Atmospheric Effects Removal for the Infrared Image Sequences

Ozsarac, Seckin
Akar, Gözde
Accurate correction of atmospheric effects on data captured by an infrared (IR) camera is crucial for several applications such as vegetation monitoring, temperature monitoring, satellite images, hyperspectral imaging, numerical model simulations, surface properties characterization, and IR measurement interpretation. Atmospheric effects depend on the temporal changes, i. e., year, season, day, hour, etc., and on the geometry between the camera and the measured scene, i. e., line of sight. The orientation and the optical depth of the camera significantly affect the variation of the geometry across the pixels. In this paper, we propose a method to estimate the range and zenith angle of each pixel using only the Global Positioning System (GPS) coordinates of the camera and a point of interest in the scene. The estimated geometry and measured meteorological data are used to obtain the spectral atmospheric transmittance and path radiance. Furthermore, we propose an atmospheric effects removal, i. e., atmospheric correction, method that considers the spectral characteristics of the detector, lens, and filter. The proposed atmospheric correction process is analyzed in detail with the simultaneous measurements of two IR cameras. In this process, an enhanced temperature calibration method is developed and it is shown that the temperature accuracy for the dynamic range of the IR camera is very close to the noise equivalent temperature difference (NETD) value of the camera.


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Thermal infrared hyperspectral image processing has become an important research topic in remote sensing. One of the research topics in thermal infrared hyperspectral image classification is dimension reduction. In this paper, thermal infrared hyperspectral dimension reduction experiment results for global and local information based linear discriminant analysis is presented. Advantages of the use of not only global pattern information, but also local pattern information are tested in thermal infrared hyper...
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Güler, Zahide Selin; Vural, Elif; Department of Electrical and Electronics Engineering (2016)
Dim point target tracking in infrared (IR) images has been an active research area especially in military fields. Due to the long distance from IR sensors, target appears as a dim moving point hidden in a heavily cluttered background and causes the Signal to Noise Ratio (SNR) to be very low. We present a tracking algorithm based on Particle Filters (PF), which estimates the target position by using both brightness level and motion model measurements. A target candidate list for the presented PF algorithm is...
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Moving hot object detection in airborne thermal videos
Kaba, Utku; Akar, Gözde; Department of Electrical and Electronics Engineering (2012)
In this thesis, we present an algorithm for vision based detection of moving objects observed by IR sensors on a moving platform. In addition we analyze the performance of different approaches in each step of the algorithm. The proposed algorithm is composed of preprocessing, feature detection, feature matching, homography estimation and difference image analysis steps. First, a global motion estimation based on planar homography model is performed in order to compensate the motion of the sensor and moving ...
Image Chain Simulation for Earth Observation Satellites
Alici, Kamil B.; Öktem, Sevinç Figen; Karci, Ozgur; Yilmaz, A. Serdar; Selimoglu, Ozgur (Institute of Electrical and Electronics Engineers (IEEE), 2019-10-01)
We present a general-purpose end-to-end image chain simulation (ICS) that enables to assess the image quality of a satellite imager for Earth observations. The image chain consists of four main components: radiometry, atmosphere, optics, and detector. In particular, ICS first computes the input radiance from the reflectance values of a high-resolution input, and then calculates the image radiance by using the optical transfer function (OTF) of the overall system. This OTF contains all the distortion effects...
Citation Formats
S. Ozsarac and G. Akar, “Atmospheric Effects Removal for the Infrared Image Sequences,” IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, pp. 4899–4909, 2015, Accessed: 00, 2020. [Online]. Available: