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Atmospheric influence on the different radio-engineering system functioning

ESTIMATION OF ATMOSPHERIC OPTICAL CHARACTERISTICS AND REMOTELY SANSED IMAGE CORRECTION

           During a long time the possibility to estimate the atmosphere optical parameters using remotely sensed images only has been under studying in our Institute. The attempts have been made to estimate such atmospheric parameters as the atmospheric optical depth τ (or the direct transmittance Tp=exp(-τ)) and the Normalized Atmospheric Point Spread Function (NAPSF). 

ESTIMATION OF THE ATMOSPHERIC OPTICAL DEPTH

 Our method of estimating the atmospheric optical depth (the direct transmittance) is based on the comparison between the values of sampling variances for radiances of all pixels on two images for the same area received at two different angles of observation [1].

From analyzing the error of this estimation method we can see that in the case of a uniform field of Lambertian reflectance the estimate agrees with the true value of the atmospheric optical depth. The deviation of the surface from the Lambertian one gives rise to the error in estimation of optical depth. Since the angle scattering properties of real surfaces on images are unknown and a quality of the estimates is not controlled, we have to draw the conclusion that the estimate of the atmospheric optical depth (the direct transmittance) using two images acquired at two angles of observation is not suitable in practice.

The situation becomes more preferable if we have images of the same site acquired for several angles of observation as in the case of the CHRIS spectrometer for example. We have managed to develop the controllable procedure of the atmospheric optical depth (direct transmittance) estimation using images for several angles of observation [2].

In Fig.1 you can see the direct transmittance estimates obtained by us for the first twelve spectral channels of the CHRIS sensor.* Here we also depicted the average values of the atmospheric direct transmittances for the same twelve spectral channels of the CHRIS as the results of simulation by means of the LOWTRAN model for four assumed aerosol conditions. Comparing the estimates obtained with the simulation results we can see their similarity on the whole. We think that this preliminary result is hopeful and we are ready to collaborate with the researcher who is interested in this subject.

 

Fig. 1. Direct transmittance estimation results for 12 channels of the spectrometer CHRIS.

 

ESTIMATION OF THE NAPSF

 It’s known that the atmosphere can be considered as a passive linear low-pass spatial filter that smoothes the images of the Earth (so-called “adjacency effect”). Such filter-atmosphere is completely determined by its Atmospheric Point Spread Function (APSF). We have managed to develop a direct method of estimating the discrete Normalized Atmospheric Point Spread Function (NAPSF) from available images alone, not using any external sources of information about the atmosphere. Knowledge of the NAPSF enables us to synthesize the correction filter, which is able to remove the adjacency effect from remotely sensed data.

Detailed description of the NAPSF estimation method and adjacency effect correction suggested by us can be found in [3-4].

Figure 2 shows the result of adjacency effect correction for a fragment (512x512) of a real image acquired in 2nd spectral channel (0.546μm – 0.556μm) of the spaceborne CHRIS sensor. The original fragment is shown in the left picture, while the result of image correction is depicted in the right frame.

Fig.2.

Figure 3 shows a fragment (512x512) of the original image acquired in sixth spectral channel (0.54μm) of the airborne hyperspectral sensor MIVIS (left picture) and the outcome of the correction filtering (restored image) (right picture).*

Fig.3.

We are open to any form of collaboration with specialists on the atmospheric point spread function estimation problem and adjacency effect correction.

 References

  1. A.A. Semenov, “Estimation of atmospheric correction parameters in analyzing of multispectral scanner images”, The Earth research from space, no.2, pp.38 – 45, (2002). (Russian edition).

  2. A.V. Moshkov, V.N. Pozhidaev, and A.A. Semenov, “Estimation of the transparency from the Earth’s surface images obtained in optical range at different angles”, Journal of communications technology and electronics (English translation of Radiotekhnika i electronika), v. 54, no. 9, pp.1000 – 1002 (2009).

  3. A.A. Semenov, “Correction of the scanner image distortions due to the adjacenc effect”, The Earth research from space, 1, pp.35 – 48 (2004) (Russian edition).

  4. A.A. Semenov, A.V. Moshkov, V.N. Pozhidaev, A. Barducci, P. Marcoionni, and I. Pippi, “Estimation of the normalized atmospheric point spread function and restoration of remotely sensed images”, IEEE Trans. Geosci. Rem. Sens., vol.49, no.7,pp. 2623 – 2634 (2011).

 

* Applicable CHRIS and MIVIS images were kindly presented by our colleagues from the Instituto di Fisica Applicata “Nello Carrara”, Florence, Italy.

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Contact address:
Alexander Semenov: E-mail:   san@cplire.ru
Victor Pozhidayev: E-mail:  
vic@cplire.ru

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