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Космические корабли и станции, автоматические КА и методы их проектирования, бортовые комплексы управления, системы и средства жизнеобеспечения, особенности технологии производства ракетно-космических систем

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Применить Всего найдено 2. Отображено 2.
25-04-2023 дата публикации

Photoelectric imaging system and imaging method thereof

Номер: CN116017123A
Автор: ZHANG RUIWEN, WANG KANG, WANG YONGQIANG, FAN QIANG, LIU SONG, CHOURAND
Принадлежит:

A photoelectric imaging system disclosed by the present invention comprises an imaging system control unit, a gyroscope angle measurement unit, a photoelectric imaging unit and a signal processing unit, the control unit controls synchronous cooperative work of the gyroscope angle measurement unit and the photoelectric imaging unit, and the gyroscope angle measurement unit outputs a camera Euler angle to the signal processing unit. The photoelectric imaging unit outputs an original image to the signal processing unit, the gyroscope angle measurement unit outputs attitude information of the photoelectric system, the image signal real-time processing unit carries out fusion enhancement processing on continuous image frames, and the signal processing unit outputs an image. The invention further discloses a photoelectric imaging method. According to the method, multiple times of exposure are adopted, image information fusion is carried out on the time domain by integrating angle measurement ...

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Номер записи: 1
07-04-2023 дата публикации

Image super-resolution reconstruction method based on high-order degradation cycle generative adversarial network

Номер: CN115936985A
Автор: ZHANG ZHIJIE, CHOURAND, LEI BO
Принадлежит:

The invention discloses an image super-resolution reconstruction method based on a high-order degradation cyclic generative adversarial network, and the method comprises the steps: generating a low-resolution image for a high-resolution image through employing a high-order image degradation model, forming an image pair, constructing a cyclic generative network model, and carrying out the reconstruction of a high-order degradation cyclic generative adversarial network. The method comprises the following steps of: generating a low-resolution image to a high-resolution image by utilizing a generator, judging, constructing a network loss function, ensuring the stability of an established mapping relation through a classic GAN network loss function and a cyclic invariant Cycle loss function, finally training a network model, configuring various hyper-parameters, and establishing a high-resolution image. And the network can be converged to obtain a better generation effect. Compared with a traditional ...

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Номер записи: 2