Selective predictor and selective predictive encoding for two-dimensional geometry compression
View Patent ↗A selective predictor utilizes a selective prediction method for coordinate data encoding. The selective predictor may calculate multiple prediction vectors for each vertex in the shape traversal order. Then, the selective predictor selects the vector that is closest to the vertex to be estimated. In determining the multiple prediction vectors, the selective predictor considers the position of several previous vertices in the traversal order. The selective predictor outputs a correction vector for the selected prediction vector and identification information indicting the selected prediction vector.
1. A method of selective prediction for coordinate data, comprising:
determining, by a processor, initial correction vectors for initial locations by estimating a position of the initial locations; and
determining a current correction vector for a current location based on one of multiple prediction vectors, in which the one of the multiple prediction vectors is calculated based on initial vertex vectors, wherein the multiple prediction vectors are related to the initial correction vectors.
2. The method of claim 1 , wherein determining the initial correction vectors comprises:
setting previous vertex vectors as initial prediction vectors; and
determining the initial correction vectors by subtracting the initial prediction vectors from initial vertex vectors.
3. The method of claim 2 , wherein determining the initial correction vectors comprises determining three initial correction vectors.
4. The method of claim 1 , wherein determining the current correction vector comprises:
determining a minimum difference between a current vertex vector and each multiple prediction vector; and
selecting one of the multiple prediction vectors with the minimum difference to be utilized in determining the current correction vector.
5. The method of claim 4 , wherein determining the current correction vector further comprises subtracting the selected one of the multiple prediction vectors from the current vertex vector.
6. The method of claim 4 , wherein the multiple prediction vectors are mathematical combinations of the initial correction vectors.
7. The method of claim 4 , further comprising determining three prediction vectors for the current location by using the equations:
{right arrow over (v)} k 0 ={right arrow over (v)} k−1 ;
{right arrow over (v)} k ′={right arrow over (v)} k−1 −{right arrow over (v)} k−2 +{right arrow over (v)} k−3 ;
{right arrow over (v)} k ″={right arrow over (v)} k−1 +{right arrow over (v)} k−1 −{right arrow over (v)} k−2 ; and
{right arrow over (v)} k ′″={right arrow over (v)} k−1 +{right arrow over (v)} k−2 −{right arrow over (v)} k−3 ,
where {right arrow over (v)} k 0 is the current vertex vector, {right arrow over (v)} k−1 , {right arrow over (v)} k−2 , and {right arrow over (v)} k−3 are initial vertex vectors, and {right arrow over (v)} k ′, {right arrow over (v)} k ″, and {right arrow over (v)} k ′″ are the multiple prediction vectors.
8. The method of claim 4 , further comprising outputting the current correction vector.
9. The method of claim 8 , further comprising outputting identification information of the selected one of the multiple prediction vectors with the current correction vector.
10. The method of claim 9 , further comprising outputting an array of identification information of the selected one of the multiple prediction vectors with an array of current correction vectors.
11. The method of claim 1 , wherein the selection prediction is used in a geospatial data system.
12. The method according to claim 1 , wherein the multiple prediction vectors are calculated using a current vertex vector and an initial vertex vector.
13. A device for performing selective prediction on coordinate data, comprising:
an input for receiving coordinate data;
a selective predictor, implemented in a processor, coupled to the input for encoding the coordinate data, the selective predictor comprising logic for determining initial correction vectors for initial locations by estimating a position of the initial locations, and logic for determining a current correction vector for a current location based on one of multiple prediction vectors, in which the one of the multiple prediction vectors is calculated based on initial vertex vectors, wherein the multiple prediction vectors are related to the initial correction vectors; and
an output coupled to the selective predictor for outputting the current correction vector.
14. The device of claim 13 , further comprising:
a quantizer coupled to the selective predictor; and
a decoder coupled to the selective predictor.
15. The device of claim 13 , wherein the selective predictor comprises logic for determining a minimum difference between a current vertex vector and each multiple prediction vector, and selecting one of the multiple prediction vectors with the minimum difference to be utilized in determining the current correction vector.
16. The device of claim 15 , wherein the selective predictor comprises logic for subtracting the selected one of the multiple prediction vectors from the current vertex vector.
17. The device of claim 15 , wherein the selective predictor further comprises logic for determining three prediction vectors for the current location by using the equations:
{right arrow over (v)} k 0 ={right arrow over (v)} k−1 ;
{right arrow over (v)} k ′={right arrow over (v)} k−1 −{right arrow over (v)} k−2 +{right arrow over (v)} k−3 ;
{right arrow over (v)} k ″={right arrow over (v)} k−1 +{right arrow over (v)} k−1 −{right arrow over (v)} k−2 ; and
{right arrow over (v)} k ′″={right arrow over (v)} k−1 +{right arrow over (v)} k−2 −{right arrow over (v)} k−3 ,
where {right arrow over (v)} k 0 is the current vertex vector, {right arrow over (v)} k−1 , {right arrow over (v)} k−2 , and {right arrow over (v)} k−3 are initial vertex vectors, and {right arrow over (v)} k ′, {right arrow over (v)} k ″, and {right arrow over (v)} k ′″ are the multiple prediction vectors.
18. The device of claim 15 , further comprising:
a memory, coupled to the selective predictor, for storing outputted identification information of the selected one of the multiple prediction vectors.
19. The method of claim 15 , wherein device for selective prediction is included in a geospatial data system.
20. The device according to claim 13 , wherein the multiple prediction vectors are calculated using a current vertex vector and an initial vertex vector.
21. A non-transitory computer readable medium comprising computer-readable instructions for causing a processor to perform the method of selective prediction, the method comprising:
determining initial correction vectors for initial locations by estimating a position of the initial locations; and
determining a current correction vector for a current location based on one of multiple prediction vectors, in which the one of the multiple prediction vectors is calculated based on initial vertex vectors, wherein the multiple prediction vectors are related to the initial correction vectors.
22. The computer readable medium of claim 21 , the method further comprising:
setting previous vertex vectors as initial prediction vectors; and
determining the initial correction vectors by subtracting the initial prediction vectors from initial vertex vectors.
23. The computer readable medium of claim 22 , the method further comprising determining three initial correction vectors.
24. The computer readable medium of claim 21 , the method further comprising:
determining a minimum difference between a current vertex vector and each multiple prediction vector; and
selecting one of the multiple prediction vectors with the minimum difference to be utilized in determining the current correction vector.
25. The computer readable medium of claim 24 , the method further comprising subtracting the selected one of the multiple prediction vectors from the current vertex vector.
26. The computer readable medium of claim 24 , wherein the multiple prediction vectors are mathematical combinations of the initial correction vectors.
27. The computer readable medium d of claim 24 , the method further comprising determining three prediction vectors for the current location by using the equations:
{right arrow over (v)} k 0 ={right arrow over (v)} k−1 ;
{right arrow over (v)} k ′={right arrow over (v)} k−1 −{right arrow over (v)} k−2 +{right arrow over (v)} k−3 ;
{right arrow over (v)} k ″={right arrow over (v)} k−1 +{right arrow over (v)} k−1 −{right arrow over (v)} k−2 ; and
{right arrow over (v)} k ′″={right arrow over (v)} k−1 +{right arrow over (v)} k−2 −{right arrow over (v)} k−3 ,
where {right arrow over (v)} k 0 is the current vertex vector, {right arrow over (v)} k−1 , {right arrow over (v)} k−2 , and {right arrow over (v)} k−3 are initial vertex vectors, and {right arrow over (v)} k ′, {right arrow over (v)} k ″, and {right arrow over (v)} k ′″ are the multiple prediction vectors.
28. The computer readable medium of claim 24 , the method further comprising outputting the current correction vector.
29. The computer readable medium of claim 28 , the method further comprising outputting identification information of the selected one of the multiple prediction vectors with the current correction vector.
30. The computer readable medium of claim 29 , the method further comprising outputting an array of identification information of the selected one of the multiple prediction vectors with an array of current correction vectors.
31. The computer readable medium according to claim 21 , wherein the multiple prediction vectors are calculated using a current vertex vector and an initial vertex vector.