 수 있는 CT 영상재구성 방법을 개발하는 것이다. 일반적으로 통계적 영상재구성 방법은 고품질 및 정확한 이미지를 생성할 수 있는 능력을 개선하면서 환자의 방사선 노출을 크게 줄일 수 있다. 그런데 CT 영상재구성과 같은 다차원의 모수 추정인 경우에서는 그것의 페널티 함수의 헤이지안 행렬의 역행렬 차수가 매우 크기 때문에 구할 수가 없다. 이러한 문제점을 해결하기 위하여 저자는 PEMG-1 알고리즘을 제안하였다. 그러나 PEMG-1 알고리즘은 일반 통계적 영상재구성 방법처럼 페널티 로그우도를 증가시키는 수렴속도에 문제점이 있다. 이에 본 연구에서는 수렴속도가 빠르고 우도의 단조 증가성을 보장하는 재구성 알고리즘을 제안한다. 이 알고리즘의 기본 구조는 반복마다 모수들을 동시에 갱신하지 않고 몇 개의 픽셀로 이루어진 그룹들을 순차적으로 갱신하는 방법이다.

Stochastic Restoration and Reconstruction Filters for 2-D and 3-Dimensional Image Reconstruction

  • Yum, Young-Ho
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1979년도 하계 전자.전기연합학술발표회논문집
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    • pp.158-159
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    • 1979
  • Based on minimum-mean-sqare error criterion, a noise filtering algorithm for the reconstruction of an image function from noisy projection data is suggested. The filter is constructed with a few projection data. This algorithm requires less computational time compared with other noise filtering algorithm.

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Image Reconstruction Based on Deep Learning for the SPIDER Optical Interferometric System

  • Sun, Yan;Liu, Chunling;Ma, Hongliu;Zhang, Wang
    • Current Optics and Photonics
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    • 제6권3호
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    • pp.260-269
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    • 2022
  • Segmented planar imaging detector for electro-optical reconnaissance (SPIDER) is an emerging technology for optical imaging. However, this novel detection approach is faced with degraded imaging quality. In this study, a 6 × 6 planar waveguide is used after each lenslet to expand the field of view. The imaging principles of field-plane waveguide structures are described in detail. The local multiple-sampling simulation mode is adopted to process the simulation of the improved imaging system. A novel image-reconstruction algorithm based on deep learning is proposed, which can effectively address the defects in imaging quality that arise during image reconstruction. The proposed algorithm is compared to a conventional algorithm to verify its better reconstruction results. The comparison of different scenarios confirms the suitability of the algorithm to the system in this paper.

Sparse-View CT Image Recovery Using Two-Step Iterative Shrinkage-Thresholding Algorithm

  • Chae, Byung Gyu;Lee, Sooyeul
    • ETRI Journal
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    • 제37권6호
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    • pp.1251-1258
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    • 2015
  • We investigate an image recovery method for sparse-view computed tomography (CT) using an iterative shrinkage algorithm based on a second-order approach. The two-step iterative shrinkage-thresholding (TwIST) algorithm including a total variation regularization technique is elucidated to be more robust than other first-order methods; it enables a perfect restoration of an original image even if given only a few projection views of a parallel-beam geometry. We find that the incoherency of a projection system matrix in CT geometry sufficiently satisfies the exact reconstruction principle even when the matrix itself has a large condition number. Image reconstruction from fan-beam CT can be well carried out, but the retrieval performance is very low when compared to a parallel-beam geometry. This is considered to be due to the matrix complexity of the projection geometry. We also evaluate the image retrieval performance of the TwIST algorithm -sing measured projection data.

Genetic Algorithm Approach to Image Reconstruction in Electrical Impedance Tomography

  • Kim, Ho-Chan;Boo, Chang-Jin;Lee, Yoon-Joon;Kang, Chang-Ik
    • KIEE International Transactions on Electrophysics and Applications
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    • 제4C권3호
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    • pp.123-128
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    • 2004
  • In electrical impedance tomography (EIT), the internal resistivity distribution of the unknown object is computed using the boundary voltage data induced by different current patterns using various reconstruction algorithms. This paper presents a new image reconstruction algorithm based on the genetic algorithm (GA) via a two-step approach for the solution of the EIT inverse problem, in particular for the reconstruction of "static" images. The computer simulation for the 32 channels synthetic data shows that the spatial resolution of reconstructed images in the proposed scheme is improved compared to that of the modified Newton-Raphson algorithm at the expense of an increased computational burden.rden.

Research on Reconstruction Technology of Biofilm Surface Based on Image Stacking

  • Zhao, Yuyang;Tao, Xueheng;Lee, Eung-Joo
    • 한국멀티미디어학회논문지
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    • 제24권11호
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    • pp.1472-1480
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    • 2021
  • Image stacking technique is one of the key techniques for complex surface reconstruction. The process includes sample collection, image processing, algorithm editing, surface reconstruction, and finally reaching reliable conclusions. Since this experiment is based on laser scanning confocal microscope to collect the original contour information of the sample, it is necessary to briefly introduce the relevant principle and operation method of laser scanning confocal microscope. After that, the original image is collected and processed, and the data is expanded by interpolation method. Meanwhile, several methods of surface reconstruction are listed. After comparing the advantages and disadvantages of each method, one-dimensional interpolation and volume rendering are finally used to reconstruct the 3D model. The experimental results show that the final 3d surface modeling is more consistent with the appearance information of the original samples. At the same time, the algorithm is simple and easy to understand, strong operability, and can meet the requirements of surface reconstruction of different types of samples.

CT Image Reconstruction of Wood Using Ultrasound Velocities I - Effects of Reconstruction Algorithms and Wood Characteristics -

  • Kim, Kwang-Mo;Lee, Jun-Jae
    • Journal of the Korean Wood Science and Technology
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    • 제33권5호통권133호
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    • pp.21-28
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    • 2005
  • For the proper conservation of wooden cultural properties, non-destructive evaluation (NDE) method, which can be used to quantitatively evaluate the internal state of wood members, are needed. In this study, an ultrasonic CT system composed of portable devices was attempted, and the capacity of this system was verified by reconstructing the CT images for two phantoms and two artificially defected specimens. Results from this study showed that the sizes of detected defects were enlarged and the shapes were distorted on the CT images. Also, the positions were shifted somewhat toward the surface of specimen, which is regarded due to the anisotropic property of wood. Compared to the filtered back-projection method, SIRT (simultaneous iterative reconstruction technique) method was determined to be more efficient as the algorithm of image reconstruction for wood. A new ultrasonic CT system is thought to be used as a NDE method for wood. However wood characteristics and wave diffraction within wood made it difficult to accurately evaluate the size, shape and position of defects. To improve the quality of CT image of wood, more research including the relationship between wood and ultrasound is needed, and wood properties should be taken into consideration on the image reconstruction algorithm.

Papoulis-Gerchberg 방법의 개선에 의한 초해상도 영상 화질 향상 (Super-resolution image enhancement by Papoulis-Gerchbergmethod improvement)

  • 장효식;김덕규;정윤수;이태균;원철호
    • 센서학회지
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    • 제19권2호
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    • pp.118-123
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    • 2010
  • This paper proposes super-resolution reconstruction algorithm for image enhancement. Super-resolution reconstruction algorithms reconstruct a high-resolution image from multi-frame low-resolution images of a scene. Conventional super- resolution reconstruction algorithms are iterative back-projection(IBP), robust super-resolution(RS)method and standard Papoulis-Gerchberg(PG)method. However, traditional methods have some problems such as rotation and ringing. So, this paper proposes modified algorithm to improve the problem. Experimental results show that this proposed algorithm solve the problem. As a result, the proposed method showed an increase in the PSNR for traditional super-resolution reconstruction algorithms.