2022年9月10日
Single-pixel imaging for edge images using deep neural networks
Applied Optics
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- 巻
- 61
- 号
- 26
- 開始ページ
- 7793
- 終了ページ
- 7797
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1364/AO.468100
Edge images are often used in computer vision, cellular morphology, and surveillance cameras, and are sufficient to identify the type of object. Single-pixel imaging (SPI) is a promising technique for wide-wavelength, low-light-level measurements. Conventional SPI-based edge-enhanced techniques have used shifting illumination patterns; however, this increases the number of the illumination patterns. We propose two deep neural networks to obtain SPI-based edge images without shifting illumination patterns. The first network is an end-to-end mapping between the measured intensities and entire edge image. The latter comprises two path convolutional layers for restoring horizontal and vertical edges individually; subsequently, both edges are combined to obtain full edge reconstructions, such as in the Sobel filter.
- リンク情報
- ID情報
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- DOI : 10.1364/AO.468100
- ISSN : 1559-128X
- eISSN : 2155-3165
- PubMed ID : 36256382
- SCOPUS ID : 85137718577