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...

Full description

Saved in:
Bibliographic Details
Main Authors Toderici, George, Alakuijala, Jyrki
Format Patent
LanguageEnglish
Published 10.02.2022
Subjects
Online AccessGet full text

Cover

Loading…
More Information
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