Two-stage filtration algorithm with interframe causal processing for multichannel image with presence of uncorrelated noise

Authors

  • O. M. Liashuk National Technical University of Ukraine, Kyiv Politechnic Institute, Kiev
  • S. V. Vishnevyy National Technical University of Ukraine, Kyiv Politechnic Institute, Kiev
  • S. Ya. Zhuk National Technical University of Ukraine, Kyiv Politechnic Institute, Kiev http://orcid.org/0000-0002-0046-8450

DOI:

https://doi.org/10.20535/RADAP.2015.63.46-54

Keywords:

multi-channel image, image filtration, combine estimates, posteriori probability density, random field

Abstract

Introduction. When solving a number of practical problems the usage of multichannel images is common practice. Multichannel of this data permits or increases the efficiency of solving the problem, or allows to obtain useful information, which in principle cannot be extracted from the single-channel images. One of the main types of noise occurring in a multichannel image is uncorrelated noise. The optimal image filtering algorithms require enormous computational cost. Therefore, the important practical value is the synthesis of multi-channel image filtering algorithms, providing the required performance indicators at moderate computational cost.
Theoretical results. Using conditional independence properties, the expression for the a posteriori probability density of pixels at the two-stage multi-channel image filtration with causal frame processing in the presence of uncorrelated noise is obtained. Gaussian algorithm for determining the estimates of image pixels and error variance estimation with causal intra and inter-frame processing is obtained in the case of multichannel image.
Experimental results. The developed algorithm for considered example allows increasing the filtration accuracy of the sequence of homogeneous Gaussian images on a 20% - 45% compared to inter-frame averaging algorithm.
Conclusion. Optimal and quasi-two-stage multi-channel image filtration algorithms were synthesized. In algorithms the first stage is one-dimensional causal filtration along each of the coordinates, and the second is the union of the results. These algorithms allow reducing the computational cost in comparison with the optimal algorithm and thus ensuring acceptable accuracy characteristics.

Author Biographies

O. M. Liashuk, National Technical University of Ukraine, Kyiv Politechnic Institute, Kiev

Liashuk O. M., M.S. , Postgraduate student

S. V. Vishnevyy, National Technical University of Ukraine, Kyiv Politechnic Institute, Kiev

Vishnevyy S. V., Cand. of Sci(Techn)

S. Ya. Zhuk, National Technical University of Ukraine, Kyiv Politechnic Institute, Kiev

Zhuk S. Ya., D. of Sci(Techn.), Prof.

References

Перечень источников

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References

Lukin V. V. (2011) Tsifrovaya obrabotka signalov i ee primenenie [Modern methods and problems of multi-channel image filtering]. Tsifrovaya obrabotka signalov i ee primenenie [Digital signal processing and its application], Iss. XIII-1, Vol. 1., Moskow, pp. 3-6.

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Vishnevyy, S. V., Zhuk, S. Ya. (2010) Algorithm of uniting of optimal one-dimensional filtering outcomes for image processing.Visn. NTUU KPI, Ser. Radioteh. radioaparatobuduv., no. 40, pp. 55-60. (in Ukrainian).

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Borzov S. M. and Uzilov S. B. (2013) Development of multiframe noise reduction algorithm for mobile thermalvision systems. Vestnik NGU. Seriya – Informatsionnye tekhnologii, Vol. 11, No. 1, pp. 16–23. (in Russian)

Published

2015-12-30

How to Cite

Ляшук, А. Н., Вишневый, С. В. and Жук, С. Я. (2015) “Two-stage filtration algorithm with interframe causal processing for multichannel image with presence of uncorrelated noise”, Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, 0(63), pp. 46-54. doi: 10.20535/RADAP.2015.63.46-54.

Issue

Section

Computing methods in radio electronics

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