SELF-SUPERVISED DEBLURRING

Systems/techniques that facilitate self-supervised deblurring are provided. In various embodiments, a system can access an input image generated by an imaging device. In various aspects, the system can train, in a self-supervised manner based on a point spread function of the imaging device, a machi...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Das, Bipul, Langoju, Rajesh Veera Venkata Lakshmi, Agrawal, Utkarsh, Patil, Bhushan D, Murthy, Prasad Sudhakara
Format: Patent
Sprache:eng
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Beschreibung
Zusammenfassung:Systems/techniques that facilitate self-supervised deblurring are provided. In various embodiments, a system can access an input image generated by an imaging device. In various aspects, the system can train, in a self-supervised manner based on a point spread function of the imaging device, a machine learning model to deblur the input image. More specifically, the system can append to the model one or more non-trainable convolution layers having a blur kernel that is based on the point spread function of the imaging device. In various aspects, the system can feed the input image to the model, the model can generate a first output image based on the input image, the one or more non-trainable convolution layers can generate a second output image by convolving the first output image with the blur kernel, and the system can update parameters of the model based on a difference between the input image and the second output image.