V.E. Dmitriyev, D.V. Popov, V.A. Shakhnov
Bauman Moscow State Technical University (Moscow, Russia)
This article deals with the digital processing of a matrix radar image. The information received from the radar scanner needs to be transformed to enable visual perception. The article describes the main methods of digital processing of matrix data, presents the images transformed by them.
The aim of the article was the development of a radar data processing algorithm that identifies the contours and edges of examined objects.
The authors propose an algorithm for isolating the geometric structure of the scanned area. The difference between the processing method and the known analogues is based on the nature of the change in the values of the array being processed and consists in the double operation of extracting the gradient of the distribution of values. The software implementation of the algorithm is made in C++ using methods from an open library of computer vision. The efficiency of the algorithm was estimated based on comparison with the algorithms for determining edges based on linear filtering and neural networks.
The results of the work can be used to create software for mobile short-range radar devices. Imaging from object boundaries and their edges provides spatial perception of the image by the operator, and free areas are available for rendering additional information. This solution allows you to combine scanning devices and thereby increase the information value of the result.
Dmitriev V.E., Popov D.V., Shakhnov V.A. Neural network processing of radar scanning data array. Neurocomputers. 2021. V. 23. № 4. Р. 14−24. DOI: https://doi.org/10.18127/j19998554-202104-02 (in Russian).
- Soyfer V.A. Kompyuternaya obrabotka izobrazheniy Chast 1. Matematicheskiye modeli. Sorosovskiy obrazovatelnyy zhur-nal. № 2. 1996. S. 118–124 (in Russian).
- Dmitriyev V.E., Popov D.V. Analiz nosimykh sredstv dlya infrakrasnoy termografii. Tekhnologii inzhenernykh i informa-tsionnykh sistem. 2018. № 2. C. 66–77 (in Russian).
- Gridnev V.N., Sergeyeva M.D., Chebova A.I. Lineynyye modeli raspoznavaniya teplovizionnykh izobrazheniy neis- pravnostey elektronnykh yacheyek. Kontrol. Diagnostika. 2014. № 8. S. 57–66 (in Russian).
- Gridnev V.N., Vlasov A.I., Panfilova S.P., Chervinskiy A.S. Beskontaktnyy teplovoy kontrol elektronno-vychislitelnykh sredstv. Tekhnologiya i konstruirovaniye v elektronnoy apparature. 2007. № 6 (72). S. 42–49 (in Russian).
- Gridnev V.N., Vlasov A.I., Panfilova S.P., Chervinskiy A.S. Beskontaktnyy teplovoy kontrol izdeliy elektronnoy tekhni-ki. Proizvodstvo elektroniki. 2007. № 3. S. 25–30 (in Russian).
- Viryasova A.Yu., Vlasov A.I., Gladkikh A.A. Neyrosetevyye metody defektoskopii integralnykh struktur. Neyro- kompyute-ry: razrabotka. primeneniye. 2019. № 2. S. 54–67 (in Russian).
- Buyanov A.I., Vlasov A.I., Zagoskin A.V. Primeneniye neyrosetevykh metodov pri defektoskopii pechatnykh plat. Neyrokom-pyutery: razrabotka. primeneniye. 2002. № 3. S. 42–70 (in Russian).
- Gridnev V.N., Vlasov A.I., Konstantinov P., Yudin A.V. Neyrosetevyye metody defektoskopii pechatnykh plat. Elektronnyye komponenty. 2004. № 8. S. 148–155 (in Russian).
- Averianikhin A.E., Vlasov A.I., Evdokimova E.V. Ierarkhicheskaya piramidalnaya subdiskretizatsiya v glubokikh svertochnykh setyakh dlya raspoznavaniya vizualnykh obrazov. Neyrokompyutery: razrabotka. primeneniye. 2021. T. 23. № 1. S. 17–31 (in Russian).
- Dulevich V.E. Teoreticheskiye osnovy radiolokatsii. M.: Sov. radio. 1964. 732 s (in Russian).
- Baldina E.A. Zatopleniye territoriy po snimkam TanDEM-X i Landsat-5/TM. Pavodok na reke Amur letom-osenyu 2013 g. – [Elektronnyy resurs] – URL: http://geogr.msu.ru/cafedra/karta/materials/radiolocation/files/2razd/2.5.practice_amur.html (data ob-rashcheniya: 15.04.2019) (in Russian).
- Konovalov A.A. Osnovy trayektornoy obrabotki radiolokatsionnoy informatsii v 2 ch. SPb.: Izd-vo SPbGETU «LETI». 2013. Ch. 1. 164 s (in Russian).
- Informatsionnyye tekhnologii v radiotekhnicheskikh sistemakh / Pod red. I.B. Fedorova. M.: Izd-vo MGTU im. N.E. Baumana. 2011. 848 s (in Russian).
- Ovtsynova V.V. Sravnitelnyy analiz algoritmov poiska granits. Nauchnoye soobshchestvo studentov XXI stoletiya. Tekhniche-skiye nauki: sb. st. po mat. XXXII mezhdunar. stud. nauch.-prakt. konf. № 5(31). URL: http://sibac.info/archive/technic/5(31).pdf (data obrashcheniya: 14.04.2019) (in Russian).
- Tr. vseros. konf. «Obrabotka prostranstvennykh dannykh v zadachakh monitoringa prirodnykh i antropogennykh protsessov». Novosibirsk. 2017. 323 s (in Russian).
- Novotortsev L.V., Voloboy A.G. Algoritm nakhozhdeniya otrezkov v zadache analiza aerofotosnimkov. Privolzhskiy nauchnyy zhurnal. 2014. № 4. S. 170–172 (in Russian).
- Ezhova K.V. Modelirovaniye i obrabotka izobrazheniy. Uchebnoye posobiye. SPb.: NIU ITMO. 2011. 93 s (in Russian).
- Tsai S. Effects of 2-D Preprocessing on Feature Extraction Accentuating Features by Decimation. Contrast Enhancement. Filtering. Department of Electrical Engineering. Stanford University. 2008.
- Zhivrin Ya.E., Alkzir N.B. Metody opredeleniya obyektov na izobrazhenii. Molodoy uchenyy. 2018. № 7. S. 8–19 (in Russian).
- Bondarenko A.Yu., Adamov V.G. Analiz metodov opredeleniya konturov izobrazheniya. Mezhdunarodnyy nauchno-issledovatelskiy zhurnal. 2015. №8 (39) Ch. 2. S. 13–16 (in Russian).
- Pitenko A.A. Ispolzovaniye neyrosetevykh tekhnologiy pri reshenii analiticheskikh zadach v GIS. Sb. nauch. trudov «Metody neyroinformatiki». Krasnoyarsk: KGTU. 1998. S. 152–163 (in Russian).
- Markova S.V., Zhigalov K.Yu. Primeneniye neyronnoy seti dlya sozdaniya sistemy raspoznavaniya izobrazheniy. Fundamen-talnyye issledovaniya. 2017. № 8–1. S. 60–64 (in Russian).
- Vlasov A.I., Papulin S.Yu. Analiz dannykh s ispolzovaniyem gistogrammnoy modeli kombinatsii priznakov. Neyrokomp-yutery: razrabotka. primeneniye. 2019. T. 21. № 5. S. 18–27 (in Russian).
- Smirnov A.V., Ivanov E.S. Ispolzovaniye mekhanizma svertochnykh neyronnykh setey dlya poiska obyektov na aerofotosnimkakh. Programmnyye sistemy: teoriya i prilozheniya. 2017. T. 8. Vyp. 4. S. 85–99 (in Russian).
- Rysmyatova A.A. Ispolzovaniye svertochnykh neyronnykh setey dlya zadachi klassifikatsii tekstov. M.: Izd-vo MGU im. M.V. Lomonosova. 2016 (in Russian).
- Prokhorov V.G. Ispolzovaniye svertochnykh setey dlya raspoznavaniya rukopisnykh simvolov. Problemi programuvaniya. 2008. № 2–3. S. 669–674 (in Russian).
- Xie S., Tu Z. Holistically-Nested Edge Detection. 2015. – [Elektronnyy resurs] – URL: https://arxiv.org/abs/1504.06375 (data obrashcheniya: 20.04.2019) (in Russian).
- Pitenko A.A. Ispolzovaniye neyrosetevykh tekhnologiy pri reshenii analiticheskikh zadach v GIS. Sb. nauch. trudov «Metody neyroinformatiki». Krasnoyarsk: Izd-vo KGTU. 1998. S. 152–163 (in Russian).
- Markova S.V., Zhigalov K.Yu. Primeneniye neyronnoy seti dlya sozdaniya sistemy raspoznavaniya izobrazheniy. Fundamen-talnyye issledovaniya. 2017. № 8–1. S. 60–64 (in Russian).
- Glushko A.A., Busov V.D., Perederin K.D. Metody algoritmicheskogo proyektirovaniya iskusstvennogo intellekta. Tekhnologii inzhenernykh i informatsionnykh sistem. 2019. № 2. S. 72–88 (in Russian).
- Shakhnov V.A., Vlasov A.I., Polyakov Yu.A., Kuznetsov A.S. Neyrokompyutery: arkhitektura i skhemotekhnika. Ser. Prilozheniye k zhurnalu «Informatsionnyye tekhnologii». № 9. M.: Mashinostroyeniye. 2000 (in Russian).
- Balukhto A.N., Bulayev V.I., Buryy E.V. i dr. Neyrokompyutery v sistemakh obrabotki izobrazheniy. Ser. Biblioteka zhurnala «Neyrokompyutery: razrabotka. primeneniye». T. 7. M.: Radiotekhnika. 2003 (in Russian).
- Balukhto A.N., Galushkin A.I., Kovalchuk D.V., Nazarov L.E., Tomashevich N.S. Neyrokompyutery v prikladnykh zadachakh ob-rabotki izobrazheniy. Ser. Biblioteka zhurnala «Neyrokompyutery: razrabotka. primeneniye». T. 8. M.: Radiotekhnika. 2003 (in Russian).
- Artemyev B.V., Popov D.V., Dmitriyev V.E. Analiz osobennostey obnaruzheniya obyektov. raspolozhennykh na odnoy osi otno-sitelno nablyudatelya. metodom radiolokatsii v millimetrovom diapazone. Kontrol. Diagnostika. 2019. № 6. S. 42–47 (in Russian).