Radiometric Calibration for MWIR Cameras

被引:0
|
作者
Yang, Hyunjin [1 ]
Chun, Joohwan [1 ]
Seo, Doo Chun [2 ]
Yang, Jiyeon [2 ]
机构
[1] Korea Adv Inst Sci & Technol, 335 Gwahangno, Taejon 305701, South Korea
[2] Korea Aerosp Res Inst, Daejeon, South Korea
关键词
Infrared; Atmospheric compensation; Image restoration; Satellite image;
D O I
10.1117/12.920553
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Korean Multi-purpose Satellite-3A (KOMPSAT-3A), which weighing about 1,000 kg is scheduled to be launched in 2013 and will be located at a sun-synchronous orbit (SSO) of 530 km in altitude. This is Korea's first satellite to orbit with a mid-wave infrared (MWIR) image sensor, which is currently being developed at Korea Aerospace Research Institute (KARI). The missions envisioned include forest fire surveillance, measurement of the ocean surface temperature, national defense and crop harvest estimate. In this paper, we shall explain the MWIR scene generation software and atmospheric compensation techniques for the infrared (IR) camera that we are currently developing. The MWIR scene generation software we have developed taking into account sky thermal emission, path emission, target emission, sky solar scattering and ground reection based on MODTRAN data. Here, this software will be used for generating the radiation image in the satellite camera which requires an atmospheric compensation algorithm and the validation of the accuracy of the temperature which is obtained in our result. Image visibility restoration algorithm is a method for removing the effect of atmosphere between the camera and an object. This algorithm works between the satellite and the Earth, to predict object temperature noised with the Earth's atmosphere and solar radiation. Commonly, to compensate for the atmospheric effect, some softwares like MODTRAN is used for modeling the atmosphere. Our algorithm doesn't require an additional software to obtain the surface temperature. However, it needs to adjust visibility restoration parameters and the precision of the result still should be studied.
引用
收藏
页数:6
相关论文
共 50 条
  • [31] Radiometric calibration of the GERB instrument
    Mossavati, R
    Harries, JE
    Kellock, S
    Wrigley, RT
    Mueller, J
    Fox, NP
    METROLOGIA, 1998, 35 (04) : 603 - 607
  • [32] CALIBRATION OF A NEUTRON RADIOMETRIC APPARATUS
    VASILEV, RD
    DOROFEEV, GA
    PETROV, VI
    MEASUREMENT TECHNIQUES-USSR, 1968, (10): : 1361 - &
  • [33] The radiometric calibration and intercalibration of Soho
    Huber, MCE
    Pauluhn, A
    von Steiger, R
    PROCEEDINGS OF THE SOHO 11 SYMPOSIUM ON FROM SOLAR MIN TO MAX: HALF A SOLAR CYCLE WITH SOHO, 2002, 508 : 213 - 214
  • [34] Preflight Radiometric Calibration of RazakSAT™
    Wai, Ng Su
    Tan, Adhwa Amir
    Mee, Jessica Wong Soo
    Ismail, Maszlan
    Subari, Mustafa Din
    RAST 2009: PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN SPACE TECHNOLOGIES, 2009, : 277 - 282
  • [35] A radiometric calibration of the SPECMAP timescale
    Thompson, William G.
    Goldstein, Steven L.
    QUATERNARY SCIENCE REVIEWS, 2006, 25 (23-24) : 3207 - 3215
  • [36] Hawkeye radiometric calibration methodology
    Lee, Shihyan
    Holmes, Alan
    Meister, Gerhard
    Patt, Frederick S.
    Feldman, Gene
    EARTH OBSERVING SYSTEMS XXIII, 2018, 10764
  • [37] RADIOMETRIC CALIBRATION OF A MULTISPECTRAL CAMERA
    Mansouri, A.
    Sanchez, M.
    Marzani, F. S.
    Gouton, P.
    COMPUTER VISION AND GRAPHICS (ICCVG 2004), 2006, 32 : 273 - 278
  • [38] Overview of the radiometric calibration of MOBY
    Clark, DK
    Feinholz, ME
    Yarbrough, MA
    Johnson, BC
    Brown, SW
    Kim, YS
    Barnes, RA
    EARTH OBSERVING SYSTEMS VI, 2002, 4483 : 64 - 76
  • [39] RADIOMETRIC CALIBRATION FOR HDR IMAGING
    Sohaib, Ahmed
    Robles-Kelly, Antonio
    2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2015, : 2815 - 2819
  • [40] Radiometric Calibration by Rank Minimization
    Lee, Joon-Young
    Matsushita, Yasuyuki
    Shi, Boxin
    Kweon, In So
    Ikeuchi, Katsushi
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2013, 35 (01) : 144 - 156