• 제목/요약/키워드: Imaging performance

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열상장비 전단증폭부 정비용 ATE의 구현 (Implementation of ATE to Maintain Pre-Amplifier of Thermal Imaging System)

  • 박재효;김한경
    • 전자공학회논문지SC
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    • 제49권1호
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    • pp.80-87
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    • 2012
  • 본 논문에서는 열상장비의 광 검출기에서 검출된 미약한 전기적 신호를 영상신호처리를 하기 위한 신호로 증폭을 해 주는 전단 증폭부의 성능 검사용 ATE(Automatic Test Equipment)를 개발하였다. 기존 ATE 장비는 주로 반도체 소자 양품검사 분야에서 활발히 개발되고 있었으나 최근에는 장비의 성능검사 분야에서도 연구되고 있다. 그러나 열상장비 성능검사 분야의 ATE 에 대한 연구는 다른 분야에 비해 미진하여 우리군의 핵심적인 감시 장비인 열상장비는 정비가 제한되었다. 이에 따라 본 논문에서는 새로운 열상장비 분야의 ATE 연구가 필요하여 전단증폭부 및 열상장비의 다른 회로카드의 범용적인 개발이 가능하도록 Matrix Relay를 개발하였다. 개발된 ATE로 전단증폭부의 증폭도를 측정한 결과 증폭 전압은 평균 2.71 Vpp로써 이론적인 분석 범위 내에 있음이 확인되어 개발된 ATE가 우수한 성능임이 검증되었다.

위상변위 극자외선 마스크의 흡수체 패턴의 기울기에 대한 오차허용도 향상 (Improved Margin of Absorber Pattern Sidewall Angle Using Phase Shifting Extreme Ultraviolet Mask)

  • 장용주;김정식;홍성철;안진호
    • 반도체디스플레이기술학회지
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    • 제15권2호
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    • pp.32-37
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    • 2016
  • Sidewall angle (SWA) of an absorber stack in extreme ultraviolet lithography mask is considered to be $90^{\circ}$ ideally, however, it is difficult to obtain $90^{\circ}$ SWA because absorber profile is changed by complicated etching process. As the imaging performance of the mask can be varied with this SWA of the absorber stack, more complicated optical proximity correction is required to compensate for the variation of imaging performance. In this study, phase shift mask (PSM) is suggested to reduce the variation of imaging performance due to SWA change by modifying mask material and structure. Variations of imaging performance and lithography process margin depending on SWA were evaluated through aerial image and developed resist simulations to confirm the advantages of PSM over the binary intensity mask (BIM). The results show that the variations of normalized image log slope and critical dimension bias depending on SWA are reduced with PSM compared to BIM. Process margin for exposure dose and focus was also improved with PSM.

Analysis of Laser-protection Performance of Asymmetric-phase-mask Wavefront-coding Imaging Systems

  • Yangliang, Li;Qing, Ye;Lei, Wang;Hao, Zhang;Yunlong, Wu;Xian'an, Dou;Xiaoquan, Sun
    • Current Optics and Photonics
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    • 제7권1호
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    • pp.1-14
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    • 2023
  • Wavefront-coding imaging can achieve high-quality imaging along with a wide range of defocus. In this paper, the anti-laser detection and damage performance of wavefront-coding imaging systems using different asymmetric phase masks are studied, through modeling and simulation. Based on FresnelKirchhoff diffraction theory, the laser-propagation model of the wavefront-coding imaging system is established. The model uses defocus distance rather than wave aberration to characterize the degree of defocus of an imaging system. Then, based on a given defocus range, an optimization method based on Fisher information is used to determine the optimal phase-mask parameters. Finally, the anti-laser detection and damage performance of asymmetric phase masks at different defocus distances and propagation distances are simulated and analyzed. When studying the influence of defocus distance, compared to conventional imaging, the maximum single-pixel receiving power and echo-detection receiving power of asymmetric phase masks are reduced by about one and two orders of magnitude respectively. When exploring the influence of propagation distance, the maximum single-pixel receiving power of asymmetric phase masks decreases by about one order of magnitude and remains stable, and the echodetection receiving power gradually decreases with increasing propagation distance, until it approaches zero.

A New Tailored Sinc Pulse and Its Use for Multiband Pulse Design

  • Park, Jinil;Park, Jang-Yeon
    • Investigative Magnetic Resonance Imaging
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    • 제20권1호
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    • pp.27-35
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    • 2016
  • Purpose: Among RF pulses, a sinc pulse is typically used for slice selection due to its frequency-selective feature. When a sinc pulse is implemented in practice, it needs to be apodized to avoid truncation artifacts at the expense of broadening the transition region of the excited-band profile. Here a sinc pulse tailored by a new apodization function is proposed that produces a sharper transition region with well suppression of truncation artifacts in comparison with conventional tailored sinc pulses. A multiband pulse designed using this newly apodized sinc pulse is also suggested inheriting the better performance of the newly apodized sinc pulse. Materials and Methods: A new apodization function is introduced to taper a sinc pulse, playing a role to slightly shift the first zero-crossing of a tailored sinc pulse from the peak of the main lobe and thereby producing a narrower bandwidth as well as a sharper pass-band in the excitation profile. The newly apodized sinc pulse was also utilized to design a multiband pulse which inherits the performance of its constituent. Performances of the proposed sinc pulse and the multiband pulse generated with it were demonstrated by Bloch simulation and phantom imaging. Results: In both simulations and experiments, the newly apodized sinc pulse yielded a narrower bandwidth and a sharper transition of the pass-band profile with a desirable degree of side-lobe suppression than the commonly used Hanning-windowed sinc pulse. The multiband pulse designed using the newly apodized sinc pulse also showed the better performance in multi-slice excitation than the one designed with the Hanning-windowed sinc pulse. Conclusion: The new tailored sinc pulse proposed here provides a better performance in slice (or slab) selection than conventional tailored sinc pulses. Thanks to the availability of analytical expression, it can also be utilized for multiband pulse design with great flexibility and readiness in implementation, transferring its better performance.

20:1 줌 열영상 장비 비열화 분석 및 시험 (Analysis and test of athermalizaion for 20:1 zoom thermal imaging system)

  • 김현숙;최세철;최세철;이국환;박용찬;김현규
    • 한국광학회지
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    • 제12권4호
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    • pp.281-288
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    • 2001
  • 본 연구에서는 넓은 운용온도에서 열영상 장비의 광학성능을 유지하도록 하기 위한 비열화 분석 및 시험을 수행하였다. 비열화 분석은 광학계 설계를 위한 컴퓨터 프로그램인 Code-V와 SIGMA2100으로 수행하였으며 비열화 시험은 열영상 장비와 콜리메이터를 온도챔버에 함께 넣어 온도에 따른 영상을 녹화하였다. 2차원배열 검출기를 사용한 20:1 줌 열영상 장비를 가지고 비열화 시뮬레이션을 수행하였으며 그 결과를 이용하여 줌궤적을 보상하였다. 비열화 시험을 통하여 온도변화에 따라 줌궤적어 적절히 작동되어 $-32^{\circ}C-+50^{\circ}C$의 온도범위 내에서 만족할 만한 광학성능이 유지되는 것을 확인하였다.

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Development and Verification of the Compact Airborne Imaging Spectrometer System

  • Lee, Kwang-Jae;Yong, Sang-Soon;Kim, Yong-Seung
    • 대한원격탐사학회지
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    • 제24권5호
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    • pp.397-408
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    • 2008
  • A wide variety of applications of imaging spectrometer have been proved using data from airborne systems. The Compact Airborne Imaging Spectrometer System (CAISS) was jointly designed and developed as the airborne hyperspectral imaging system by Korea Aerospace Research Institute (KARI) and ELOP inc., Israel. The primary mission of the CAISS is to acquire and provide full contiguous spectral information with high spatial resolution for advanced applications in the field of remote sensing. The CAISS consists of six physical units; the camera system, the gyro-stabilized mount, the jig, the GPS/INS, the power inverter and distributor, and the operating system. These subsystems are to be tested and verified in the laboratory before the flight. Especially the camera system of the CAISS has to be calibrated and validated with the calibration equipments such as the integrating sphere and spectral lamps. To improve data quality and its availability, it is the most important to understand the mechanism of imaging spectrometer system and the radiometric and spectral characteristics. The several performance tests of the CAISS were conducted in the camera system level. This paper presents the major characteristics of the CAISS, and summarizes the results of performance tests in the camera system level.

Deep-Learning-Based Molecular Imaging Biomarkers: Toward Data-Driven Theranostics

  • Choi, Hongyoon
    • 한국의학물리학회지:의학물리
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    • 제30권2호
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    • pp.39-48
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    • 2019
  • Deep learning has been applied to various medical data. In particular, current deep learning models exhibit remarkable performance at specific tasks, sometimes offering higher accuracy than that of experts for discriminating specific diseases from medical images. The current status of deep learning applications to molecular imaging can be divided into a few subtypes in terms of their purposes: differential diagnostic classification, enhancement of image acquisition, and image-based quantification. As functional and pathophysiologic information is key to molecular imaging, this review will emphasize the need for accurate biomarker acquisition by deep learning in molecular imaging. Furthermore, this review addresses practical issues that include clinical validation, data distribution, labeling issues, and harmonization to achieve clinically feasible deep learning models. Eventually, deep learning will enhance the role of theranostics, which aims at precision targeting of pathophysiology by maximizing molecular imaging functional information.

그릴 분광계를 사용하여 3중 부호화한 하다마드 변환 영상 분광계 (Triply-Encoded Hadamard Transform Imaging Spectrometer using the Grill Spectrometer)

  • 곽대연;박진배;박영재
    • 대한전기학회논문지:전력기술부문A
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    • 제48권12호
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    • pp.1527-1536
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    • 1999
  • In this paper, a triply-encoded Hadamard transform imaging spectrometer is proposed by applying the grill spectrometer to the Hadamard transform imaging spectrometer. The proposed system encodes the input radiation triply ; once through the input image mask and twice through the two masks in the grill spectrometer. We use an electro-optical mask in the grill spectrometer which is controlled by a left-cyclic simplex matrix. Then we modeled the system using $D^{-1}$ method. In this paper, the average mean square error associated with a recovered estimate is considered for performance evaluation. The relative performance is compared with those of the other conventional systems.

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Convolutional Neural Networks for Character-level Classification

  • Ko, Dae-Gun;Song, Su-Han;Kang, Ki-Min;Han, Seong-Wook
    • IEIE Transactions on Smart Processing and Computing
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    • 제6권1호
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    • pp.53-59
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    • 2017
  • Optical character recognition (OCR) automatically recognizes text in an image. OCR is still a challenging problem in computer vision. A successful solution to OCR has important device applications, such as text-to-speech conversion and automatic document classification. In this work, we analyze character recognition performance using the current state-of-the-art deep-learning structures. One is the AlexNet structure, another is the LeNet structure, and the other one is the SPNet structure. For this, we have built our own dataset that contains digits and upper- and lower-case characters. We experiment in the presence of salt-and-pepper noise or Gaussian noise, and report the performance comparison in terms of recognition error. Experimental results indicate by five-fold cross-validation that the SPNet structure (our approach) outperforms AlexNet and LeNet in recognition error.