• Title/Summary/Keyword: IR image

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High Performance Millimeter-Wave Image Reject Low-Noise Amplifier Using Inter-stage Tunable Resonators

  • Kim, Jihoon;Kwon, Youngwoo
    • ETRI Journal
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    • v.36 no.3
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    • pp.510-513
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    • 2014
  • A Q-band pHEMT image-rejection low-noise amplifier (IR-LNA) is presented using inter-stage tunable resonators. The inter-stage L-C resonators can maximize an image rejection by functioning as inter-stage matching circuits at an operating frequency ($F_{OP}$) and short circuits at an image frequency ($F_{IM}$). In addition, it also brings more wideband image rejection than conventional notch filters. Moreover, tunable varactors in L-C resonators not only compensate for the mismatch of an image frequency induced by the process variation or model error but can also change the image frequency according to a required RF frequency. The implemented pHEMT IR-LNA shows 54.3 dB maximum image rejection ratio (IRR). By changing the varactor bias, the image frequency shifts from 27 GHz to 37 GHz with over 40 dB IRR, a 19.1 dB to 17.6 dB peak gain, and 3.2 dB to 4.3 dB noise figure. To the best of the authors' knowledge, it shows the highest IRR and $F_{IM}/F_{OP}$ of the reported millimeter/quasi-millimeter wave IR-LNAs.

Infrared Image Sharpness Enhancement Method Using Super-resolution Based on Adaptive Dynamic Range Coding and Fusion with Visible Image (적외선 영상 선명도 개선을 위한 ADRC 기반 초고해상도 기법 및 가시광 영상과의 융합 기법)

  • Kim, Yong Jun;Song, Byung Cheol
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.11
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    • pp.73-81
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    • 2016
  • In general, infrared images have less sharpness and image details than visible images. So, the prior image upscaling methods are not effective in the infrared images. In order to solve this problem, this paper proposes an algorithm which initially up-scales an input infrared (IR) image by using adaptive dynamic range encoding (ADRC)-based super-resolution (SR) method, and then fuses the result with the corresponding visible images. The proposed algorithm consists of a up-scaling phase and a fusion phase. First, an input IR image is up-scaled by the proposed ADRC-based SR algorithm. In the dictionary learning stage of this up-scaling phase, so-called 'pre-emphasis' processing is applied to training-purpose high-resolution images, hence better sharpness is achieved. In the following fusion phase, high-frequency information is extracted from the visible image corresponding to the IR image, and it is adaptively weighted according to the complexity of the IR image. Finally, a up-scaled IR image is obtained by adding the processed high-frequency information to the up-scaled IR image. The experimental results show than the proposed algorithm provides better results than the state-of-the-art SR, i.e., anchored neighborhood regression (A+) algorithm. For example, in terms of just noticeable blur (JNB), the proposed algorithm shows higher value by 0.2184 than the A+. Also, the proposed algorithm outperforms the previous works even in terms of subjective visual quality.

Image-Based Machine Learning Model for Malware Detection on LLVM IR (LLVM IR 대상 악성코드 탐지를 위한 이미지 기반 머신러닝 모델)

  • Kyung-bin Park;Yo-seob Yoon;Baasantogtokh Duulga;Kang-bin Yim
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.34 no.1
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    • pp.31-40
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    • 2024
  • Recently, static analysis-based signature and pattern detection technologies have limitations due to the advanced IT technologies. Moreover, It is a compatibility problem of multiple architectures and an inherent problem of signature and pattern detection. Malicious codes use obfuscation and packing techniques to hide their identity, and they also avoid existing static analysis-based signature and pattern detection techniques such as code rearrangement, register modification, and branching statement addition. In this paper, We propose an LLVM IR image-based automated static analysis of malicious code technology using machine learning to solve the problems mentioned above. Whether binary is obfuscated or packed, it's decompiled into LLVM IR, which is an intermediate representation dedicated to static analysis and optimization. "Therefore, the LLVM IR code is converted into an image before being fed to the CNN-based transfer learning algorithm ResNet50v2 supported by Keras". As a result, we present a model for image-based detection of malicious code.

Automatic Registration between EO and IR Images of KOMPSAT-3A Using Block-based Image Matching

  • Kang, Hyungseok
    • Korean Journal of Remote Sensing
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    • v.36 no.4
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    • pp.545-555
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    • 2020
  • This paper focuses on automatic image registration between EO (Electro-Optical) and IR (InfraRed) satellite images with different spectral properties using block-based approach and simple preprocessing technique to enhance the performance of feature matching. If unpreprocessed EO and IR images from Kompsat-3A satellite were applied to local feature matching algorithms(Scale Invariant Feature Transform, Speed-Up Robust Feature, etc.), image registration algorithm generally failed because of few detected feature points or mismatched pairs despite of many detected feature points. In this paper, we proposed a new image registration method which improved the performance of feature matching with block-based registration process on 9-divided image and pre-processing technique based on adaptive histogram equalization. The proposed method showed better performance than without our proposed technique on visual inspection and I-RMSE. This study can be used for automatic image registration between various images acquired from different sensors.

Robust Least Squares Motion Deblurring Using Inertial Sensor for Strapdown Image IR Sensors (스트랩다운 적외선 영상센서를 위한 관성센서 기반 강인최소자승 움직임 훼손영상 복원 기법)

  • Kim, Ki-Seung;Ra, Sung-Woong
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.4
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    • pp.314-320
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    • 2012
  • This paper proposes a new robust motion deblurring filter using the inertial sensor measurements for strapdown image IR applications. With taking the PSF measurement error into account, the motion blurred image is modeled by the linear uncertain state space equation with the noise corrupted measurement matrix and the stochastic parameter uncertainty. This motivates us to solve the motion deblurring problem based on the recently developed robust least squares estimation theory. In order to suppress the ringing effect on the deblurred image, the robust least squares estimator is slightly modified by adoping the ridge-regression concept. Through the computer simulations using the actual IR scenes, it is demonstrated that the proposed algorithm shows superior and reliable motion deblurring performance even in the presence of time-varying motion artifact.

LOSSY JPEG CHARACTERISTIC ANALYSIS OF METEOROLOGICAL SATELLITE IMAGE

  • Kim, Tae-Hoon;Jeon, Bong-Ki;Ahn, Sang-Il;Kim, Tae-Young
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.282-285
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    • 2006
  • This paper analyzed the characteristics of the Lossy JPEG of the meteorological satellite image, and analyzed the quality of the Lossy JPEG compression, which is proper for the LRIT(Low Rate Information Transmission) to be serviced to the SDUS(Small-scale Data Utilization Station) system of the COMS(Communication, Oceans, Meteorological Satellite). Since COMS is to start running after 2008, we collected the data of the MTSAT-1R(Multi-functional Transport Satellite -1R) for analysis, and after forming the original image to be used to LRIT by each channel and time zone of the satellite image data, we set the different quality with the Lossy JPEG compression, and compressed the original data. For the characteristic analysis of the Lossy JPEG, we measured PSNR(Peak Signal to Noise Rate), compression rate and the time spent in compression following each quality of Lossy JPEG compression. As a result of the analysis of the satellite image data of the MTSAT-1R, the ideal quality of the Lossy JPEG compression was found to be 90% in the VIS Channel, 85% in the IR1 Channel, 80% in the IR2 Channel, 90% in the IR3 Channel and 90% in the IR4 Channel.

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Synthetic Infra-Red Image Dataset Generation by CycleGAN based on SSIM Loss Function (SSIM 목적 함수와 CycleGAN을 이용한 적외선 이미지 데이터셋 생성 기법 연구)

  • Lee, Sky;Leeghim, Henzeh
    • Journal of the Korea Institute of Military Science and Technology
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    • v.25 no.5
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    • pp.476-486
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    • 2022
  • Synthetic dynamic infrared image generation from the given virtual environment is being the primary goal to simulate the output of the infra-red(IR) camera installed on a vehicle to evaluate the control algorithm for various search & reconnaissance missions. Due to the difficulty to obtain actual IR data in complex environments, Artificial intelligence(AI) has been used recently in the field of image data generation. In this paper, CycleGAN technique is applied to obtain a more realistic synthetic IR image. We added the Structural Similarity Index Measure(SSIM) loss function to the L1 loss function to generate a more realistic synthetic IR image when the CycleGAN image is generated. From the simulation, it is applicable to the guided-missile flight simulation tests by using the synthetic infrared image generated by the proposed technique.

A Study on an Infrared Illumination Stabilization Method in a Head Mounted Eye Tracking System for Sport Applications (착용형 시선 추적 장치의 스포츠 분야 적용을 위한 적외선 조명 변화 최소화에 관한 연구)

  • Lee, Sang-Cheol
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.3
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    • pp.265-272
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    • 2009
  • In this paper, a simple optical method that uses an infrared(IR) cut filter is proposed to minimize variation of eye image by external infrared(IR) sources in a video based head mounted eye tracking system that is used in the field of sports. For this, the IR cut filter is attached to a head mount of the eye tracking system, and the camera with an IR LED is located between the IR cut filter and eye. In this structure, external IR is blocked by the IR cut filter, and the IR intensity on the eye can be controlled by the IR LED. Therefore, the illumination condition of the camera to capture the eye can be stable without being affected by external IR illuminations. To verify the proposed idea, variation of the eye image and intensity of the IR with/without the IR cut filter is measured under various illumination conditions. The measured data show that the IR cut filter method can block external IR effectively, and complex pupil detection algorithms can be replaced by a simple binarized method.

Comparison of Non-Destructive Testing Images using $^{192}Ir$ and $^{75}Se$ with Computed Radiography System (Computed Radiography 시스템에 $^{192}Ir$$^{75}Se$ 동위원소를 적용하여 촬영한 비파괴검사 영상 비교)

  • Kang, Sang-Mook;Chol, Chang-Il;Lee, Seung-Kyu;Park, Sang-Ki;Kim, Yong-Kyun
    • Journal of Radiation Protection and Research
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    • v.35 no.1
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    • pp.26-33
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    • 2010
  • A computed Radiography (CR) system by use of reusable Image Plate (IP) offers a convenient and reliable way to replace a conventional film-screen system for NDT (non-destructive testing) field. The quality of a radiography to detect a defect of welded objects depends on the procedure embracing several factors such as measurement conditions, image plate type/class, radiation energy, radiation type, and source to image plate distance. Also, the ability of images to detect a flaw reduces with increasing object thickness. In the study, the properties of gamma ray source were summarized for NDT field and inspection images of CR image system manufactured by FUJI were acquired using $^{75}Se$ and $^{192}Ir$ with welded objects. We analyzed the gray scale of hole defect image by using XCAP image processing program and calculated the image contrast and SNR in definition. Also the sesitivities of image quality indicator(IQI) were calculated for hot and cooling tube image of $^{75}Se$ and $^{192}Ir$.

Automatic Registration Method for EO/IR Satellite Image Using Modified SIFT and Block-Processing (Modified SIFT와 블록프로세싱을 이용한 적외선과 광학 위성영상의 자동정합기법)

  • Lee, Kang-Hoon;Choi, Tae-Sun
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.4 no.3
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    • pp.174-181
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    • 2011
  • A new registration method for IR image and EO image is proposed in this paper. IR sensor is applicable to many area because it absorbs thermal radiation energy unlike EO sensor does. However, IR sensor has difficulty to extract and match features due to low contrast compared to EO image. In order to register both images, we used modified SIFT(Scale Invariant Feature Transform) and block processing to increase feature distinctiveness. To remove outlier, we applied RANSAC(RANdom SAample Concensus) for each block. Finally, we unified matching features into single coordinate system and remove outlier again. We used 3~5um range IR image, and our experiment result showed good robustness in registration with IR image.