What is claimed is:
1. A method to determine a video motion estimation comprising:
selecting a first predict start point in a search frame and a second predict start point in the search frame;
using the first predict start point, performing a first coarse search to select a block in a reference frame that is a good match to a block in the search frame; and
using information from the good match block and the second predict start point, performing a second coarse search in an effort to select a block in the reference frame that is a better match to the block in the search frame.
2. The method of claim 1 further comprising:
using information from the better match block, performing a fine search in an effort to select a block in the reference frame that is yet a better match to the block the in the search frame.
3. The method of claim 1 further comprising: determining whether a second coarse search is needed before performing the second coarse search, wherein if the second coarse search is not needed, skipping the second coarse search step and go directly to the fine search step.
4. The method of claim 3 wherein a second coarse search is needed if:
V0.xv.xV0.yv.y4
wherein V0 is a motion vector associated with the second predict start and v is a motion vector associated with the block in a reference frame that is a good match to a block in the search.
5. The method of claim 1, wherein the first and second coarse searches involve a macroblock diamond search and a macroblock smaller diamond search, wherein the smaller diamond search is carried out based on information generated by the diamond search.
6. The method of claim 5, wherein the diamond search and the smaller diamond search are based on a 5SDS search.
7. The method of claim 2, wherein the fine search involves an 88 block search and a half-pixel search, wherein the half-pixel search is carried out based on information generated by the 88 block search.
8. The method of claim 1, wherein the first predicted start position is based on a block immediately adjacent and on top of the block in the search frame, and the second predicted start position is based on a block immediately adjacent and left of the block in the search frame.
9. The method of claim 8, wherein a selection criteria used in the searches is a Sum of Absolute Difference (SAD) defined as:
4
SAD
(
v
)
=
j
,
k
=
1
N
I
V
(
j
,
k
)
–
I
CP
(
j
+
v
x
,
k
+
v
y
)
where IV is intensity level of pixels inside a macroblock inside the previous frame, ICP is intensity level of pixels at a checking point inside the current frame, and N is the number of rows and the number of columns in a block.
10. A method to determine a video motion estimation comprising:
selecting a first predict start point in a search frame and a second predict start point in the search frame;
using the first predict start point and the second predict start point in the search frame, concurrently performing a first diamond search and a second diamond search to select two blocks in a reference frame that are good matches to a block in the search frame;
using information from the two good match blocks, concurrently performing a first smaller diamond search and a second smaller diamond search to select two blocks in the reference frame that are better matches to the block in the search frame, wherein the first smaller diamond search is based on information from the first diamond search and the second smaller diamond search is based on information from the second diamond search; and
comparing the two better match blocks to select a more matched block of the two.
11. The method of claim 10 further comprising:
using information from the more matched block, performing a fine search to select a block in the reference frame that is even a better match to the block the in the search frame.
12. The method of claim 11, wherein the diamond searches and the smaller diamond searches are based on a 5SDS.
13. The method of claim 11, wherein the fine search involves an 88 block search and a half-pixel search, wherein the half-pixel search is carried out based on information generated by the 88 block search.
14. The method of claim 10, wherein the first predicted start position is based on a block immediately adjacent and on top of the block in the search frame, and the second predicted start position is based on a block immediately adjacent and left of the block in the search frame.
15. The method of claim 14, wherein a selection criteria used in the searches is a Sum of Absolute Difference (SAD) defined as:
5
SAD
(
v
)
=
j
,
k
=
1
N
I
V
(
j
,
k
)
–
I
CP
(
j
+
v
x
,
k
+
v
y
)
where IV is intensity level of pixels inside a macroblock inside the previous frame, ICP is intensity level of pixels at a checking point inside the current frame, and N is the number of rows and the number of columns in a block.
16. A video motion estimator coupled to memory and a Central Processing Unit (CPU) comprising:
a diamond search module coupled to memory, the diamond search module performing diamond searches to select a block in a reference frame that is a match to a block in a search frame based on a selection criteria;
a compare and motion vector module coupled the diamond search module, the compare and motion vector module monitoring and storing an updated selection criteria value, the compare and motion vector module monitoring and determining the motion vector associated with the matched block associated with the updated criteria value; and
a scheduler coupled to the diamond search module, the scheduler controlling searches performed by the diamond search module based on a predetermined motion estimation process utilizing two predicted start positions.
17. The video motion estimator of claim 16, wherein the motion estimation process comprising:
selecting a first predict start point in a search frame and a second predict start point in the search frame;
using the first predict start point, performing a first coarse search to select a block in a reference frame that is a good match to a block in the search frame; and
using information from the good matched block and the second predict start point, performing a second coarse search to select a block in the reference frame that is a better match to the block in the search frame.
18. The video motion estimator of claim 17 further comprising an 88 search module coupled to memory, the compare and motion vector module, and the scheduler, wherein the motion estimation process further comprising performing a fine search to select a block in the reference frame that is yet a better match to the block the in the search frame, the 88 search module performing an 88 search as a part of the fine search based on the selection criteria using information from the better matched block.
19. The video motion estimator of claim 17, wherein the motion estimation process further comprising determining whether a second coarse search is needed before performing the second coarse search, wherein if the second coarse search is not needed, skipping the second coarse search step and go directly to the fine search step.
20. The video motion estimator of claim 17, wherein the first and second coarse searches involve a macroblock diamond search and a macroblock smaller diamond search, wherein the smaller diamond search is carried out based on information generated by the diamond search.
21. The video motion estimator of claim 20, wherein the diamond search and the smaller diamond search are based on a 5SDS search.
22. The video motion estimator of claim 18, wherein the fine search further includes a half-pixel search, wherein the half-pixel search is carried out by the diamond search module based on information generated by the 88 block search.
23. The video motion estimator of claim 17, wherein the first predicted start position is based on a block immediately adjacent and on top of the block in the search frame, and the second predicted start position is based on a block immediately adjacent and left of the block in the search frame.
24. The video motion estimator of claim 23, wherein the selection criteria used in the searches is a Sum of Absolute Difference (SAD) defined as:
6
SAD
(
v
)
=
j
,
k
=
1
N
I
V
(
j
,
k
)
–
I
CP
(
j
+
v
x
,
k
+
v
y
)
where IV is intensity level of pixels inside a macroblock inside the previous frame, ICP is intensity level of pixels at a checking point inside the current frame, and N is the number of rows and the number of columns in a block.
25. The video motion estimator of claim 16 further comprising:
a standard deviation calculator coupled to memory and the scheduler, the standard deviation calculator computing the Mean And Standard Deviation (MAD) value of a block when receiving a signal from the scheduler that the motion estimation process is completed; and
an intrainter decision module coupled to the scheduler and the standard deviation calculator, the intrainter decision module determines whether an I-frame or a P-frame is involved by comparing the MAD value against the updated selection criteria value.
26. The video motion estimator of claim 16, wherein the motion estimation process comprising:
selecting a first predict start point in a search frame and a second predict start point in the search frame;
using the first predict start point and the second predict start point in the search frame, performing a first diamond search and a second diamond search to select two blocks in a reference frame that are good matches to a block in the search frame;
using information from the two good match blocks, performing a first smaller diamond search and a second smaller diamond search to select two blocks in the reference frame that are better matches to the block in the search frame, wherein the first smaller diamond search is based on information from the first diamond search and the second smaller diamond search is based on information from the second diamond search; and
comparing the two better match blocks to determine a more matched block of the two.
27. The video motion estimator of claim 26 further comprising an 88 search module coupled to memory, the compare and motion vector module, and the scheduler, wherein the motion estimation process further comprising performing a fine search to select a block in the reference frame that is yet a better match to the block the in the search frame, the 88 search module performing an 88 search as a part of the fine search based on the selection criteria using information from the more matched block.
28. The video motion estimator of claim 26 wherein the diamond searches and the smaller diamond searches are based on 5SDS.
29. The video motion estimator of claim 27 wherein the fine search further includes a half-pixel search, wherein the half-pixel search is carried out by the diamond search module based on information generated by the 88 block search.
30. The video motion estimator of claim 26, wherein the first predicted start position is based on a block immediately adjacent and on top of the block in the search frame, and the second predicted start position is based on a block immediately adjacent and left of the block in the search frame.
31. The video motion estimator of claim 30, wherein a selection criteria used in the searches is a Sum of Absolute Difference (SAD) defined as:
7
SAD
(
v
)
=
j
,
k
=
1
N
I
V
(
j
,
k
)
–
I
CP
(
j
+
v
x
,
k
+
v
y
)
where IV is intensity level of pixels inside a macroblock inside the previous frame, ICP is intensity level of pixels at a checking point inside the current frame, and N is the number of rows and the number of columns in a block.
32. A computer system adapted to perform motion estimation on video data comprising:
a central processing unit (CPU);
system memory coupled to the CPU;
a video interface coupled to the CPU, the video interface receiving video data from a video source;
a video display coupled to the CPU;
a graphicsdisplay controller coupled to the CPU, the video interface, the video display, and the system memory, the graphics controller comprising:
a graphics engine (GE);
an memory interface unit (MIU) coupled to the GE;
memory coupled to the MIU; and
a video encoder connected to the MIU and coupled to the memory, the video encoder comprising:
a diamond search module coupled to memory, the diamond search module performing a diamond search to select a block in a reference frame that is a match to a block in a search frame based on a selection criteria;
an 88 search module coupled to memory, the 88 search module performing an 88 search to select a block in a reference frame that is a match to a block in a search frame based on the selection criteria;
a compare and motion generator module coupled the diamond search module and the 88 search module, the compare and motion generator module monitoring and storing an updated selection criteria value, the compare and motion generator module generating the motion vector associated with the match block associated with the updated criteria value; and
a scheduler coupled to the diamond search module and the 88 search module, the scheduler controlling searches performed by the diamond search module and 88 search module based on a predetermined motion compensated estimation process utilizing two predicted start positions.
33. The computer system of claim 32, wherein the motion estimation process comprising:
selecting a first predict start point in a search frame and a second predict start point in the search frame;
using the first predict start point, performing a first coarse search to select a block in a reference frame that is a good match to a block in the search frame;
using information from the good match block and the second predict start point, performing a second coarse search to select a block in the reference frame that is a better match to the block in the search frame; and
using information from the better match block, performing a fine search to select a block in the reference frame that is yet a better match to the block the in the search frame.
34. The computer system of claim 32, wherein the motion estimation process comprising:
selecting a first predict start point in a search frame and a second predict start point in the search frame;
using the first predict start point and the second predict start point in the search frame, performing a first diamond search and a second diamond search to select two blocks in a reference frame that are good matches to a block in the search frame;
using information from the two good match blocks, performing a first smaller diamond search and a second smaller diamond search to select two blocks in the reference frame that are better matches to the block in the search frame, wherein the first smaller diamond search is based on information from the first diamond search and the second smaller diamond search is based on information from the second diamond search;
comparing the two better match blocks to determine a more matched block of the two; and
using information from the more matched block, performing a fine search to select a block in the reference frame that is even a better match to the block the in the search frame.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1.-14. (canceled)
15. A method of producing a polymer matrix composite, comprising:
(1) mixing a first polyether polyol having a first molecular weight and a second polyether polyol having a second molecular weight higher than the first molecular weight with one or more catalysts, water, and optional surfactant;
(2) optionally introducing reinforcing fibrous materials into the mixture;
(3) introducing inorganic filler into the mixture;
(4) introducing poly- or di-isocyanate into the mixture; and
(5) allowing the exothermic reaction to proceed without forced cooling except to control runaway exotherm, thereby forming a polymer matrix composite.
16. The method of claim 15, further comprising extruding the mixture or the polymer matrix composite through a die.
17. The method of claim 16, wherein at least a portion of the mixing or reaction, or both occurs in an extruder.
18. The method of claim 15, further comprising molding the polymer matrix composite into a desired shape.
19. The method of claim 16, further comprising forming the polymer matrix composite into a synthetic lumber.
20. The method of claim 19, wherein the forming comprises shaping the polymer matrix composite into a size and shape suitable for synthetic lumber.
21. The method of claim 20, wherein the forming further comprises embossing or impressing at least one surface of the polymer matrix composite with a pattern.
22. The method of claim 15, wherein the one or more catalysts comprise a skin-forming catalyst.
23. The method of claim 22, wherein the skin-forming catalyst comprises an organic tin compound.
24. The method of claim 15, wherein the one or more catalysts comprise a gelation catalyst.
25. The method of claim 24, wherein the gelation catalyst comprises an amine.
26. The method of claim 15, further comprising introducing axially oriented fiber rovings into the polymer matrix composite.
27. The method of claim 26, wherein the fiber rovings are introduced on, in, or beneath the surface of the composite.