Volume XL-1/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W3, 117-121, 2013
https://doi.org/10.5194/isprsarchives-XL-1-W3-117-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W3, 117-121, 2013
https://doi.org/10.5194/isprsarchives-XL-1-W3-117-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

  24 Sep 2013

24 Sep 2013

SEPERATION OF IKONOS SENSOR’S ELECTRONIC NOISE FROM ATMOSPHERIC INDUCED EFFECTS

M. R. Mobashery1 and M. Dastfard2 M. R. Mobashery and M. Dastfard
  • 1Department of Remote Sensing Engineering, Industrial University of Khajeh Nasir, Iran
  • 2Telecommunication Engineering at Khavaran Institute, Iran

Keywords: Atmosphere correction, remote sensing, IKONOS, CCD, Noise, sensor

Abstract. The quality of satellite images has always been of particular importance in remote sensing. Signals received from satellite sensors include some signals other than those of target signal that may be classified totally as the atmospheric effect and the sensor induced noise. Separating non-target signals and attempting in removing them from images is essential. One method for measuring and removing non-target signals is that of atmospheric correction by Dark Object Subtraction (DOS). This method is based on the sensor’s output for the targets that should have almost zero reflectance in a given band. Next, the obtained value will be deducted from the remaining pixels values; regardless of the type of the sensors. Each Charge-Coupled Device (CCD) has its own noise behavior; therefore, the amount deducted values from each pixel can be different for each CCD unit and type. Among the various noises of the CCD and their related electronic circuits, dark current noise, non-uniform pixels noise and read noise were selected to be studied in this paper. The data were obtained from multispectral sensor images of IKONOS. This sensor can provide images in two forms of Panchromatic (PAN) and Multispectral (MS). The results of this study showed that the amount of dark object pixels and the total amount of CCD noises in each band are different. Separation of the noises introduced in this paper from the amount of dark object pixel values can result in an upgraded method for image atmosphere corrections.