• Title/Summary/Keyword: IR image processing

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Verification of GEO-KOMPSAT-2A AMI Radiometric Calibration Parameters Using an Evaluation Tool (분석툴을 이용한 천리안2A 기상탑재체 복사 보정 파라미터 검증)

  • Jin, Kyoungwook;Park, Jin-Hyung
    • Korean Journal of Remote Sensing
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    • v.36 no.6_1
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    • pp.1323-1337
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    • 2020
  • GEO-KOMPSAT-2A AMI (Advanced Meteorological Imager) radiometric calibration evaluation is an essential element not only for functional and performance verification of the payload but for the quality of the sensor data. AMI instrument consists of six reflective channels and ten thermal infrared ones. One of the key parameters representing radiometric properties of the sensor is a SNR (Signal-to-Noise Ratio) for the reflective channels and a NEdT (Noise Equivalent delta Temperature) for the IR ones respectively. Other important radiometric calibration parameters are a dynamic range and a gain value related with the responsivity of detectors. To verify major radiometric calibration performance of AMI, an offline radiometric evaluation tool was developed separately with a real-time AMI data processing system. Using the evaluation tool, validation activities were carried out during the GEO-KOMPSAT-2A In-Orbit Test period. The results from the evaluation tool were cross checked with those of the HARRIS, which is the AMI payload vendor. AMI radiometric evaluation activities were conducted through three phases for both sides (Side 1 and Side 2) of AMI payload. Results showed that performances of the key radiometric properties were outstanding with respect to the radiometric requirements of the payload. The effectiveness of the evaluation tool was verified as well.

Implementation of A Safe Driving Assistance System and Doze Detection (졸음 인식과 안전운전 보조시스템 구현)

  • Song, Hyok;Choi, Jin-Mo;Lee, Chul-Dong;Choi, Byeong-Ho;Yoo, Ji-Sang
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.3
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    • pp.30-39
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    • 2012
  • In this paper, a safe driving assistance system is proposed by detecting the status of driver's doze based on face and eye detection. By the level of the fatigue, safe driving system alarms or set the seatbelt on vibration. To reduce the effect of backward light and too strong solar light which cause a decrease of face and eye detection rate and false fatigue detection, post processing techniques like image equalization are used. Haar transform and PCA are used for face detection. By using the statistic of the face and eye structural ratio of normal Koreans, we can reduce the eye candidate area in the face, which results in reduction of the computational load. We also propose a new eye status detection algorithm based on Hough transform and eye width-height ratio, which are used to detect eye's blinking status which decides doze level by measuring the blinking period. The system alarms and operates seatbelt on vibration through controller area network(CAN) when the driver's doze level is detected. In this paper, four algorithms are implemented and proposed algorithm is made based on the probability model and we achieves 84.88% of correct detection rate through indoor and in-car environment experiments. And also we achieves 69.81% of detection rate which is better result than that of other algorithms using IR camera.

Quantitative Indices of Small Heart According to Reconstruction Method of Myocardial Perfusion SPECT Using the 201Tl (201Tl을 이용한 심근관류 SPECT에서 재구성 방법에 따른 작은 용적 심장의 정량 지표 변화)

  • Kim, Sung Hwan;Ryu, Jae Kwang;Yoon, Soon Sang;Kim, Eun Hye
    • The Korean Journal of Nuclear Medicine Technology
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    • v.17 no.1
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    • pp.18-24
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    • 2013
  • Purpose: Myocardial perfusion SPECT using $^{201}Tl$ is an important method for viability of left ventricle and quantitative evaluation of cardiac function and now various reconstruction methods are used to improve the image quality. But in case of small sized heart, you should always be careful because of the Partial Volume Effect which may cause errors of quantitative indices at the reconstruction step. So, In this study, we compared those quantitative indices of left ventricle according to the reconstruction method of myocardial perfusion SPECT with the Echocardiography and verified the degree of the differences between them. Materials and Methods: Based on ESV 30 mL of Echocardiography, we divided 278 patients (male;98, female;188, Mean age;$65.5{\pm}11.1$) who visited the Asan medical center from February to September, 2012 into two categories; below the criteria to small sized heart, otherwise, normal or large sized heart. Filtered and output each case, we applied the method of FBP and OSEM to each of them, and calculated EDV, ESV and LVEF, and we conducted statistical processing through Repeated Measures ANOVA with indices that measured in Echocardiography. Results: In case of men and women, there were no significant difference in EDV between FBP and OSEM (p=0.053, p=0.098), but in case of Echocardiography, there were meaningful differences (p<0.001). The change of ESV especially women in small sized heard, significant differences has occurred among FBP, OSEM and Echocardiography. Also, in LVEF, there were no difference in men and women who have normal sized heart among FBP, OSEM and Echocardiography (p=0.375, p=0.969), but the women with small sized heart have showed significant differences (p<0.001). Conclusion: The change in quantitative indices of left ventricle between Nuclear cardiology image reconstruction, no difference has occurred in the patients with normal sized heart but based on ESV, under 30 mL of small sized heart, especially in female, there were significant differences in FBP, OSEM and Echocardiography. We found out that overestimated LVEF caused by PVE can be reduced in average by applying OSEM to all kinds of gamma camera, which are used in analyzing the differences.

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True Orthoimage Generation from LiDAR Intensity Using Deep Learning (딥러닝에 의한 라이다 반사강도로부터 엄밀정사영상 생성)

  • Shin, Young Ha;Hyung, Sung Woong;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.4
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    • pp.363-373
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    • 2020
  • During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.