Leveraging Classic Deconvolution and Feature Extraction in Zero-Shot Image Restoration-Reference-Cited by-同舟云学术

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Leveraging Classic Deconvolution and Feature Extraction in Zero-Shot Image Restoration

Published:2023-10-02 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
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Author:

Chobola Tomáš¹,Müller Gesine²,Dausmann Veit³,Theileis Anton³,Taucher Jan³,Huisken Jan²,Peng Tingying⁴

Affiliation:

1. Technical University of Munich,Munich,Germany

2. Georg-August-University Göttingen,Göttingen,Germany

3. GEOMAR Helmholtz Centre for Ocean Research Kiel,Kiel,Germany

4. Helmholtz Munich - German Research Center for Environmental Health,Helmholtz AI,Neuherberg,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10350357/10350360/10350608.pdf?arnumber=10350608

Reference54 articles.

1. Generation of annotated multimodal ground truth datasets for abdominal medical image registration

2. Image restoration: Total variation, wavelet frames, and beyond

3. Self-Supervised Blind Image Deconvolution via Deep Generative Ensemble Learning

4. LUCYD: A Feature-Driven Richardson-Lucy Deconvolution Network

5. A modified damped Richardson–Lucy algorithm to reduce isotropic background effects in spherical deconvolution

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