IP Library › Granted Patent US 12,610,053
Granted Patent B2
US 12,610,053 · App. 18/884,281 · Granted Apr 21, 2026

Encoding method and apparatus, and decoding method and apparatus

Inventors: Zehui Lin (Shenzhen, CN); Kangying Cai (Beijing, CN); Hu Chen (Munich, DE); Rong Wei (Shenzhen, CN)
Assignee: HUAWEI TECHNOLOGIES CO., LTD.
H04N19/126H04N19/159
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Quick Facts
Patent No.
US 12,610,053
App. No.
18/884,281
Granted
Apr 21, 2026
Kind
B2
Abstract

Embodiments of the present disclosure relate to the field of media technologies, and disclose an encoding method and apparatus, and a decoding method and apparatus, to reduce a rendering loss caused by compression of probe data. The encoding method includes: first determining a target normalization combination of a probe data group, then normalizing the probe data group based on the target normalization combination to obtain a normalized probe data group, and encoding the normalized probe data group into a bitstream. The target normalization combination minimizes a rendering loss corresponding to the probe data group among a plurality of normalization combinations, and the target normalization combination includes a target normalization method and a target normalization parameter.

Claims (57)

1 . An encoding method, comprising:

determining a target normalization combination of a probe data group, wherein the target normalization combination minimizes a rendering loss corresponding to the probe data group among a plurality of normalization combinations, and the target normalization combination comprises a target normalization method and a target normalization parameter;

normalizing the probe data group based on the target normalization combination to obtain a normalized probe data group; and

encoding the normalized probe data group into a bitstream.

2 . The method of claim 1 , wherein the determining a target normalization combination of a probe data group comprises:

determining a rendering loss corresponding to each of the plurality of normalization combinations and corresponding to the probe data group; and

determining the normalization combination, among the plurality of normalization combinations, that minimizes the rendering loss corresponding to the probe data group as the target normalization combination.

3 . The method of claim 2 , wherein the determining a rendering loss corresponding to each of the plurality of normalization combinations and corresponding to the probe data group comprises:

performing a target operation on the probe data group based on each normalization combination, to obtain a rendering result of the normalization combination on each probe data group, wherein the target operation comprises normalization, coding, and denormalization; and

determining, based on a rendering result obtained by rendering the probe data group through the target operation and a rendering result obtained by rendering the probe data group without the target operation, the rendering loss that corresponds to each normalization combination and that corresponds to the probe data group.

4 . The method of claim 1 , further comprising:

encoding the target normalization combination into the bitstream.

5 . The method of claim 1 , further comprising:

determining a normalization parameter variation of the probe data group based on the target normalization parameter of the probe data group and a reference target normalization parameter, wherein the reference target normalization parameter is a target normalization parameter of a probe data group related to the probe data group; and

encoding the normalization parameter variation into the bitstream.

6 . The method of claim 1 , further comprising:

determining a normalization parameter variation of the probe data group based on the target normalization parameter of the probe data group and a reference target normalization parameter, wherein the reference target normalization parameter is a target normalization parameter of a probe data group related to the probe data group; and

encoding first information into the bitstream, wherein the first information indicates whether the target normalization parameter of the probe data group is changed compared with the reference target normalization parameter.

7 . The method of claim 6 , further comprising:

when the first information indicates that the target normalization parameter of the probe data group is changed compared with the reference target normalization parameter, encoding the normalization parameter variation into the bitstream.

8 . The method of claim 5 , further comprising:

encoding index information into the bitstream, wherein the index information comprises an identifier of the probe data group and the normalization parameter variation of the probe data group.

9 . The method of claim 1 , further comprising:

determining a normalization parameter in the plurality of normalization combinations based on a reference target normalization parameter, wherein the reference target normalization parameter is a target normalization parameter of a probe data group related to the probe data group.

10 . The method of claim 1 , wherein the probe data group comprises ambient environment data of a probe, and the ambient environment data comprises: illumination data, a color, visibility data, a material, a normal direction, and/or texture coordinates.

11 . The method of claim 4 , wherein the encoding the target normalization combination into the bitstream comprises:

when the probe data group is an intra coded probe data group, encoding the target normalization combination into the bitstream.

12 . The method of claim 5 , wherein the encoding the normalization parameter variation into the bitstream comprises:

when the probe data group is an inter coded probe data group, encoding the normalization parameter variation into the bitstream.

13 . A decoding method, comprising:

decoding a bitstream to obtain a normalized probe data group;

denormalizing the normalized probe data group based on a target normalization combination of a first probe data group to obtain a second probe data group, wherein the target normalization combination minimizes a rendering loss corresponding to the first probe data group among a plurality of normalization combinations, the first probe data group is a probe data group that is normalized to obtain the normalized probe data group, and the target normalization combination comprises a target normalization method and a target normalization parameter; and

performing rendering based on the second probe data group.

14 . The method of claim 13 , further comprising:

decoding the bitstream to obtain the target normalization combination.

15 . The method of claim 13 , further comprising:

decoding the bitstream to obtain a normalization parameter variation of the first probe data group; and

determining the target normalization combination based on the normalization parameter variation and a reference normalization combination, wherein the reference normalization combination is a target normalization combination of a probe data group related to the first probe data group.

16 . The method of claim 13 , further comprising:

decoding the bitstream to obtain first information, wherein the first information indicates whether the target normalization parameter of the first probe data group is changed compared with a reference target normalization parameter, and the reference target normalization parameter is a target normalization parameter of a probe data group related to the first probe data group; and

when the first information indicates that the target normalization parameter of the first probe data group is not changed compared with the reference target normalization parameter, determining the target normalization combination based on a reference normalization combination, wherein the reference normalization combination is a target normalization combination of the probe data group related to the first probe data group; or

when the first information indicates that the target normalization parameter of the first probe data group is changed compared with the reference target normalization parameter, decoding the bitstream to obtain second information, wherein the second information indicates a normalization parameter variation of the first probe data group, and determining the target normalization combination based on the normalization parameter variation and the reference normalization combination.

17 . A decoding apparatus, comprising:

a memory configured to store instructions;

at least one processor coupled to the memory, and configured to execute the instructions to cause the decoding apparatus to:

decode a bitstream to obtain a normalized probe data group;

denormalize the normalized probe data group based on a target normalization combination of a first probe data group to obtain a second probe data group, wherein the target normalization combination corresponds to a smallest rendering loss associated with the first probe data group among a plurality of normalization combinations, the first probe data group is a probe data group that is normalized to obtain the normalized probe data group, and the target normalization combination comprises a target normalization method and a target normalization parameter; and

perform rendering based on the second probe data group.

18 . The apparatus of claim 17 , wherein the at least one processor is further configured to execute the instructions to cause the decoding apparatus to:

decode the bitstream to obtain the target normalization combination.

19 . The apparatus of claim 17 , wherein the at least one processor is further configured to execute the instructions to cause the decoding apparatus to:

decode the bitstream to obtain a normalization parameter variation of the first probe data group; and

determine the target normalization combination based on the normalization parameter variation and a reference normalization combination, wherein the reference normalization combination is a target normalization combination of a probe data group related to the first probe data group.

20 . The apparatus of claim 17 , wherein the at least one processor is further configured to execute the instructions to cause the decoding apparatus to:

decode the bitstream to obtain first information, wherein the first information indicates whether the target normalization parameter of the first probe data group is changed compared with a reference target normalization parameter, and the reference target normalization parameter is a target normalization parameter of a probe data group related to the first probe data group; and

when the first information indicates that the target normalization parameter of the first probe data group is not changed compared with the reference target normalization parameter, determine the target normalization combination based on a reference normalization combination, wherein the reference normalization combination is a target normalization combination of the probe data group related to the first probe data group; or

when the first information indicates that the target normalization parameter of the first probe data group is changed compared with the reference target normalization parameter, decode the bitstream to obtain second information, wherein the second information indicates a normalization parameter variation of the first probe data group, and determine the target normalization combination based on the normalization parameter variation and the reference normalization combination.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 9, 2025
From: LIN, ZEHUI; CAI, KANGYING; CHEN, HU; WEI, RONG
To: HUAWEI TECHNOLOGIES CO., LTD.
Reel/Frame 073150/0011 →
Priority Claims (1)
CN 202210254653.7 · Mar 15, 2022 · national
Continuity (2)
Continuation PCTCN2023072525 · Jan 17, 2023
Related Publication 20250008105A1 · Jan 2, 2025
References Cited (15)
US 7167176B2 · Sloan · 2007 [cited by examiner]
US 11941752B2 · Stengel · 2024 [cited by examiner]
US 20180253869A1 · Yumer · 2018 [cited by examiner]
US 20200275074A1 · Hamilton · 2020 [cited by examiner]
US 20200388022A1 · Bourd · 2020 [cited by examiner]
US 20210012562A1 · McGuire · 2021 [cited by examiner]
US 20220414971A1 · Chang · 2022 [cited by examiner]
CN 112755535B · 2022 [cited by examiner]
Michael Stengel et al:“A Distributed, Decoupled System for Losslessly Streaming Dynamic Light Probes to Thin Clients.”arXiv:2103.05875v1 [cs.DC] Mar. 10, 2021 (Year: 2021). [cited by examiner]
Ari Silvennoinen and Peter-Pike Sloan:“Moving Basis Decomposition for Precomputed Light Transport.”Jul. 15, 2021 (Year: 2021). [cited by examiner]
Zina H. Cigolle et al:“A Survey of Efficient Representations for Independent Unit Vectors.”Journal of Computer Graphics Techniques vol. 3, No. 2, Apr. 17, 2014 (Year: 2014). [cited by examiner]
Ping Luo, et al,“Differentiable Learning-to-Normalize via Switchable Normalization”, arXiv:1806.10779v3 [cs.CV] Jul. 3, 2018, total 13 pages. [cited by applicant]
Zina H. Cigolle et al:“A Survey of Efficient Representations for Independent Unit Vectors.”Journal of Computer Graphics Techniques vol. 3, No. 2, Apr. 17, 2014. total 30 pages. [cited by applicant]
Michael Stengel et al:“A Distributed, Decoupled System for Losslessly Streaming Dynamic Light Probes to Thin Clients.”arXiv:2103.05875v1 [cs.DC] Mar. 10, 2021. total 13 pages. [cited by applicant]
Ari Silvennoinen and Peter-Pike Sloan:“Moving Basis Decomposition for Precomputed Light Transport.”Jul. 15, 2021, total 11 pages. [cited by applicant]