M.A. Pantyukhin – Ph.D.(Eng.), Head of Research and Development Laboratory, 

MESC «Zhukovsky–Gagarin Air Force Academy» (Voronezh)

E-mail: ol-max@mail.ru

A.V. Bogoslovsky – Honored Scientist of RF, Dr.Sc.(Eng.), Professor, 

Department of Radioelectronics, MESC «Zhukovsky–Gagarin Air Force Academy» (Voronezh) E-mail: p-digim@mail.ru

I.V. Zhigulina – Ph.D.(Eng.), Associate Professor, Professor, 

Department of Mathematics, MESC «Zhukovsky–Gagarin Air Force Academy» (Voronezh) E-mail: ira_zhigulina@mail.ru

The features of two-dimensional discrete filtering of the simplest objects are shown. The influence of the filter aperture, dimension and contrast of the prototype and the object, the prototype’s background for the type and polarity of the processed image’s signal are diagnosted. Recommendations for selecting the preferred apertures, dimension and prototype’s contrast are formulated. The results of the real image processing using a simplest prototype are shown.

Two-dimensional discrete Winner-Hopf filtering allows to select images of objects on an arbitrary background. It includes a stage of spatial image processing using a two-dimensional filter, the impulse response is calculated based on the properties of the processed image and a prototype of an object interest.

The aim of the article is to study the main features of two-dimensional discrete filtering based on the analysis of the simplest test images processing results. These images contain a segment of a straight horizontal line and a rectangle. The paper presents typical variants of the video signal of the processed image, as well as the results of image processing in case of coincidence of the prototype’s shape and the object of interest, with the characteristic apertures and preferred intervals of their variety.

Shows the effect of mismatch of the size of the reference object on the processing results, the impact of the background of the reference and input image, and the relative contrast of the reference object and the magnitude and polarity of the video signal. It is shown that the polarity of the video signal of the processed image is independent of the contrast of the standard. The real image processing results are illustrated and the main results are formulated.

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2. Yane B. Tsifrovaya obrabotka izobrazhenii. M.: Tekhnosfera. 2007. 581 s. (in Russian)
3. Obrabotka mnogomernykh signalov. V dvukh knigakh. Kn. 1. Lineinaya mnogomernaya diskretnaya obrabotka signalov. Metody analiza i sinteza. Pod red.A.V. Bogoslovskogo. M.: Radiotekhnika. 2013. 168 s. (in Russian)
4. Bogoslovskii A.V., Pantyukhin M.A., Zhigulina I.V. Vybor apertury filtra pri soglasovannoi so svoistvami vkhodnogo izobrazheniya filtratsii verkhnikh prostranstvennykh chastot. Radiotekhnika. 2016. T. 33. № 10. S. 128−133. (in Russian)
5. Bogoslovsky A.V., Zhigulina I.V. A Way of Energy Analysis for Image and Video Sequence Processing. Intelligent Systems Reference Library. V. 73. Computer Vision in Control Systems-1. Mathematical Theory. Springer. 2015. P. 183−210. DOI 10.1007/978-3-31910653-3.
6. Pantyukhin M.A., Roslyakov F.A., Pisarev Yu.V. Algoritm opredeleniya razmerov etalonov dlya raspoznavaniya obrazov ob’ektov na izobrazheniyakh pri nadirnoi s’emke. Materialy Mezhdunar. nauchno-tekhnich. konf. «Fundamentalnye problemy radioelektronnogo priborostroeniya» (INTERMATIC–2018). 19–23 noyabrya 2018, Moskva. Pod red. akademika RAN A.S. Sigova. M.: RTU MIREA. 2018. Ch. 4. S. 993−996. (in Russian)
7. Foto avtomobilnoi razvyazki. URL: https://www.motorists.org/wp-content/ uploads/2015/09/DN-thumbnail-high-five-interchange.jpg (data obrashcheniya: 20.11.2019).