Wang et al., 2021 - Google Patents
Real-esrgan: Training real-world blind super-resolution with pure synthetic dataWang et al., 2021
View PDF- Document ID
- 16494996782918821323
- Author
- Wang X
- Xie L
- Dong C
- Shan Y
- Publication year
- Publication venue
- Proceedings of the IEEE/CVF international conference on computer vision
External Links
Snippet
Though many attempts have been made in blind super-resolution to restore low-resolution images with unknown and complex degradations, they are still far from addressing general real-world degraded images. In this work, we extend the powerful ESRGAN to a practical …
- 238000006731 degradation reaction 0 abstract description 96
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- G06T2207/20172—Image enhancement details
- G06T2207/20182—Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
- G06T5/001—Image restoration
- G06T5/002—Denoising; Smoothing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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- G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
- G06T3/40—Scaling the whole image or part thereof
- G06T3/4053—Super resolution, i.e. output image resolution higher than sensor resolution
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- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
- G06T5/001—Image restoration
- G06T5/003—Deblurring; Sharpening
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