Unsupervised learning approach for video deblurring
AssigneeNVIDIA Corporation
InventorsJinwei Gu, Orazio Gallo, Ming-Yu Liu, Jan Kautz, Huaijin Chen
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Abstract
An image processing method extracts consecutive input blurry frames from a video, and generates sharp frames corresponding to the input blurry frames. An optical flow is determined between the sharp frames, and the optical flow is used to compute a per-pixel blur kernel. The blur kernel is used to reblur each of the sharp frames into a corresponding re-blurred frame. The re-blurred frame is used to fine-tune the deblur network by minimizing the distance between the re-blurred frame and the input blurry frame.
Claims20
An image processing method comprising:
- extracting a plurality of consecutive input blurry frames from a video;
- generating a plurality of sharp frames, each of the sharp frames corresponding to one of the input blurry frames;
- determining an optical flow between the sharp frames;
- applying the optical flow to compute a per-pixel blur kernel;
- and
- applying the blur kernel to reblur each of the sharp frames into a corresponding re-blurred frame.
An image processing apparatus comprising:
- a graphics processing unit;
- and
- logic to configure the graphics processing unit to:
- extract a plurality of consecutive input blurry frames from a video;
- generate a plurality of sharp frames, each of the sharp frames corresponding to one of the input blurry frames;
- determine an optical flow between the sharp frames;
- apply the optical flow to compute a per-pixel blur kernel;
- and
- apply the blur kernel to reblur each of the sharp frames into a corresponding re-blurred frame.
Dependencies are inferred from the claim text.