Deep CNN prior based image reconstruction for multispectral imaging

Date

2020-10-07

Author

Manisali, İrfan
Cam, Refik
Bezek, Can Deniz
Öktem, Sevinç Figen

Metadata

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Spektral görüntüleme, fizik, kimya, biyoloji, tıp, astronomi ve uzaktan algılama gibi farklı alanlarda yaygın olarak kullanılan temel bir tanılayıcı tekniktir. Bu bildiride, hesaplamalı görüntüleme prensibine dayanan ve kırınımlı lens içeren birçoklu spektral görüntüleme tekniğine odaklanılmakta, bunun için evrişimsel sinir ağlarından yararlanan görüntü geriçatım yöntemi geliştirilmektedir. Sistemin elde ettiği ham verilerden spektral görüntülerin geriçatılması için, ters problem düzenlileştirme içeren bir eniyileme problemi olarak formüle edilir. Bu eniyileme problemi yön değiştiren çarpanlar yöntemi ile alt problemlere ayrılır ve gürültüden arındırma problemine karşılık gelen alt problem analitik yöntemler yerine, öğrenme tabanlı evrişimsel gürültüsüzleştirme sinir ağı ile çözülür. Elde edilen sonuçlar önerilen yöntemin umut verici geriçatım performansını ortaya koymaktadır.

Subject Keywords

Evrişimsel sinir ağları, Spektral görüntüleme, Ters problemler, Görüntü oluşturma, Convolutional neural networks, Spectral imaging, Inverse problems, Image reconstruction

URI

https://hdl.handle.net/11511/83911
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9302259

DOI

https://doi.org/10.1109/SIU49456.2020.9302259

Conference Name

28th Signal Processing and Communications Applications Conference, SIU (2020)

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

İ. Manisali, R. Cam, C. D. Bezek, and S. F. Öktem, “Deep CNN prior based image reconstruction for multispectral imaging,” presented at the 28th Signal Processing and Communications Applications Conference, SIU (2020), Gaziantep, Turkey, 2020, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/83911.