US20120224786A1 - Hierarchically layered adaptive median motion vector generation and smoothing - Google Patents
Hierarchically layered adaptive median motion vector generation and smoothing Download PDFInfo
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- US20120224786A1 US20120224786A1 US13/473,008 US201213473008A US2012224786A1 US 20120224786 A1 US20120224786 A1 US 20120224786A1 US 201213473008 A US201213473008 A US 201213473008A US 2012224786 A1 US2012224786 A1 US 2012224786A1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/189—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the adaptation method, adaptation tool or adaptation type used for the adaptive coding
- H04N19/196—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the adaptation method, adaptation tool or adaptation type used for the adaptive coding being specially adapted for the computation of encoding parameters, e.g. by averaging previously computed encoding parameters
- H04N19/198—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the adaptation method, adaptation tool or adaptation type used for the adaptive coding being specially adapted for the computation of encoding parameters, e.g. by averaging previously computed encoding parameters including smoothing of a sequence of encoding parameters, e.g. by averaging, by choice of the maximum, minimum or median value
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
- H04N19/503—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving temporal prediction
- H04N19/51—Motion estimation or motion compensation
- H04N19/513—Processing of motion vectors
Abstract
Description
- This application is a continuation of copending U.S. utility application entitled, “Method and System for Hierarchically Layered Adaptive Median Motion Vector Smoothing,” having Ser. No. 11/931,528, filed on Oct. 31, 2007, which is entirely incorporated herein by reference.
- Certain embodiments of the invention relate to processing of video data. More specifically, certain embodiments of the invention relate to a method and system for hierarchically layered adaptive median motion vector smoothing.
- In the past, methods for estimating such motion vectors have been so expensive that it was only cost-effective to perform motion-estimation and/or motion-compensation (ME/MC) in high-end video processors. However, recent advances in technology and reductions in cost have changed this situation, and ME/MC algorithms have become cost-effective in many consumer-level devices. ME/MC is currently being developed for, if not actively used in, current generation televisions, set-top boxes, DVD-players, and various other devices, to perform, for example, temporal filtering, de-interlacing, frame rate conversions, cross chroma reduction.
- Accordingly, in many video processing applications, it may be useful to have knowledge of the motion that occurs from picture to picture. Video processing methods generally strive to accurately model motion between pictures for use with compression algorithms. One method is to double a display rate of a video sequence by repeating every picture twice. However, such picture repetition may result in motion judder or judder. Accordingly, various video processing standards, such as, for example, MPEG1 and MPEG2, may compress video using more sophisticated methods to estimate motion between pictures. Decoding such compressed video data may result in pictures, which may have other artifacts.
- Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of such systems with some aspects of the present invention as set forth in the remainder of the present application with reference to the drawings.
- A system and/or method for hierarchically layered adaptive median motion vector smoothing, substantially as shown in and/or described in connection with at least one of the figures, as set forth more completely in the claims.
- Various advantages, aspects and novel features of the present invention, as well as details of an illustrated embodiment thereof, will be more fully understood from the following description and drawings.
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FIG. 1 is an exemplary diagram of a portion of a mobile terminal, in accordance with an embodiment of the invention. -
FIG. 2A is an exemplary image lattice illustrating initial motion vector locations, in accordance with an embodiment of the invention. -
FIG. 2B is an exemplary image lattice illustrating determining motion vector locations, in accordance with an embodiment of the invention. -
FIG. 3 is a data flow diagram illustrating exemplary multi-layer hierarchical motion estimation, in accordance with an embodiment of the invention. -
FIG. 4A is a diagram illustrating an exemplary initial motion vector search in a quarter resolution image, in accordance with an embodiment of the invention. -
FIG. 4B is a diagram illustrating an exemplary second motion vector search in a half resolution image, in accordance with an embodiment of the invention. -
FIG. 4C is a diagram illustrating an exemplary third motion vector search in a full resolution image, in accordance with an embodiment of the invention. -
FIG. 5 is a data flow diagram illustrating an exemplary hierarchical motion vector search combined with layer motion vector smoothing, in accordance with an embodiment of the invention. -
FIG. 6A is a diagram illustrating exemplary block vector inputs to a motion vector smoothing filter, in accordance with an embodiment of the invention. -
FIG. 6B is a diagram illustrating an exemplary output motion vector generated by a smoothing filter, in accordance with an embodiment of the invention. -
FIG. 7 is a block diagram illustrating an exemplary motion vector smoothing filter, in accordance with an embodiment of the invention. -
FIG. 8 is a flow diagram illustrating exemplary steps for a hierarchically layered adaptive median motion vector smoothing, in accordance with an embodiment of the invention. - Certain embodiments of the invention may be found in a method and system for hierarchically layered adaptive median motion vector smoothing. Aspects of the invention may comprise generating motion vectors for video pictures at each level of a hierarchical motion estimation process. The motion vectors may be generated using a different resolution for each level. The motion vectors generated by the hierarchical motion estimation process may be smooth filtered at each level so as to remove or reduce spurious motion vectors. The motion vectors at a lower level of the hierarchical motion estimation process may be scaled up to match the resolution of the next higher level before being communicated to the next higher level. The resulting scaled up motion vectors may be utilized to generate higher resolution motion vectors.
- The smooth filtering may comprise scalar median filtering and/or vector median filtering. In an exemplary embodiment of the invention, the smooth filtering may receive, as inputs, a plurality of motion vectors, for example, the motion vector being filtered and eight motion vectors from the surrounding video blocks. The number of motion vectors from surrounding video blocks may vary, and accordingly, is not limited to eight. The vector cost values of the nine motion vectors may be compared to a threshold vector cost value, and those motion vectors that have vectors costs above the threshold value may be discarded. Accordingly, the window size of the smoothing filter may be adjusted by the threshold vector cost value used. The threshold vector cost value may also be dynamically changed based on, for example, content of the video pictures.
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FIG. 1 is an exemplary diagram of a portion of a mobile terminal, in accordance with an embodiment of the invention. Referring toFIG. 1 , there is shown amobile terminal 100. Themobile terminal 100 may comprise animage sensor 110, animage processor 112, aprocessor 114, and amemory block 116. Theimage sensor 110 may comprise suitable circuitry and/or logic that may enable capture of light intensity at a plurality of colors, such as, for example, red, green, and blue. The captured light intensity levels may be further processed as video and/or still photograph outputs. These color levels may be converted to, for example, a YUV color space and the resulting image information may be communicated to theimage processor 112 for further processing. - The
image processor 112 may comprise suitable circuitry and/or logic that may enable processing of video information. The processing may comprise, for example, compressing the video information from theimage sensor 110. The video compression may comprise, for example, hierarchically layered adaptive median motion vector smoothing. Theprocessor 114 may determine the mode of operation of various portions of themobile terminal 100. For example, theprocessor 114 may set up data registers in theimage processor block 112 to allow direct memory access (DMA) transfers of video data to thememory block 116. The processor may also communicate instructions to theimage sensor 110 to initiate capturing of images. Thememory block 116 may be used to store image data that may be processed and communicated by theimage processor 112. Thememory block 116 may also be used for storing code and/or data that may be used by theprocessor 114. Thememory block 116 may also be used to store data for other functionalities of themobile terminal 100. For example, thememory block 116 may store data corresponding to voice communication. - In operation, the
processor 114 may initiate image capture by theimage sensor 110. Theimage sensor 110 may communicate the video data corresponding to the captured images to theimage processor 112. Theimage processor 112 may, for example, compress the video data in a suitable format for storing as a file. Hierarchically layered adaptive median motion vector smoothing by theimage processor 112 is discussed with respect toFIGS. 2-8 . The video data in thememory block 116 may be further processed by, for example, theprocessor 114. -
FIGS. 2A and 2B are exemplary image lattices illustrating motion vector estimations, in accordance with an embodiment of the invention. Referring toFIG. 2A , there is shown theimage lattice 200, where theimage lattice 200 may be a representation of a previous picture F. Theimage lattice 200 may comprise a plurality of blocks, where each block may comprise, for example, M pixels in a horizontal direction and N pixels in a vertical direction. For example, M and N may each be 16. Referring toFIG. 2B , there is shown theimage lattice 210, where theimage lattice 210 may be a representation of a present picture FK. Theimage lattice 210 may be similar to theimage lattice 200 with respect to the number of blocks in the image and where each block comprises M×N pixels. Theimage processor 112 may, for example, process image lattices to determine motion estimation between various pictures. - Motion estimation may be an effective but highly complex technique for video compression and other processing systems. To estimate the motion of a block of video, for example, the
block 211 in the picture FK, a search may be initiated to locate a most similar block, or a best matched block, in a previous picture. Based on the search, a motion vector may be generated that may indicate motion from a block in the previous picture to a block in the present picture. For example, the best match for theblock 211 in the present picture FK may be theblock 202 in the previous picture F. Accordingly, the motion vector for theblock 211 may indicate movement from theblock 202 in the picture FK-1 to theblock 211 in the present picture FK. To search for the best matched block, a Full Search (FS) motion estimation may be used, where the algorithm may search through all possible candidates in a search range. This may result in smallest error in matching, or a smallest cost value, but the FS motion estimation may use most resources and most search time. - Accordingly, other search methods, such as, for example, a hierarchical search method, which may have a higher cost value, but a more efficient use of resources and a shorter search time, may be used. Basically, efficiency may be gained by skipping some candidate blocks so that the computational complexity may be lower but the search result may still be close to the best-matched result. The higher cost value may refer to loss of precision. Another method of searching may comprise, for example, a sub-sampling scheme, where an image may be sub-sampled to a smaller, lower resolution image for motion estimation search. Accordingly, these various methods may be combined to reduce a search time while limiting loss of precision. Various embodiments of the invention utilizing hierarchical search with sub-sampled video data is disclosed with respect to
FIGS. 3-5 , and 8. -
FIG. 3 is a data flow diagram illustrating exemplary multi-layer hierarchical motion estimation, in accordance with an embodiment of the invention. Referring toFIG. 3 , there is shown asearch engine 300, which may be a part of theimage processor 112, for example, that may use a multi-layer hierarchical motion estimation algorithm. In an embodiment of the invention, thesearch engine 300 may operate on received video data in small blocks, such as, for example, blocks of 8 pixels by 8 pixels. Accordingly, each picture may comprise a plurality of blocks, and the motion from one picture to a next picture may be modeled in terms of translational shifts of these blocks. Each block may be assigned a two-dimensional (horizontal/vertical) motion vector (MV) that may describe the translational shift of that block. - A portion of the
search engine 300 may comprise, for example, sub-sampling blocks 310 and 320, and search blocks 302, 312, and 322. The sub-sampling blocks 310 and 320 may comprise suitable logic, circuitry, and/or code that may enable receiving video data and generating output video data that may comprise one-half the resolution of the input video data. The search blocks 302, 312, and 322 may comprise suitable logic, circuitry, and/or code that may enable receiving video data for a present picture and a previous picture, and determining a block in the previous picture that may most closely match a block in the present picture. - In operation, input video data may be received as pictures, for example, by the
search engine 300, and communicated to thesub-sampling block 310 and thesearch block 302. The input video data may be received, for example, from theimage sensor 110. Thesub-sampling block 310 may sub-sample the input picture, which may be a full-resolution picture, to generate a lower resolution picture. The sub-sampling may utilize, for example, a factor of 2×2. Accordingly, the full-resolution picture may be down-sampled by a factor of two in both horizontal and vertical directions, and the result may be a half-resolution picture. The half-resolution picture may be communicated to thesearch block 312 and to thesub-sampling block 320. - The
sub-sampling block 320 may sub-sample the half-resolution picture to generate a lower resolution picture. The sub-sampling may also utilize, for example, a factor of 2×2. Accordingly, the half-resolution picture may be down-sampled to a quarter-resolution picture. The quarter-resolution picture may be communicated to thesearch block 322. - The
search block 322 may perform a search to determine a motion estimation for each quarter-resolution block in the present picture FK with respect to a quarter resolution block in the previous picture F. Thesearch block 322 may search in the search range of the previous block FK-1 for a quarter-resolution block that may most closely match the block in the present picture FK. A motion vector may then be generated for each block in the present picture FK. The motion vectors for the quarter-resolution present picture FK may be scaled up by two to account for the sub-sampling by thesub-sampling block 320 and communicated to the nextlevel search block 312. - Accordingly, the
search block 312 may use the motion vectors from thesearch block 322 to refine its search for a half-resolution block in the previous picture FK-1 that may most closely match a half-resolution block in the present picture FK. Thesearch block 312 may be enabled to search within a search range that may be design dependent. The motion vectors for the half-resolution present picture FK may be scaled up by two to account for the sub-sampling by thesub-sampling block 310 and communicated to the nextlevel search block 302. - Similarly, the
search block 302 may use the motion vectors from thesearch block 312 to refine its search for a full-resolution block in the previous picture FK-1 that may most closely match a full-resolution block in the present picture FK. Thesearch block 302 may be enabled to search within a search range that may be design dependent. The motion vector for each full-resolution block in the present picture FK may be output for use by, for example, theimage processor 112 for generating compressed video from the input video data. - Accordingly, block motion estimation using sub-sampled pictures take a wider, more “global” look at the input pictures. This global view of a local area may enable reduction in spurious motion vectors since the lower resolution blocks may act as a low-pass filter for the video information in the pictures. The motion estimations at each level may be refined about a previous result to provide improved results with small details, and the motion estimations may converge to the final full-resolution estimation. This may effectively keep motion estimations in a local region close to the initial results. The search range, or the local region, for each search block may be, for example, programmable by the
processor 114 and/or theimage processor 112. - Various embodiments of the invention may comprise a plurality of levels of search, and the specific number of search levels may be design and/or implementation dependent. Similarly, various embodiments of the invention may comprise sub-sampling video pictures at sub-sampling rates other than 2×2, and the sub-sampling by each of the sub-sampling blocks need not be the same. The specific sub-sampling rate for each sub-sampling block may be controlled by a processor, such as the
image processor 112 and/or theprocessor 114. -
FIGS. 4A , 4B, and 4C illustrate exemplary motion vector searches using multi-layer hierarchical motion estimation, in accordance with an embodiment of the invention. Although an exemplary search description with respect toFIGS. 4A-C is for one block in a video picture, the motion vector search may be made for other portions, including all blocks, in a video picture before the determined motion vectors are communicated to a next level for further searches. Referring toFIG. 4A , there is shown a quarter-resolution picture 400 comprising asearch range 410 that may be used by thesearch block 322, where thesearch range 410 may comprise a plurality of quarter-resolution video blocks about the video block to be matched. - The
search range 410 may comprise, for example, an entire video picture, or a portion of the video picture about the video block for which the search is being made. Thevideo block position 411 may correspond to, for example, a quarter-resolution block in the present picture FK for which a motion estimate may be generated by thesearch block 322. Thevideo block position 412 may correspond to, for example, a quarter-resolution block in the previous picture FK-1 that may best match the quarter-resolution block in thevideo block position 411. Accordingly, a motion vector may be generated for the video block in thevideo block position 411 that may correspond to the motion from the quarter-resolutionvideo block position 412. In addition to the motion vector, a vector cost may be generated, where the vector cost, which may be a measure of distortion, may be generated. The vector cost may be used as an indication of confidence in the motion vector. This motion vector may be scaled up by two to account for the sub-sampling by thesub-sampling block 320 and communicated to the nextlevel search block 312. The scaled motion vector may then be used by thesearch block 312 to perform a motion vector refinement around the result from quarter-resolution search by thesearch block 322. - Referring to
FIG. 4B , there is shown asearch range 420 that may be used by thesearch block 312, where thesearch range 420 may comprise a plurality of half-resolution video blocks. Thesearch range 420 may comprise, for example, a portion of the video picture about thevideo block position 412, where thevideo block position 412 was determined by thesearch block 322. Accordingly, thesearch block 312 may search for a half-resolution video block in thesearch range 420 of the previous picture FK-1 that may best match the half-resolution video block in the half-resolutionvideo block position 412 in the present picture FK. The best match may be, for example, a half-resolution video block in thevideo block position 422. - Accordingly, a motion vector may be generated for the video block in the
video block position 411 that may correspond to the motion from the half-resolutionvideo block position 422. The vector cost generated with respect to thevideo block position 412 may be re-calculated based on the newvideo block position 422. This motion vector may then be scaled up by two to account for the sub-sampling by thesub-sampling block 310 and communicated to the nextlevel search block 302. The scaled motion vector may then be used by thesearch block 302 to perform a motion vector refinement around the result from half-resolution search by thesearch block 312. - Referring to
FIG. 4C , there is shown a full-resolution search range 420 that may be used by thesearch block 302, where the search range may comprise a plurality of full-resolution video blocks. Thesearch range 430 may comprise, for example, a portion of the video picture about thevideo block position 422, where thevideo block position 422 was determined by thesearch block 312. Accordingly, thesearch block 302 may search for a full-resolution video block in the previous picture FK-1 that may best match the full-resolution video block in the full-resolutionvideo block position 422 in the present picture FK. The best match may be, for example, a full-resolution video block in thevideo block position 432. - Accordingly, a motion vector may be generated for the video block in the
video block position 411 that may correspond to motion from the full-resolutionvideo block position 432. Again, the vector cost generated with respect to thevideo block position 422 may be re-calculated based on the newvideo block position 432. The vector cost with respect to thevideo block position 432 may be expected to be lower than the initial vector cost with respect to thevideo block position 412. This motion vector may be used, for example, by theimage processor 112 to generate predictive (P) pictures and/or bi-predictive (B) pictures. - Accordingly, with respect to
FIGS. 4A-4C , at quarter-resolution, the reasonable motion vector search range may be reduced by a factor of 4. This may allow the search to be much smaller in extent and still be able to track fast moving objects. By refining the vectors at the half-resolution level and the full-resolution level, the quality of the motion vectors relative to results may be improved using the initial quarter-resolution search. However, the search range used during these refinement stages may be made relatively small since the best matched video block may tend to be near the motion vector passed up from the lower resolution level. -
FIG. 5 is a data flow diagram illustrating an exemplary hierarchical motion vector search combined with layer motion vector smoothing, in accordance with an embodiment of the invention. Referring toFIG. 5 , there is shown thesearch engine 500 that may comprise search blocks 510, 522, and 532, smoothing filter blocks 512, 524, and 534, andsub-sampling blocks FIG. 3 . The smoothing filter blocks 512, 524, and 534 may comprise suitable logic, circuitry, and/or code that may enable attenuation or removal of spurious motion vectors to leave a more consistent motion vector field. - The
search engine 500, which may be a part of theimage processor 112, for example, may use a multi-layer hierarchical motion estimation algorithm with motion vector smoothing for the motion vectors generated by the search blocks 510, 522, and 532. In an embodiment of the invention, thesearch engine 500 may operate on received video data in small blocks, such as, for example, blocks of 8 pixels by 8 pixels. Accordingly, each picture may comprise a plurality of blocks, and the motion from one picture to a next picture may be modeled in terms of translational shifts of these blocks. Each block may be assigned a two-dimensional (horizontal/vertical) motion vector that may describe the translational shift of that block. - In operation, input video data may be received as pictures, for example, by the
search engine 500, and communicated to thesub-sampling block 520 and thesearch block 510. The input video data may be received, for example, from theimage sensor 110. Thesub-sampling block 520 may sub-sample the input picture, which may be a full-resolution picture, to generate a lower resolution picture. The sub-sampling may be, for example, by a factor of 2×2. Accordingly, the full-resolution picture may be down-sampled by a factor of two in both horizontal and vertical directions, and the result may be a half-resolution picture. The half-resolution picture may be communicated to thesearch block 522 and to thesub-sampling block 530. - The
sub-sampling block 530 may sub-sample the half-resolution picture to generate a lower resolution picture. The sub-sampling may also be, for example, by a factor of 2×2. Accordingly, the half-resolution picture may be down-sampled to a quarter-resolution picture. The quarter-resolution picture may be communicated to thesearch block 532. - The
search block 532 may perform a search to determine a motion estimation for each quarter-resolution block in the present picture FK with respect to a quarter resolution block in the previous picture F. Thesearch block 532 may search in the search range of the previous block FK-1 for a quarter-resolution block that may most closely match the block in the present picture FK. A motion vector may then be generated for each block in the present picture FK. - The motion vectors for the quarter-resolution present picture FK may be scaled up by two to account for the sub-sampling by the
sub-sampling block 530. The scaled motion vectors may be communicated to the smoothingfilter block 534. The smoothingfilter block 534 may filter the motion vectors to remove spurious motion vectors to generate a more consistent motion vector field. An embodiment of the smoothing filter blocks 512, 524, and 534 is described in more detail with respect toFIGS. 6A , 6B, and 7. The filtered motion vectors for the present quarter-resolution picture FK may be communicated to thesearch block 522. - Accordingly, the
search block 522 may use the motion vectors from the smoothingfilter block 534 to refine its search for a half-resolution block in the previous picture FK-1 that may most closely match a half-resolution block in the present picture FK. Thesearch block 522 may make its search within a search range that may be design dependent. A motion vector may then be generated for each block in the half-resolution present picture FK. The motion vectors for the half-resolution present picture FK may be scaled up by two to account for the sub-sampling by thesub-sampling block 520 and communicated to the smoothingfilter block 524. The smoothingfilter block 524 may filter the motion vectors to remove spurious motion vectors to generate a more consistent motion vector field. The filtered motion vectors for the half-resolution present picture FK may be communicated to thesearch block 510. - The
search block 510 may use the motion vectors from the smoothingfilter block 524 to refine its search for a full-resolution block in the previous picture FK-1 that may most closely match a full-resolution block in the present picture FK. Thesearch block 510 may make its search within a search range that may be design dependent. A motion vector may then be generated for each block in the full-resolution present picture FK. The motion vectors for the full-resolution present picture FK may be communicated to the smoothingfilter block 512. The smoothingfilter block 512 may filter the motion vectors to remove spurious motion vectors to generate a more consistent motion vector field. The filtered motion vectors for the full-resolution present picture FK may be output for use by, for example, theimage processor 112 for generating compressed video from the input video data. - The block motion estimation using sub-sampled pictures takes a wider, more “global” look at the input pictures. This global view of a local area may result in a reduction of spurious motion vectors since the lower resolution blocks may act as a low-pass filter for the video information in the pictures. The motion estimations at each level may refined about a previous result to provide improved results with small details, and the motion estimations may converge about the original lowest resolution estimation. This may effectively keep motion estimations in a local region close to the initial results. The search range, or the local region, for each search block may be, for example, programmable by the
processor 114 and/or theimage processor 112. - Various embodiments of the invention may comprise a plurality of levels of search, and the specific number of search levels may be design and/or implementation dependent. Similarly, various embodiments of the invention may comprise sub-sampling video pictures by factors other than sub-sample rate of 2×2, and the sub-sampling by each of the sub-sampling blocks need not be the same. The specific sub-sampling rate for each sub-sampling block may be controlled by a processor, such as the
image processor 112 and/or theprocessor 114. - While an embodiment of the invention is described using a smoothing filter for the outputs of the search blocks 510, 522, and 532, the invention need not be so limited. For example, various embodiments of the invention may apply smoothing filtering for only a portion of search blocks that may be used in a search engine. Additionally, while an embodiment of the invention described the output motion vectors as being scaled by the search blocks 532 and 522, the invention need not be so limited. For example, the scaling may be performed by the smoothing
filters 534 and/or 524. -
FIG. 6A is a diagram illustrating exemplary block vector inputs to a motion vector smoothing filter, in accordance with an embodiment of the invention.FIG. 6B is a diagram illustrating an exemplary output motion vector generated by a smoothing filter, in accordance with an embodiment of the invention.FIGS. 6A and 6B are illustrations of exemplary block vector inputs to a motion vector smoothing filter resulting in an output motion vector generated by a smoothing filter, in accordance with an embodiment of the invention. Referring toFIG. 6A , there is shown a diagram 600 of a cluster ofmotion vectors 602 . . . 618. Themotion vectors 602 . . . 618 may be used to generate an output motion vector that may correspond to themotion vector MV_E 610. Accordingly, each motion vector in a picture may be smooth filtered using the motion vectors surrounding it. Referring toFIG. 6B , there is shown anoutput motion vector 650 generated by a smoothing filter block, such as, for example, the smoothingfilter block - In operation, the
motion vector 610 may be filtered using themotion vectors FIG. 7 . - For motion vectors at the edges of the picture, various embodiments of the invention may use those motion vectors that are available. For example, if the
motion vector 610 is the first motion vector for a picture, only the threemotion vectors motion vector 610 is the first motion vector for a picture, themotion vector 610 may be replicated and used in place of themissing motion vectors -
FIG. 7 is a block diagram illustrating an exemplary motion vector smoothing filter, in accordance with an embodiment of the invention. Referring toFIG. 7 , there is shown a smoothingfilter block 700 comprising a vectorcost thresholding block 702 and amedian filter block 704. The smoothingfilter block 700 may be similar to, for example, the smoothing filter blocks 512, 524, and 534. The vectorcost thresholding block 702 may comprise suitable logic, circuitry, and/or code that may enable determining whether input motion vectors may have vector costs above a threshold vector cost. Those motion vectors with vector costs that are above the threshold vector cost may be discarded. Accordingly, only those motion vectors that have vector costs less than or equal to the threshold vector cost may be output. Themedian filter block 704 may comprise suitable logic, circuitry, and/or code that may enable determining an output motion vector that may be a median of the input motion vectors. - In operation, the motion vectors MVA, . . . , MV_E, . . . MVI may be communicated to smoothing
filter block 700 to generate a filtered output motion vector Output_MV that may correspond to the motion vector MV_E. The motion vectors MV_A, . . . , MV_E, . . . MV_I may correspond to the motion vectors described with respect toFIG. 6A , and the motion vector Output_MV output by thefilter block 700 may correspond to the motion vector Output_MV described with respect toFIG. 6B . - The motion vectors MV_A, . . . , MV_E, . . . MV_I may be received by the vector
cost thresholding block 702. The vector cost values of the each of the motion vectors MV_A, . . . , MV_E, . . . MV_I may be compared to a threshold vector cost value, where the threshold vector cost value may be programmable, for example, by theprocessor 114. Any motion vector whose vector cost is above this threshold vector cost may be ignored. The remaining motion vectors may be communicated to themedian filter block 704. Accordingly, the threshold vector cost value may be used to adaptively adjust the size and shape of the median filter window. Various embodiments of the invention may also adjust the threshold vector cost value based, for example, on the content of the video pictures. When the vector cost values of all the motion vectors input to the vectorcost thresholding block 702 are above the threshold vector cost value, then just the motion vector that is being filtered, for example, the motion vector MV_E, may be communicated to themedian filter block 704. - The
median filter block 704 may perform a median operation upon the input motion vectors to generate an output motion vector for the smoothingfilter block 700. In the exemplarymedian filter block 704, the number of input vectors may range from one to nine. Themedian filter block 704 may generate a motion vector that may be a median of the input motion vectors. This median filtering process may be either a scalar or vector median filtering process. - The scalar median filtering process may comprise a 1-dimensional operation that may be performed independently on dx and dy components of the motion vectors. The dx and dy components may be horizontal and vertical components, respectively, of a motion vector. In general, the median of either the dx or dy component may be determined by sorting all input motion vectors into, for example, an increasing order and selecting the value at the midpoint of the motion vectors. In instances when there may be an even number of motion vectors, the
median filter block 704 may, for example, select one of the two motion vectors that may be closest to a median value, or interpolate an output motion vector from the two motion vectors that may be closest to the median value. The specific scalar median operation may be design dependent. - The vector median filtering process may comprise a 2-dimensional operation that may be performed jointly on the dx and dy components of the input motion vectors. The vector median (VM) operation may be defined as determining an input vector that may minimize the “distance” to all other input motion vectors, as represented below:
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- The parameter ‘L’ may be the order of the “distance” measurement. For example, L=1 may imply an absolute value, and L=2 may imply a squared Euclidian distance.
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FIG. 8 is a flow diagram illustrating exemplary steps for a hierarchically layered adaptive median motion vector smoothing, in accordance with an embodiment of the invention. Referring toFIG. 8 , there are shownsteps 800 to 814. Instep 800, thesearch engine 500 may receive full resolution video pictures. Instep 802, each full resolution video picture may be sampled to produce lower resolution pictures, and the appropriate lower resolution pictures may be communicated to the appropriate level of motion vector generation. For example, if there are 3 levels of motion vector generation, the top level may perform motion vector generation using the full-resolution pictures, the middle level may perform motion vector generation using half-resolution pictures, and the bottom level may perform motion vector generation using quarter-resolution pictures. Similarly, if there are N levels of motion vector generation, then N-1 lower resolution pictures may be generated for use by the lower N-1 levels, where the specific resolution at each level may be controlled, for example, by theprocessor 114 and/or theimage processor 112. - Accordingly, with 3 levels of search, the
search block 532 at the bottom level may receive the quarter-resolution picture from, for example, thesub-sampling block 530. At the middle level, thesearch block 522 may receive the half-resolution picture from, for example, thesub-sampling block 520. At the top level, thesearch block 510 may use the full-resolution resolution picture. - In
step 804, a motion vector search may be executed at the lowest search level. Accordingly, in instances where there are three levels of motion vector search, the first motion vector search may be performed by, for example, thesearch block 532 at the bottom level using quarter-resolution pictures. Instep 806, a search block, for example, thesearch block 532 for the bottom level, thesearch block 522 for the middle level, or thesearch block 510 for the top level, may generate motion vectors for each of the blocks in a picture. The generated motion vectors may be communicated to a corresponding smoothing filter block, for example, the smoothingfilter block step 808, the appropriate smoothing filter block may filter the motion vectors to remove spurious motion vectors. - In
step 810, a determination may be made as to whether the present search level may be the highest search level. If so, the next step may bestep 814. Otherwise, the next step may bestep 812. Instep 812, the filtered motion vectors may be communicated to the next level up. Prior to communicating the filtered motion vectors to the next level of search, the filtered motion vectors may be scaled appropriately to compensate for the higher resolution at the next level. For example, if the next level has a resolution that is better by a factor of two in the horizontal and vertical directions, the scaling may utilize a factor of two in each direction. The scaling may be performed, for example, by thesearch block 532 or the smoothingfilter block 534. The next step may bestep 806. - In
step 812, the smoothed motion vectors may be output for further processing by, for example, theimage processor 112. Theimage processor 112 may, for example, use the motion vectors for generating a compressed video file. - In accordance with an embodiment of the invention, aspects of an exemplary system may comprise the
search engine 500 generating motion vectors for video pictures at each level of a hierarchical motion estimation process. The motion vectors may be generated, for example, by the search blocks 510, 522, and 532. The search engine at each level of the hierarchical motion estimation process may receive progressively lower resolution video pictures. For example, the full resolution video picture may be sub-sampled by a factor or 2 by thesub-sampling block 520 in both the horizontal and vertical directions to generate half-resolution video pictures. The half-resolution pictures may be further sub-sampled by a factor of 2 by thesub-sampling block 530 to generate quarter-resolution video pictures. - The quarter resolution pictures may be used by the
search block 532 to generate motion vectors, which may be filtered by the smoothingfilter block 534. Thesearch block 522 may use the half-resolution video pictures and the filtered motion vectors output by the smoothingfilter block 534 to generate more refined motion vectors. Since thesearch block 522 may use half-resolution video pictures, the filtered motion vectors from the smoothingfilter block 534 may need to be scaled up to a higher resolution to compensate for the sub-sampling by thesub-sampling block 530. Accordingly, either thesearch block 532 may scale up motion vectors prior to communicating the motion vectors to the smoothingfilter block 534, or the smoothingfilter block 534 may need to scale up the motion vectors before communicating the smooth filtered motion vectors to thesearch block 522. - Similarly, the
search block 522 may scale up motion vectors prior to communicating the motion vectors to the smoothingfilter block 524, or the smoothingfilter block 524 may need to scale up the motion vectors before communicating the smooth filtered motion vectors to thesearch block 510. Thesearch block 510 may generate further refined motion vectors based on the smoothed motion vectors from the smoothingfilter block 524 and the full-resolution video pictures. - The smooth filtering by the smooth filtering blocks 512, 524, and/or 534 may comprise scalar median filtering or vector median filtering. The smooth filtering blocks 512, 524, and/or 534 may have as inputs a plurality of motion vectors. For example, the smooth filtering blocks 512, 524, and/or 534 may have as inputs the motion vector to be filtered, and eight motion vectors from blocks that may be surrounding neighbors of that motion vector. The vector costs of the nine motion vectors may be compared to a threshold vector cost value by the vector
cost thresholding block 702 to determine which of those nine motion vector may be used for filtering. For example, a motion vector whose vector cost value may be above the threshold vector cost value may be discarded. The motion vectors that are not discarded may be communicated to themedian filter block 704, which may select a motion vector that may be a median of the motion vectors input to themedian filter block 704. Accordingly, the threshold vector cost value used for themedian filter block 704 may result in using those motion vectors that appear most reliable. This may, for example, effectively adjust the size and/or shape of the median filter. Various embodiments of the invention may also dynamically change the threshold vector cost value of the median filter block 704 based on content of the video pictures. - Another embodiment of the invention may provide a machine-readable storage, having stored thereon, a computer program having at least one code section executable by a machine, thereby causing the machine to perform the steps as described above for hierarchically layered adaptive median motion vector smoothing.
- Accordingly, the present invention may be realized in hardware, software, or a combination of hardware and software. The present invention may be realized in a centralized fashion in at least one computer system, or in a distributed fashion where different elements are spread across several interconnected computer systems. Any kind of computer system or other apparatus adapted for carrying out the methods described herein is suited. A typical combination of hardware and software may be a general-purpose computer system with a computer program that, when being loaded and executed, controls the computer system such that it carries out the methods described herein.
- The present invention may also be embedded in a computer program product, which comprises all the features enabling the implementation of the methods described herein, and which when loaded in a computer system is able to carry out these methods. Computer program in the present context means any expression, in any language, code or notation, of a set of instructions intended to cause a system having an information processing capability to perform a particular function either directly or after either or both of the following: a) conversion to another language, code or notation; b) reproduction in a different material form.
- While the present invention has been described with reference to certain embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the scope of the present invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the present invention without departing from its scope. Therefore, it is intended that the present invention not be limited to the particular embodiment disclosed, but that the present invention will comprise all embodiments falling within the scope of the appended claims.
Claims (20)
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Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2015009132A1 (en) * | 2013-07-19 | 2015-01-22 | Samsung Electronics Co., Ltd. | Hierarchical motion estimation method and apparatus based on adaptive sampling |
Families Citing this family (34)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7714838B2 (en) * | 2006-04-27 | 2010-05-11 | Research In Motion Limited | Handheld electronic device having hidden sound openings offset from an audio source |
US20090100482A1 (en) * | 2007-10-16 | 2009-04-16 | Rodriguez Arturo A | Conveyance of Concatenation Properties and Picture Orderness in a Video Stream |
US8875199B2 (en) * | 2006-11-13 | 2014-10-28 | Cisco Technology, Inc. | Indicating picture usefulness for playback optimization |
US20080115175A1 (en) * | 2006-11-13 | 2008-05-15 | Rodriguez Arturo A | System and method for signaling characteristics of pictures' interdependencies |
US20090180546A1 (en) | 2008-01-09 | 2009-07-16 | Rodriguez Arturo A | Assistance for processing pictures in concatenated video streams |
US8416859B2 (en) * | 2006-11-13 | 2013-04-09 | Cisco Technology, Inc. | Signalling and extraction in compressed video of pictures belonging to interdependency tiers |
US8804845B2 (en) * | 2007-07-31 | 2014-08-12 | Cisco Technology, Inc. | Non-enhancing media redundancy coding for mitigating transmission impairments |
US8958486B2 (en) * | 2007-07-31 | 2015-02-17 | Cisco Technology, Inc. | Simultaneous processing of media and redundancy streams for mitigating impairments |
US8718388B2 (en) * | 2007-12-11 | 2014-05-06 | Cisco Technology, Inc. | Video processing with tiered interdependencies of pictures |
US8416858B2 (en) * | 2008-02-29 | 2013-04-09 | Cisco Technology, Inc. | Signalling picture encoding schemes and associated picture properties |
US8175160B1 (en) * | 2008-06-09 | 2012-05-08 | Nvidia Corporation | System, method, and computer program product for refining motion vectors |
US8886022B2 (en) * | 2008-06-12 | 2014-11-11 | Cisco Technology, Inc. | Picture interdependencies signals in context of MMCO to assist stream manipulation |
US8699578B2 (en) * | 2008-06-17 | 2014-04-15 | Cisco Technology, Inc. | Methods and systems for processing multi-latticed video streams |
US8705631B2 (en) * | 2008-06-17 | 2014-04-22 | Cisco Technology, Inc. | Time-shifted transport of multi-latticed video for resiliency from burst-error effects |
US8971402B2 (en) * | 2008-06-17 | 2015-03-03 | Cisco Technology, Inc. | Processing of impaired and incomplete multi-latticed video streams |
US20090323822A1 (en) * | 2008-06-25 | 2009-12-31 | Rodriguez Arturo A | Support for blocking trick mode operations |
CN102124745A (en) * | 2008-08-26 | 2011-07-13 | 升级芯片技术公司 | Apparatus and method for converting 2D image signals into 3D image signals |
US8259814B2 (en) * | 2008-11-12 | 2012-09-04 | Cisco Technology, Inc. | Processing of a video program having plural processed representations of a single video signal for reconstruction and output |
US8326131B2 (en) * | 2009-02-20 | 2012-12-04 | Cisco Technology, Inc. | Signalling of decodable sub-sequences |
US8782261B1 (en) | 2009-04-03 | 2014-07-15 | Cisco Technology, Inc. | System and method for authorization of segment boundary notifications |
US8949883B2 (en) | 2009-05-12 | 2015-02-03 | Cisco Technology, Inc. | Signalling buffer characteristics for splicing operations of video streams |
US8279926B2 (en) | 2009-06-18 | 2012-10-02 | Cisco Technology, Inc. | Dynamic streaming with latticed representations of video |
KR101441874B1 (en) * | 2009-08-21 | 2014-09-25 | 에스케이텔레콤 주식회사 | Video Coding Method and Apparatus by Using Adaptive Motion Vector Resolution |
WO2011021914A2 (en) | 2009-08-21 | 2011-02-24 | 에스케이텔레콤 주식회사 | Method and apparatus for encoding/decoding images using adaptive motion vector resolution |
US20110222837A1 (en) * | 2010-03-11 | 2011-09-15 | Cisco Technology, Inc. | Management of picture referencing in video streams for plural playback modes |
US9832428B2 (en) | 2012-12-27 | 2017-11-28 | Kateeva, Inc. | Fast measurement of droplet parameters in industrial printing system |
JP6147172B2 (en) * | 2013-11-20 | 2017-06-14 | キヤノン株式会社 | Imaging apparatus, image processing apparatus, image processing method, and program |
US10621731B1 (en) * | 2016-05-31 | 2020-04-14 | NGCodec Inc. | Apparatus and method for efficient motion estimation for different block sizes |
CN108632501B (en) * | 2017-03-23 | 2020-07-03 | 展讯通信(上海)有限公司 | Video anti-shake method and device and mobile terminal |
US10152822B2 (en) * | 2017-04-01 | 2018-12-11 | Intel Corporation | Motion biased foveated renderer |
US10319064B2 (en) | 2017-04-10 | 2019-06-11 | Intel Corporation | Graphics anti-aliasing resolve with stencil mask |
US10733783B2 (en) * | 2018-10-09 | 2020-08-04 | Valve Corporation | Motion smoothing for re-projected frames |
US11558637B1 (en) * | 2019-12-16 | 2023-01-17 | Meta Platforms, Inc. | Unified search window to support multiple video encoding standards |
US11363247B2 (en) | 2020-02-14 | 2022-06-14 | Valve Corporation | Motion smoothing in a distributed system |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20030086497A1 (en) * | 2001-11-08 | 2003-05-08 | Mitsubishi Denki Kabushiki Kaisha | Motion vector detecting device improved in detection speed of motion vectors and system employing the same devices |
US20040013201A1 (en) * | 2002-07-18 | 2004-01-22 | Samsung Electronics Co., Ltd | Method and apparatus for estimating a motion using a hierarchical search and an image encoding system adopting the method and apparatus |
US20050232499A1 (en) * | 2004-04-13 | 2005-10-20 | Samsung Electronics Co., Ltd. | Method for motion estimation of video frame and video encoder using the method |
US20080101469A1 (en) * | 2006-10-31 | 2008-05-01 | Motorola, Inc. | Method and apparatus for adaptive noise filtering of pixel data |
US20110080955A1 (en) * | 2004-07-20 | 2011-04-07 | Qualcomm Incorporated | Method and apparatus for motion vector processing |
US20110305275A1 (en) * | 2006-03-03 | 2011-12-15 | Alexandros Eleftheriadis | System and method for providing error resilence, random access and rate control in scalable video communications |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7480334B2 (en) * | 2003-12-23 | 2009-01-20 | Genesis Microchip Inc. | Temporal motion vector filtering |
US8144778B2 (en) * | 2007-02-22 | 2012-03-27 | Sigma Designs, Inc. | Motion compensated frame rate conversion system and method |
-
2007
- 2007-10-31 US US11/931,528 patent/US8208551B2/en not_active Expired - Fee Related
-
2012
- 2012-05-16 US US13/473,008 patent/US20120224786A1/en not_active Abandoned
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20030086497A1 (en) * | 2001-11-08 | 2003-05-08 | Mitsubishi Denki Kabushiki Kaisha | Motion vector detecting device improved in detection speed of motion vectors and system employing the same devices |
US20040013201A1 (en) * | 2002-07-18 | 2004-01-22 | Samsung Electronics Co., Ltd | Method and apparatus for estimating a motion using a hierarchical search and an image encoding system adopting the method and apparatus |
US20050232499A1 (en) * | 2004-04-13 | 2005-10-20 | Samsung Electronics Co., Ltd. | Method for motion estimation of video frame and video encoder using the method |
US20110080955A1 (en) * | 2004-07-20 | 2011-04-07 | Qualcomm Incorporated | Method and apparatus for motion vector processing |
US20110305275A1 (en) * | 2006-03-03 | 2011-12-15 | Alexandros Eleftheriadis | System and method for providing error resilence, random access and rate control in scalable video communications |
US20080101469A1 (en) * | 2006-10-31 | 2008-05-01 | Motorola, Inc. | Method and apparatus for adaptive noise filtering of pixel data |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2015009132A1 (en) * | 2013-07-19 | 2015-01-22 | Samsung Electronics Co., Ltd. | Hierarchical motion estimation method and apparatus based on adaptive sampling |
CN105580371A (en) * | 2013-07-19 | 2016-05-11 | 三星电子株式会社 | Hierarchical motion estimation method and apparatus based on adaptive sampling |
US9560377B2 (en) | 2013-07-19 | 2017-01-31 | Samsung Electronics Co., Ltd. | Hierarchical motion estimation method and apparatus based on adaptive sampling |
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