Invention Grant
- Patent Title: Efficient update of cumulative distribution functions for image compression
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Application No.: US17904030Application Date: 2020-07-06
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Publication No.: US12149265B2Publication Date: 2024-11-19
- Inventor: Pascal Massimino , Vincent Rabaud
- Applicant: GOOGLE LLC
- Applicant Address: US CA Mountain View
- Assignee: GOOGLE LLC
- Current Assignee: GOOGLE LLC
- Current Assignee Address: US CA Mountain View
- Agency: Brake Hughes Bellermann LLP
- International Application: PCT/US2020/070236 WO 20200706
- International Announcement: WO2022/010531 WO 20220113
- Main IPC: H03M7/30
- IPC: H03M7/30 ; H03M7/40 ; H04N19/91

Abstract:
Updating cumulative distribution functions (CDFs) during arithmetic encoding can be a challenge because the final element of the CDF should remain fixed during the update calculations. If the probabilities were floating-point numbers, this would not be too much of a challenge; nevertheless, the probabilities and hence the CDFs are represented as integers to take advantage of infinite-precision arithmetic. Some of these difficulties may be alleviated by introducing a “mixing” CDF along with the active CDF being updated; the mixing CDF provides nonlocal context for updating the CDF due to the introduction of a particular symbol in the encoding. Improved techniques of performing arithmetic encoding include updating the CDF using two, one-dimensional mixing CDF arrays: a symbol-dependent array and a symbol-dependent array. The symbol-dependent array is a sub array of a larger, fixed array such that the sub array selected depends on the symbol being used.
Public/Granted literature
- US20230085142A1 EFFICIENT UPDATE OF CUMULATIVE DISTRIBUTION FUNCTIONS FOR IMAGE COMPRESSION Public/Granted day:2023-03-16
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