Spectral-based approach to subpixel image formation

: pp. 87-92
Lviv Polytechnic National University
Lviv Polytechnic National University
Lviv Polytechnic National University
Lviv Polytechnic National University
Lviv Polytechnic National University

Current approach to the increase of the resolution is based on receiving images from several image sensor arrays shifted by subpixel distance [1, 2]. The analysis of the image forming process has shown that a pixel aperture works as a low-pass spatial filter and decreases spatial resolution even if several image sensors shifted by subpixel distance are used. The proposed by the authors approach uses both shifted image sensor arrays and data processing based on inverse filtering. That technique is more advantageous in comparison to existing approaches based on image sensors positioning or masks.

The main results of the investigation are: discussion of problems of increase in the resolution of remote sensing; simulation of the image forming process for estimation of the impact of a pixel aperture on the image forming process; a new technique for eliminating the influence of a pixel aperture.

The simulation performed on the basis of the proposed approach has shown that it is possible to get a restored image with the resolution almost similar to the resolution of a test high-resolution image, what indicates the effective reduction of the influence of the pixel aperture. It has been shown that for a blurred test image received by using the aperture of 8 pixels its normalized absolute error is of 0.123 and for a restored by inverse filter image its error reduces to 0.019.

  1. S. Blazhevych, V. Vintaev, and N. Ushakova, “Synthesis of space image with improved resolution on the basis of sub-pixel scanning ”, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, vol. 13, №2, pp. 9 – 13, Moscow, Russia, 2010. (Russian)
  2. S. Blazhevych, V. Vintaev,  N. Ushakova, E. Selyutina,  “Synthesis of digital images of sub-pixel resolution level using the defocusing ”, Mekhanika, upravlenie i informatika, pp. 127-136, Moscow, Russia, 2012. (Russian)
  3. G. Vasylenko and A. Taratorin, Image Restoration. Moscow, Russia: Radio i svyaz, 1986. (Russian)
  4. V. Gornyj, M. Kislitskiy, and I. Latypov, “ Evaluating the effectiveness of algorithms of synthetic aperture scanning radiometer”. In Sovremennye problemy distantsionnogo zondiro­vaniya Zemli iz kosmosa. Fizicheskie osnovy, metody i tehnologii monitoringa okruzhayushhey sredy, potentsialno opasnykh yavleniy i obyekto, vol. 7, №2, pp. 14-25, Мoscow, Russia: Uchrezhdenie Rossijskoj akademii nauk Institut kosmicheskih issledovanij RAN, 2010.
  5. S. Blazhevych, V. Vintaev,  N. Ushakova, and V. Shakov, “Synthesis of space image with improved resolution on the basis of sub-pixel scanning”, in Proc. VII-th Russian open annual conference, p. 18, Moscow, Russia, IKI RAN, 2009. (Russian)
  6. E. Selyutina and S. Blazhevych, “Increasing the resolution of digital images using sub-pixel scanning”, Nauchnyy aspekt, № 1, p. 204, Samara, Russia: «Aspekt», 2013. (Russian)
  7. S. Gao, X. Zhang, and W. Sun,  Lossless inter-array predictive coding for subpixel-shifted satellite images based on texture analysis, in Proc. 12th Int. Conf. on Geoinformatics − Geospatial Information Research: Bridging the Pacific and Atlantic, pp. 275-276, Gävle, Sweden, 2004.