US 11,876,969 B2
Neural-network media compression using quantized entropy coding distribution parameters
Amir Said, San Diego, CA (US)
Assigned to QUALCOMM Incorporated, San Diego, CA (US)
Filed by QUALCOMM Incorporated, San Diego, CA (US)
Filed on Jul. 22, 2022, as Appl. No. 17/814,426.
Claims priority of provisional application 63/267,857, filed on Feb. 11, 2022.
Prior Publication US 2023/0262222 A1, Aug. 17, 2023
Int. Cl. H04N 19/13 (2014.01); H04N 19/42 (2014.01); H04N 19/124 (2014.01); H04N 19/134 (2014.01); H04N 19/136 (2014.01)
CPC H04N 19/13 (2014.11) [H04N 19/124 (2014.11); H04N 19/134 (2014.11); H04N 19/136 (2014.11); H04N 19/42 (2014.11)] 20 Claims
OG exemplary drawing
 
1. A method of coding media data, the method comprising:
determining a probability distribution function parameter for a data element of a data stream coded by a neural-based media compression technique, wherein the probability distribution function parameter is based on a distribution of the data stream wherein the probability distribution function parameter is optimized for quantization,
determining a code vector based on the probability distribution function parameter; and
entropy coding the data element using the code vector.