Invention Grant
- Patent Title: Efficient use of quantization parameters in machine-learning models for video coding
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Application No.: US16134134Application Date: 2018-09-18
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Publication No.: US10674152B2Publication Date: 2020-06-02
- Inventor: Claudionor Coelho , Dake He , Aki Kuusela , Shan Li
- Applicant: GOOGLE LLC
- Applicant Address: US CA Mountain View
- Assignee: GOOGLE LLC
- Current Assignee: GOOGLE LLC
- Current Assignee Address: US CA Mountain View
- Agency: Young Basile Hanlon & MacFarlane, P.C.
- Main IPC: H04N19/124
- IPC: H04N19/124 ; H04N19/164 ; H04N19/96 ; H04N19/176

Abstract:
A method for encoding an image block includes presenting, to a machine-learning model, the image block and a first value corresponding to a first quantization parameter; obtaining first mode decision parameters from the machine-learning model; and encoding the image block using the first mode decision parameters. The first value results from a non-linear function using the first quantization parameter as input. The machine-learning model is trained to output mode decision parameters by using training data. Each training datum includes a training block that is encoded by a second encoder, second mode decision parameters used by the second encoder for encoding the training block, and a second value corresponding to a second quantization parameter. The second encoder used the second quantization parameter for encoding the training block and the second value results from the non-linear function using the second quantization parameter as input.
Public/Granted literature
- US20200092556A1 Efficient Use of Quantization Parameters in Machine-Learning Models for Video Coding Public/Granted day:2020-03-19
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