title: ÐÐ¾Ð²ÑÑÐµÐ½Ð¸Ðµ ÐºÐ°ÑÐµÑÑÐ²Ð° ÑÐ°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹ Ð·Ð° ÑÑÑÑ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ð¸ Ð¼ÑÐ»ÑÑÐ¸Ð¿Ð»Ð¸ÐºÐ°ÑÐ¸Ð²Ð½Ð¾Ð³Ð¾ ÑÑÐ¼Ð° Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Improving the quality of radar images by filtering multiplicative noise using deep learning methods
Creators: name: ÐÐ°ÑÐ°ÑÐµÐ², ÐÐ°Ð´Ð¸Ð¼
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: ÑÐ°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ðµ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ðµ
ÑÐ°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ðµ ÑÐ¸Ð½ÑÐµÐ·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð°Ð¿ÐµÑÑÑÑÑ
Ð¼ÑÐ»ÑÑÐ¸Ð¿Ð»Ð¸ÐºÐ°ÑÐ¸Ð²Ð½ÑÐ¹ ÑÑÐ¼
ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ñ ÑÐ¿ÐµÐºÐ»-ÑÑÐ¼Ð°
Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÑ ÑÐ¸Ð»ÑÑÑÐ¾Ð²
Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð¾Ð¿ÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ðµ
Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
radar image
synthetic aperture radar
multiplicative noise
speckle noise filtering
filter parameters
neural networks
optical image
deep learning

description: ÐÐ±ÑÐµÐºÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ â ÑÐ°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½ÑÐµ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ. Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ â ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¸ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ð¸ Ð¼ÑÐ»ÑÑÐ¸Ð¿Ð»Ð¸ÐºÐ°ÑÐ¸Ð²Ð½Ð¾Ð³Ð¾ ÑÐ¿ÐµÐºÐ»-ÑÑÐ¼Ð° Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ñ ÐºÐ°ÑÐµÑÑÐ²Ð° ÑÐ°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹. ÐÐ»Ñ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ð¸ Ð¼ÑÐ»ÑÑÐ¸Ð¿Ð»Ð¸ÐºÐ°ÑÐ¸Ð²Ð½Ð¾Ð³Ð¾ ÑÐ¿ÐµÐºÐ»-ÑÑÐ¼Ð° Ð½Ð° ÑÐ°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸ÑÑ ÑÐ¿ÑÐ¾ÐµÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ñ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÐµ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑÑ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹. ÐÑÐµÐ½ÐºÐ° ÑÐ°Ð±Ð¾ÑÑ Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½ÑÑ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð¿ÑÐ¾Ð²Ð¾Ð´Ð¸Ð»Ð°ÑÑ Ð¿ÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ ÑÐ¿ÐµÑÐ¸Ð°Ð»ÑÐ½ÑÑ Ð¼ÐµÑÑÐ¸Ðº ÐºÐ°ÑÐµÑÑÐ²Ð° Ð½Ð° ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½Ð¾Ð¼ Ð½Ð°Ð±Ð¾ÑÐµ Ð´Ð°Ð½Ð½ÑÑ. Ð¢Ð°ÐºÐ¶Ðµ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¾ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð° Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐµÑÐºÐ¸Ð¼Ð¸ Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸. ÐÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¸ÑÑ Ð¾ÑÐºÑÑÑÑÐµ Ð¾Ð±ÑÐ°Ð·Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½ÑÐµ ÑÐµÑÑÑÑÑ Ð¸ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ñ Ð¿Ð¾Ð¸ÑÐºÐ° Ð¸ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¸. ÐÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¸ÑÑ ÑÑÐµÐ´ÑÑÐ²Ð° Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð°ÑÐ¸Ð¸ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸: Python. ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¾ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ðµ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ðµ: MATLAB. Ð ÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð¼ ÑÐ²Ð»ÑÐµÑÑÑ Ð¾Ð±ÑÑÐµÐ½Ð½Ð°Ñ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸, ÐºÐ¾ÑÐ¾ÑÐ°Ñ Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÐµÑ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ ÑÐ´Ð°Ð»ÑÑÑ Ð¼ÑÐ»ÑÑÐ¸Ð¿Ð»Ð¸ÐºÐ°ÑÐ¸Ð²Ð½ÑÐ¹ ÑÑÐ¼ Ñ ÑÐ°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹, ÑÐµÐ¼ ÑÐ°Ð¼ÑÐ¼ Ð¿Ð¾Ð²ÑÑÐ°Ñ Ð¸Ñ ÐºÐ°ÑÐµÑÑÐ²Ð¾.
description: The given work is devoted to developing and apply algorithms for filtering multiplicative speckle noise based on deep learning methods to improve the quality of radar images. Various artificial neural networks have been designed to filter multiplicative speckle noise on radar images. The evaluation of the work of the obtained models was carried out using special quality metrics on the developed data set. The neural network approach is also compared with classical methods. Open educational resources and information search and analysis programs were used. Development automation tools were used: Python. Software used: MATLAB. The result is a trained neural network model that effectively removes multiplicative noise from radar images, thereby improving their quality.