METHOD AND APPARATUS FOR REFERENCE AREA TRANSFER WITH PRE-ANALYSIS

Information

  • Patent Application
  • 20230199216
  • Publication Number
    20230199216
  • Date Filed
    February 13, 2023
    a year ago
  • Date Published
    June 22, 2023
    a year ago
Abstract
A method and apparatus for reduction of reference data transfer and coding efficiency improvement. The method includes performing pre-analysis on a decimated version of an image, and utilizing the predictions of the pre-analysis to transfer smaller reference area.
Description
FIELD OF THE INVENTION

This invention generally relates to a method and apparatus for reference area transfer. More specifically, it relates to performing pre-analysis for transferring a specific reference area.


BACKGROUND OF THE INVENTION

In video processing, minimizing the amount of data transfer from external memory to internal memory for motion estimation (ME) and motion compensation (MC) is critical to reduce power consumption. In general, there is a trade-off between the amount of data transfer and internal memory size, i.e., the amount of data transfer can be reduced by increasing internal memory size and vice versa.


However, because internal memory size is fixed based on silicon area, the amount of data transfer needs to be minimized for a given internal memory size. Thus, there is a need for a reference data transfer method and apparatus that minimizes the amount of data transfer using pre-analysis information for a given internal memory size and that improves coding efficiency.


SUMMARY OF THE INVENTION

An embodiment of the present invention provides a method and apparatus for reduction of reference data transfer and coding efficiency improvement. The method includes performing pre-analysis on a decimated version of an image, and utilizing the predictions of the pre-analysis to transfer smaller reference area.





BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the above recited features of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to embodiments, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered limiting of its scope, for the invention may admit to other equally effective embodiments.



FIG. 1 is an embodiment of partitions and best partition selection;



FIG. 2 is an embodiment of a search area and corresponding reference window;



FIG. 3 is an embodiment of an overlapped areas between current and left/upper windows; and



FIG. 4. is an embodiment depicting estimation of required internal memory size.





DETAILED DESCRIPTION

To minimize the amount of data transfer using pre-analysis information for a given internal memory size and to improve coding efficiency, utilizing accurate pre-analysis enables to control the amount of data transfer and improves PSNR performance. The proposed method minimizes hardware resources, such as, power consumption and internal memory size, for encoding high resolution videos or fast/complex motion videos and for improving coding efficiency.


For example, minimizing the amount of data transfer from external memory to internal memory for motion estimation and motion compensation is critical to reduce power consumption of a video codec. In general, there is a trade-off between the amount of data transfer and internal memory size, i.e., the amount of data transfer can be reduced by increasing internal memory size and vice versa. However, because internal memory size is fixed based on silicon area, the amount of data transfer needs to be minimized for a given internal memory size. Pre-analysis can provide various information, such as, initial motion search point, motion boundary, partition size, etc., which may be utilized to perform motion estimation that minimizes the amount of data transfer and improves coding efficiency.


In one embodiment, as shown in FIG. 1, in pre-analysis, motion estimation (ME) is performed on 4:1 decimated frame, which is resized to ΒΌ in both horizontal and vertical direction, to generate motion information for main ME on original resolution frame (1:1 domain). Using a 7x7 2D decimation filter to generate 4:1 decimated frames, original frames, usually without reconstructed frame, are decimated and stored into encoder reference memory buffer. FIG. 1 is an embodiment of partitions and best partition selection.


Usually, motion search on 4:1 domain is performed based on 16x16 block (64x64 on 1:1 domain). However, it will generate motion vectors (MV) for smaller blocks within a 16x16 block, as well as, motion vector for the 16x16 block. Neighboring motion vectors (left, upper-left, upper and upper-right) and global MV are used as initial prediction points. In pre-analysis, cost maybe evaluated at each point and the best point that produces minimum cost is chosen. More motion vectors, such as, co-located motion vectors can be added to increase prediction accuracy. For each initial prediction point, costs of smaller partitions (16x8, 8x16, 8x8 and 4x4) are also evaluated. Each partition has its own best motion vector.


After determining the best initial motion vector, more points maybe searched around the motion vector, such that accurate motion is found. All points within 16x16 and 8x8 search areas around the motion vector for P-type and B-type frame, respectively, are searched. Each partition keeps updating best motion vector during the refinement. After the refinement, each partition has its own best motion vector. To minimize total cost, more combinations with 8x8 and 4x4 partitions are generated. First, we determine best cost for each 8x8 partition (one 8x8 block or four 4x4 block). Then, we compare the best partition to 16x16, 16x8 and 8x16 partitions.


Cost for a search point consists of sum of absolute difference (SAD) and cost for motion vector, where the cost = SAD + lambda * MVD_bits, wherein lambda is a Lagrangian multiplier and MVD_bits is number of bits to encode MV difference between current motion vector and motion vector predictor (MVP). Motion vector predictor is a median of neighboring motion vectors (left, upper and upper-right). Accurate motion vector predictor is available for 16x16 block; however, for smaller partitions, because motion vectors of neighboring blocks are not determined, motion vector predictor of 16x16 block is used.


In one embodiment, search area on 4:1 domain can be determined based on available data transfer bandwidth and internal memory size. The computational complexity for initial predictor evaluation on 4:1 domain is similar to that on 1:1 domain. Refinement of 4:1 domain motion estimation requires more sum of absolute difference calculations, where the main motion estimation may need, for example, 6-tap filtering and 18 sum of absolute difference calculations for fractional-pel search. Thus, assuming computational complexity per 16x16 block is roughly similar to that of main motion estimation, and the total extra computational complexity is (num_16xl6 / 16) * comp_per_16x16, where num_16x16 is a number of 16x16 blocks in a frame and comp_per_16x16 is computational complexity per 16x16 block on 1:1 domain.


Pre-analysis will produce one MV for each 16x16 on 1:1 domain. Let crude motion vector (CMV) denote the MV from pre-analysis because it is crude on 1:1 domain. Search area on 1:1 domain is determined for each 16x16 block using crude motion vector. Reference window, which is actual area for motion estimation, is calculated based on search range, required number of pixels for fractional-pel search and block size (16x16). For example, when search area is +/-9 around CMV in vertical and horizontal directions, reference window becomes +/-40 around CMV in vertical and horizontal directions (in H.264/AVC). FIG. 2 is an embodiment of a search area and corresponding reference window. In FIG. 2, the reference window size for search area is +/-9. The reference window should be available at internal memory before starting motion search for current 16x16 block. Maximum search range, which is usually different from the search area, on 1:1 domain is four times of search range on 4:1 domain. For example, if maximum search range on 4:1 domain is +/-64, maximum search range on 1:1 domain becomes +/-256.


For motion search on 1:1 domain, neighboring motion vector, global MV, temporal motion vectors and Crude motion vectors are used as initial predictors. However, if a motion vector is not within a valid search area determined by Crude motion vector, then the motion vector will be excluded. Also, crude motion vector is used as an initial predictor to reduce computational complexity at the cost of PSNR performance. Similarly, the best initial predictor may be refined by using 3-step search or grid search. For the best search point, fractional-pel may be performed.


When skip/direct MV is not within a valid search range, reference area for skip/direct motion vector may be transferred from external to internal memory; hence, the cost of skip/direct motion vector can be always evaluated.


At final stage, we select a mode (inter or intra) that produces minimal cost. Since a 16x16 block has its own reference window, the reference window should be transferred from external to internal memory. However, if there is an overlapped area between current reference window and neighboring reference window, only non-overlapped area may be transferred.



FIG. 3 is an embodiment of overlapped areas between current and left/upper windows. In FIG. 3. let Left_Overlap and Upper_Overlap denote overlapped area between current and left windows and overlapped area between current and upper windows, respectively. To minimize data transfer, we can calculate total overlapped area (Left _Overlap + Upper Overlap) and transfer non-overlapped area.


Alternatively, larger overlapped area is selected and corresponding non-overlapped area is transferred, which increases data transfer but enables to avoid total overlapped area calculation and complex data transfer. In FIG. 3., the amount of data is (40x40 - Left_Overlap) because Left_Overlap is larger than Upper Overlap, i.e., (40x40 -Left_Overlap) is smaller than (40x40 - Upper _Overlap). Also, left overlapped area may be used to reduce overlapped area calculation and minimize internal memory size.


A skip/direct motion vector may not be within a valid search range. In such a case, the reference area is transferred for the skip/direct motion vector. In one embodiment, the reference area is 22x22 (3 + 3 + 16 = 22 for each direction in H.264), and transferred. There is no overlapped area calculation between skip/direct motion vector reference window and main 40x40 window, i.e., both data transfers are done separately.


In order to ensure real-time operations, instantaneous and average data transfer rate should meet hardware requirement. For example, data transfer rate in IVAHD2.0 is 3584 bytes per 16x16 block for 3840x2160 @ 30 fps. The amount of data transfer (on 1:1 domain) may be estimated with sum of non-overlapped areas of all 16x16 blocks within a frame. Hence, when reference window size is 40x40 for P-type frame, maximum amount of data transfer is 40*40 + 24*24 = 2176 bytes per 16x16 block. For B-type frame, if reference window size is 32x32, maximum amount of data transfer is 2 * (32*32 + 24*24) = 3200 bytes per 16x16 block. In both cases, maximum amount of data transfer is less than 3584 bytes per 16x16 block, which guarantees real-operations. If overlapped areas are considered, actual amount of data transfer is much less than maximum amount.


The required internal memory size (for 1:1 domain) may be estimated by combining overlapped areas between current reference window and left or upper reference window. If Left_Overlap is larger than Upper_Overlap, Upper_Overlap does not need to be stored, and left overlapped area may be released from internal memory immediately after current window finishes motion search. However, If Upper_ Overlap is larger than Left_Overlap, the Upper _Overlap needs to be stored in internal memory until current window finishes motion search.



FIG. 4. is an embodiment depicting estimation of required internal memory size. FIG. 4 shows total internal memory estimation for upper overlapped areas. In FIG. 4, Window(x) denotes reference window of x-th 16x16 block in a frame, bwidth is frame width in 16x16 block unit. Thus, the required internal memory size is sum of Upper_ overlap(x), x = i ~ (i + bwidth - 1) and Upper_overlap(x) > Left overlap(x).


Frame size of 4:1 decimated frame is 1/16 of original frame size. For example, 4:1 decimated frame size for 3840x2160 video is 960x540. If vertical sliding window scheme is used with vertical search range +/-64 (+/-256 on 1:1 domain), total internal memory size for B-type frame is 2 * ((2 * 64 +16) * (960 + 32)) = 285696 bytes per 16x16 block. Maximum horizontal search range is same as frame width (+/-960). The amount of data transfer of vertical sliding window scheme is roughly 16 bytes / 4x4 block on 4:1 domain (luma only), which means we need additional transfer of 16 bytes / 16x16 block on 1:1 domain.


While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.

Claims
  • 1. A method comprising: performing, with the processor, motion estimation on a first version of a frame to generate a first set of motion vectors based on a first set of search areas;determining, with the processor, a second set of search areas for a plurality of blocks in a second version of the frame based on the first set of motion vectors, wherein the second set of search areas is different than the first set of search areas;performing, with the processor, motion estimation on the second version of the frame to generate a second set of motion vectors based on the second set of search areas; andtransferring, by the processor to a memory, a subset of the first set of search areas and the second set of search areas.
  • 2. The method of claim 1, wherein the subset of the first set of search areas and the second set of search areas comprises a non-overlapped area of a current window and a neighboring reference window.
  • 3. The method of claim 1, further comprising: determining a left overlap area between a current reference window and a left reference window;determining an upper overlap area between the current reference window and an upper reference window; andcombining the left overlap area and the upper overlap area to define the overlap area of the current reference window and a non-overlapped area of the current reference window,wherein transferring the subset comprises transferring a non-overlapped area of the current window.
  • 4. The method of claim 1, further comprising: determining a left overlap area between a current reference window and a left reference window;determining an upper overlap area between the current reference window and an upper reference window; anddetermining a larger overlap area of the left overlap area and the upper overlap area,wherein transferring the subset comprises transferring a non-overlapped area of the current window.
  • 5. The method of claim 1, further comprising determining the first set of search areas based on available data transfer bandwidth or based on a size of the memory.
  • 6. The method of claim 1, wherein the memory comprises an internal memory coupled to the processor.
  • 7. The method of claim 1, wherein a first resolution of the first version of the frame is lower than a second resolution of the first version of the frame.
  • 8. The method of claim 1, further comprising generating the first version of the frame by at least decimating the second version of the frame.
  • 9. The method of claim 1, wherein performing motion estimation on the first version of the frame comprises generating a crude motion vector, andwherein performing motion estimation on the second version of the frame comprises generating the second set of motion vectors based on the crude motion vector.
  • 10. An apparatus comprising: means for performing motion estimation on a first version of a frame to generate a first set of motion vectors based on a first set of search areas;means for determining a second set of search areas for a plurality of blocks in a second version of the frame based on the first set of motion vectors, wherein the second set of search areas is different than the first set of search areas;means for performing motion estimation on the second version of the frame to generate a second set of motion vectors based on the second set of search areas; andmeans for transferring, to a memory, a subset of the first set of search areas and the second set of search areas.
  • 11. The apparatus of claim 10, wherein the subset of the first set of search areas and the second set of search areas comprises a non-overlapped area of a current window and a neighboring reference window.
  • 12. The apparatus of claim 10, wherein the memory comprises an internal memory coupled to the means for performing motion estimation on the second version of the frame.
  • 13. The apparatus of claim 10, wherein a first resolution of the first version of the frame is lower than a second resolution of the first version of the frame.
  • 14. The apparatus of claim 10, further comprising means for generating the first version of the frame by at least decimating the second version of the frame.
  • 15. The apparatus of claim 10, wherein the means for performing motion estimation on the first version of the frame comprise means for generating a crude motion vector, andwherein the means for performing motion estimation on the second version of the frame comprise means for generating the second set of motion vectors based on the crude motion vector.
  • 16. A non-transitory computer readable medium including computer instructions that, when executed by one or more processors, cause the one or more processors to: perform motion estimation on a first version of a frame to generate a first set of motion vectors based on a first set of search areas;determine a second set of search areas for a plurality of blocks in a second version of the frame based on the first set of motion vectors, wherein the second set of search areas is different than the first set of search areas;perform motion estimation on the second version of the frame to generate a second set of motion vectors based on the second set of search areas; andtransfer, to a memory, a subset of the first set of search areas and the second set of search areas.
  • 17. The non-transitory computer readable medium of claim 16, wherein the subset of the first set of search areas and the second set of search areas comprises a non-overlapped area of a current window and a neighboring reference window.
  • 18. The non-transitory computer readable medium of claim 16, wherein the memory comprises an internal memory coupled to the one or more processors.
  • 19. The non-transitory computer readable medium of claim 16, wherein a first resolution of the first version of the frame is lower than a second resolution of the first version of the frame.
  • 20. The non-transitory computer readable medium of claim 16, wherein the instructions to perform motion estimation on the first version of the frame comprise instructions to generate a crude motion vector, andwherein the instructions to perform motion estimation on the second version of the frame comprise instructions to generate the second set of motion vectors based on the crude motion vector.
CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. Pat. Application Serial No. 13/542,171, filed Jul. 5, 2012, which is scheduled to issue as U.S. Pat. No. 11,582,479 on Feb. 14, 2023, and which claims priority to U.S. Provisional Pat. Application Serial No. 61/504,587, filed Jul. 5, 2011, the entireties of each of which are incorporated by reference herein.

Provisional Applications (1)
Number Date Country
61504587 Jul 2011 US
Continuations (1)
Number Date Country
Parent 13542171 Jul 2012 US
Child 18108773 US