Invention Grant
- Patent Title: Low-latency vector quantization for data compression
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Application No.: US15658282Application Date: 2017-07-24
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Publication No.: US10230969B2Publication Date: 2019-03-12
- Inventor: Viswanathan Swaminathan , Saayan Mitra , Haoliang Wang
- Applicant: Adobe Systems Incorporated
- Applicant Address: US CA San Jose
- Assignee: Adobe Systems Incorporated
- Current Assignee: Adobe Systems Incorporated
- Current Assignee Address: US CA San Jose
- Agency: Kilpatrick Townsend & Stockton LLP
- Main IPC: H04N19/42
- IPC: H04N19/42 ; H04N19/94 ; H04N21/4147

Abstract:
Various embodiments describe data compression that implements vector quantization. A computer system generates a codebook for the vector quantization by iteratively clustering vectors representative of data that should be compressed. The iterative clustering uses geometric reasoning to avoid distance computations between vectors as appropriate, thereby reducing the latency associated with generating the codebook. Further, the system encodes the vectors based on the codebook. To do so, the computer system generates hashes of the vectors by applying locality sensitive hashing to these vectors. The hashes are compared and matched with hashes of codebook vectors. The computer system represents the vectors based on the matched codebook vectors.
Public/Granted literature
- US20190028723A1 LOW-LATENCY VECTOR QUANTIZATION FOR DATA COMPRESSION Public/Granted day:2019-01-24
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