Invention Grant
- Patent Title: Tiled image compression using neural networks
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Application No.: US16617484Application Date: 2018-05-29
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Publication No.: US11250595B2Publication Date: 2022-02-15
- Inventor: Michele Covell , Damien Vincent , David Charles Minnen , Saurabh Singh , Sung Jin Hwang , Nicholas Johnston , Joel Eric Shor , George Dan Toderici
- Applicant: GOOGLE LLC
- Applicant Address: US CA Mountain View
- Assignee: GOOGLE LLC
- Current Assignee: GOOGLE LLC
- Current Assignee Address: US CA Mountain View
- Agency: Fish & Richardson P.C.
- International Application: PCT/US2018/034933 WO 20180529
- International Announcement: WO2018/218249 WO 20181129
- Main IPC: G06T9/00
- IPC: G06T9/00 ; G06N3/04 ; G06N3/08 ; G06T3/40 ; G06T7/00

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for image compression and reconstruction. An image encoder system receives a request to generate an encoded representation of an input image that has been partitioned into a plurality of tiles and generates the encoded representation of the input image. To generate the encoded representation, the system processes a context for each tile using a spatial context prediction neural network that has been trained to process context for an input tile and generate an output tile that is a prediction of the input tile. The system determines a residual image between the particular tile and the output tile generated by the spatial context prediction neural network by process the context for the particular tile and generates a set of binary codes for the particular tile by encoding the residual image using an encoder neural network.
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