US-20260127769-A1 - PREDICTIVE ENCODING/DECODING METHOD AND APPARATUS FOR AZIMUTH INFORMATION OF POINT CLOUD

Abstract

The present invention discloses a predictive encoding/decoding method and apparatus for azimuth information of a point cloud. The encoding method includes: obtaining original point cloud data; obtaining depth information of a point cloud based on the original point cloud data; establishing a relationship between the depth information and azimuth information of the point cloud; and predictively encoding the azimuth information of the point cloud by using the relationship between the depth information and the azimuth information of the point cloud, to obtain coded stream information.

Inventors

• Wei Zhang
• Fuzheng Yang
• Yuxin DU
• Wenjie ZOU

Assignees

• HONOR DEVICE CO., LTD.

Dates

Publication Date

20260507

Application Date

20251229

Priority Date

20210526

Claims (20)

1. 1 . A predictive encoding method for azimuth information of a point cloud, the method comprising: obtaining original point cloud data; obtaining depth information of a point cloud based on the original point cloud data; establishing a relationship between the depth information and azimuth information of the point cloud; and predictively encoding the azimuth information of the point cloud by using the relationship between the depth information and the azimuth information of the point cloud, to obtain coded stream information; wherein the predictively encoding the azimuth information of the point cloud by using the relationship between the depth information and the azimuth information of the point cloud comprises: predicting the azimuth of the point cloud based on the relationship between the depth information and the azimuth information of the point cloud, to obtain an initial predicted value of an azimuth residual; selectively shifting the initial predicted value of the azimuth residual to obtain a final predicted value of the azimuth residual and a prediction residual of the azimuth residual; and encoding the prediction residual of the azimuth residual and azimuth auxiliary information.
2. 2 . The method according to claim 1 , wherein the establishing the relationship between the depth information and azimuth information of the point cloud comprises: establishing the relationship between the depth information and the azimuth information of the point cloud by using a mathematical derivation method.
3. 3 . The method according to claim 1 , wherein the establishing the relationship between the depth information and azimuth information of the point cloud comprises: establishing the relationship between the depth information and the azimuth information of the point cloud by using a fitting method.
4. 4 . The method according to claim 2 , wherein a relational expression between the depth information and the azimuth information of the point cloud is established by using the mathematical derivation method as follows: φ - φ 0 = - α - arctan ⁢ H o r ; wherein φ represents azimuth information of a point, φ 0 represents originally collected azimuth information of the point, r represents depth information of the point, α represents a horizontal correction angle of a laser to which the point belongs, and H o represents a horizontal offset of the laser to which the point belongs.
5. 5 . The method according to claim 2 , wherein a relational expression between the depth information and the azimuth information of the point cloud is established by using the mathematical derivation method as follows: φ - φ 0 = 90 ⁢ ° - α - arccos ⁡ ( - H o r ) ; wherein φ represents azimuth information of a point, φ 0 represents originally collected azimuth information of the point, r represents depth information of the point, α represents a horizontal correction angle of a laser to which the point belongs, and H o represents a horizontal offset of the laser to which the point belongs.
6. 6 . The method according to claim 4 , wherein after the relational expression between the depth information and the azimuth information of the point cloud is obtained, the method further comprises: selecting several points from points collected by a same laser or encoded points and estimating unknown parameters α and H o in the relational expression based on information about the selected points.
7. 7 . The method according to claim 5 , wherein after the relational expression between the depth information and the azimuth information of the point cloud is obtained, the method further comprises: selecting several points from points collected by a same laser or encoded points and estimating unknown parameters α and H o in the relational expression based on information about the selected points.
8. 8 . The method according to claim 6 , wherein a formula for estimating the unknown parameters α and H o by selecting two points is: H o = ( r 1 - r 2 ) · ( 1 + tan ⁢ Δφ 1 · tan ⁢ Δφ 2 ) ± ( r 1 - r 2 ) 2 · ( 1 + tan ⁢ Δφ 1 · tan ⁢ Δφ 2 ) 2 - 4 ⁢ ( tan ⁢ Δφ 1 - tan ⁢ Δφ 2 ) 2 · r 1 · r 2 2 ⁢ ( tan ⁢ Δφ 1 - tan ⁢ Δφ 2 ) tan ⁢ α = r 1 · tan ⁢ Δφ 1 - r 2 · tan ⁢ Δφ 2 H o · ( tan ⁢ Δφ 1 - tan ⁢ Δφ 2 ) - ( r 1 - r 2 ) ; wherein r 1 and r 2 separately represent depth information of the two selected points, and Δφ 1 and Δφ 2 separately represent azimuth residuals of the two selected points.
9. 9 . The method according to claim 7 , wherein a formula for estimating the unknown parameters α and H o by selecting two points is: H o = ( r 1 - r 2 ) · ( 1 + tan ⁢ Δφ 1 · tan ⁢ Δφ 2 ) ± ( r 1 - r 2 ) 2 · ( 1 + tan ⁢ Δφ 1 · tan ⁢ Δφ 2 ) 2 - 4 ⁢ ( tan ⁢ Δφ 1 - tan ⁢ Δφ 2 ) 2 · r 1 · r 2 2 ⁢ ( tan ⁢ Δφ 1 - tan ⁢ Δφ 2 ) tan ⁢ α = r 1 · tan ⁢ Δφ 1 - r 2 · tan ⁢ Δφ 2 H o · ( tan ⁢ Δφ 1 - tan ⁢ Δφ 2 ) - ( r 1 - r 2 ) ; wherein r 1 and r 2 separately represent depth information of the two selected points, and Δφ 1 and Δφ 2 separately represent azimuth residuals of the two selected points.
10. 10 . The method according to claim 1 , wherein the original point cloud data includes a group of 3D spatial points, each spatial point in the group of 3D spatial points records its geometric position information, and the geometric position information of each spatial point is expressed based on a Cartesian coordinate system.
11. 11 . The method according to claim 1 , wherein encoding the prediction residual of the azimuth residual and azimuth auxiliary information comprises: using an entropy encoding technology to encode the prediction residual of the azimuth residual; and encoding the azimuth auxiliary information in a differential encoding manner, wherein the azimuth auxiliary information is an azimuth index j of the point.
12. 12 . A predictive encoding device for azimuth information of a point cloud, the device comprising: at least one processor; and memory storing at least one instruction that, when executed by the at least one processor, cause the device to perform operations comprising: obtaining original point cloud data; obtaining depth information of a point cloud based on the original point cloud data; establishing a relationship between the depth information and azimuth information of the point cloud; and predictively encoding the azimuth information of the point cloud by using the relationship between the depth information and the azimuth information of the point cloud, to obtain coded stream information; wherein the predictively encoding the azimuth information of the point cloud by using the relationship between the depth information and the azimuth information of the point cloud comprises: predicting the azimuth of the point cloud based on the relationship between the depth information and the azimuth information of the point cloud, to obtain an initial predicted value of an azimuth residual; selectively shifting the initial predicted value of the azimuth residual to obtain a final predicted value of the azimuth residual and a prediction residual of the azimuth residual; and encoding the prediction residual of the azimuth residual and azimuth auxiliary information.
13. 13 . The device according to claim 12 , wherein the establishing the relationship between the depth information and azimuth information of the point cloud comprises: establishing the relationship between the depth information and the azimuth information of the point cloud by using a mathematical derivation method.
14. 14 . The device according to claim 12 , wherein the establishing the relationship between the depth information and azimuth information of the point cloud comprises: establishing the relationship between the depth information and the azimuth information of the point cloud by using a fitting method.
15. 15 . The device according to claim 13 , wherein a relational expression between the depth information and the azimuth information of the point cloud is established by using the mathematical derivation method as follows: φ - φ 0 = - α - arctan ⁢ H o r ; wherein φ represents azimuth information of a point, φ 0 represents originally collected azimuth information of the point, r represents depth information of the point, α represents a horizontal correction angle of a laser to which the point belongs, and H o represents a horizontal offset of the laser to which the point belongs.
16. 16 . The device according to claim 13 , wherein a relational expression between the depth information and the azimuth information of the point cloud is established by using the mathematical derivation method as follows: φ - φ 0 = 90 ⁢ ° - α - arccos ⁡ ( - H o r ) ; wherein φ represents azimuth information of a point, φ 0 represents originally collected azimuth information of the point, r represents depth information of the point, α represents a horizontal correction angle of a laser to which the point belongs, and H o represents a horizontal offset of the laser to which the point belongs.
17. 17 . The device according to claim 12 , wherein the original point cloud data includes a group of 3D spatial points, each spatial point in the group of 3D spatial points records its geometric position information, and the geometric position information of each spatial point is expressed based on a Cartesian coordinate system.
18. 18 . The device according to claim 12 , wherein encoding the prediction residual of the azimuth residual and azimuth auxiliary information comprises: using an entropy encoding technology to encode the prediction residual of the azimuth residual; and encoding the azimuth auxiliary information in a differential encoding manner, wherein the azimuth auxiliary information is an azimuth index j of the point.
19. 19 . A predictive decoding method for azimuth information of a point cloud, the method comprising: obtaining coded stream information, and decoding the coded stream information to obtain a prediction residual of an azimuth residual of a point cloud and azimuth auxiliary information; predicting an azimuth of the point cloud by using reconstructed depth information and a relationship between the depth information and azimuth information, to obtain a final predicted value of the azimuth residual; reconstructing the azimuth residual of the point cloud based on the final predicted value of the azimuth residual and the prediction residual of the azimuth residual; and reconstructing the azimuth information of the point cloud based on the reconstructed azimuth residual and the azimuth auxiliary information; wherein reconstructing the azimuth residual of the point cloud based on the final predicted value of the azimuth residual and the prediction residual of the azimuth residual comprises: adding the final predicted value of the azimuth residual and the prediction residual of the azimuth residual, to reconstruct the azimuth residual of the point cloud.
20. 20 . The method according to claim 19 , wherein reconstructing the azimuth information of the point cloud based on the reconstructed azimuth residual and the azimuth auxiliary information further comprises: calculating an approximate value of an originally collected azimuth of the point cloud by using a decoded azimuth index; and adding the reconstructed azimuth residual and the approximate value of the originally collected azimuth, to reconstruct the azimuth information of the point cloud.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application is a continuation of U.S. application Ser. No. 18/270,591, filed on Jun. 30, 2023, which is a national stage of International Application No. PCT/CN2022/093678, filed on May 18, 2022, which claims priority to Chinese Patent Application No. 202110580220.6, filed on May 26, 2021. All of the aforementioned applications are hereby incorporated by reference in their entireties. TECHNICAL FIELD The present invention pertains to the field of a point cloud encoding/decoding technologies, and particularly relates to a predictive encoding/decoding method and apparatus for azimuth information of a point cloud. BACKGROUND With the improvement of a hardware processing capability and the rapid development of computer vision, three-dimensional point cloud data has been widely used in fields such as virtual reality, augmented reality, self-driving, and environment modeling. However, a large-scale point cloud usually has a large amount of data, which is not conducive to the transmission and storage of the point cloud data. Therefore, the large-scale point cloud needs to be efficiently encoded/decoded. In a conventional encoding/decoding technology for the large-scale point cloud, Cartesian coordinates of the point cloud are usually predicted by using cylindrical coordinates (including azimuth information, depth information, and the like) of the point cloud. Therefore, each cylindrical coordinate component of the point cloud needs to be predictively encoded in the prior art. Specifically, for predictive encoding of the azimuth information of the point cloud, a point cloud encoding/decoding method based on a prediction tree is provided in the prior art 1. First, a multiple of a difference between an azimuth of a current point and an azimuth obtained in a selected prediction mode with respect to an angular velocity of rotation needs to be calculated, and then the azimuth of the current point is predicted by using an integral multiple of the angular velocity of rotation and the azimuth obtained in the selected prediction mode, to obtain a prediction residual, and finally the integral multiple and the prediction residual of the azimuth are encoded to reconstruct azimuth information in the same manner on a decoder. A point cloud encoding/decoding method based on a single-chain structure is provided in the prior art 2. First, an azimuth of each point is quantized, and a quantized value of the azimuth of each point may be restored by using the single-chain structure. Then, a quantized residual of the azimuth is predictively encoded, and specifically, a prediction mode list is created, and an optimal prediction mode is selected by an encoder, to complete predictive encoding of azimuth information of a point cloud. However, when the two methods are used to predictively encode the azimuth information of the point cloud, only encoded azimuth information is used for prediction, and a relationship between other information and the azimuth information is not considered. Consequently, the obtained prediction residuals of the azimuth information are large and are not centralized, and the validity of an entropy encoding context model is destroyed, and therefore, encoding efficiency of the azimuth information of the point cloud is low. SUMMARY To resolve the foregoing problem in the prior art, the present invention provides a predictive encoding/decoding method and apparatus for azimuth information of a point cloud. Technical problems in the present invention are resolved by the following technical solutions: A predictive encoding method for azimuth information of a point cloud includes: obtaining original point cloud data; obtaining depth information of a point cloud based on the original point cloud data;establishing a relationship between the depth information and azimuth information of the point cloud; andpredictively encoding the azimuth information of the point cloud by using the relationship between the depth information and the azimuth information of the point cloud, to obtain coded stream information. In an embodiment of the present invention, the establishing a relationship between the depth information and azimuth information of the point cloud includes: establishing the relationship between the depth information and the azimuth information of the point cloud by using a mathematical derivation method; orestablishing the relationship between the depth information and the azimuth information of the point cloud by using a fitting method. In an embodiment of the present invention, a relational expression between the depth information and the azimuth information of the point cloud is established by using the mathematical derivation method as follows: φ-φ0=-α-arctan⁢Hor. φ represents azimuth information of a point, φ0 represents originally collected azimuth information of the point, r represents depth information of the point, α represents a horizontal correction angle of a laser t