QUANTIZATION CONSTRAINED NEURAL IMAGE CODING
Artificial image generation may include obtaining a source image, identifying quantization information from the source image, wherein identifying the quantization information includes identifying multiresolution quantization interval information from the source image, generating a restoration filter...
Saved in:
Main Authors | , |
---|---|
Format | Patent |
Language | English |
Published |
10.02.2022
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Artificial image generation may include obtaining a source image, identifying quantization information from the source image, wherein identifying the quantization information includes identifying multiresolution quantization interval information from the source image, generating a restoration filtered image by restoration filtering the source image, generating a constrained restoration filtered image by constraining the restoration filtered image based on the quantization information, obtaining an unconstrained artificial image based on the constrained restoration filtered image and a generative artificial neural network obtained using a generative adversarial network, obtaining the artificial image by constraining the unconstrained artificial image based on the quantization information, and outputting the artificial image. |
---|---|
Bibliography: | Application Number: US202117505819 |