US20010002205A1 - Encoding digital signals - Google Patents
Encoding digital signals Download PDFInfo
- Publication number
- US20010002205A1 US20010002205A1 US09/088,831 US8883198A US2001002205A1 US 20010002205 A1 US20010002205 A1 US 20010002205A1 US 8883198 A US8883198 A US 8883198A US 2001002205 A1 US2001002205 A1 US 2001002205A1
- Authority
- US
- United States
- Prior art keywords
- prediction parameters
- initial prediction
- motion vectors
- motion
- estimating
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/223—Analysis of motion using block-matching
-
- 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
- H04N19/56—Motion estimation with initialisation of the vector search, e.g. estimating a good candidate to initiate a search
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Compression Or Coding Systems Of Tv Signals (AREA)
- Compression, Expansion, Code Conversion, And Decoders (AREA)
Abstract
Description
- The present invention relates to a method and apparatus for encoding digital signals. The invention is of particular advantage in the compression and transmission of digital video signals.
- Digital video compression systems can reduce the data rate of the transmitted signal by using temporal predictive coding. In the coding process, predictions are made for the reconstruction of the current picture (or frame) based on elements of frames that have been coded in the past. These picture elements (or blocks) can be manipulated in a certain way before they form the basis of the prediction. Prediction parameters (or motion vectors) relate the predicted blocks to earlier blocks. The motion vectors used in the manipulation of the blocks have to be transmitted to the receiver with a residual signal. This minimises the effects of prediction errors and makes it possible to reconstruct the sequence at the receiver.
- Due to the spatial correlation of adjacent picture elements, the motion vectors themselves are coded differentially. This means that the differences between successive motion vectors are coded. Therefore small changes are represented by fewer bits of code than larger ones which are less common.
- The quality of the block prediction is assessed using a distortion measurement which is based on the difference between the predicted block and the block to be coded.
- A problem arises when predictions of approximately equal quality are made from completely different picture areas. There is a danger that a small advantage in prediction quality may be outweighed by a larger code word representing the motion vector. This situation is particularly common when picture areas are corrupted by noise and the motion vectors vary radically from one prediction to the next.
- Accordingly, one object of the present invention is to provide a method and apparatus for improving the selection of motion vectors by using additional information in the motion estimator.
- According to one aspect of the present invention, there is provided a method of generating prediction parameters for a digital coding technique, the method comprising the steps of: estimating a plurality of initial prediction parameters, storing the initial prediction parameters and re-estimating the or each initial prediction parameter in dependence on one or more other said initial prediction parameters, characterised in that the method further comprises repeating the re-estimating step one or more times to generate the prediction parameters.
- According to a second aspect of the present invention there is provided apparatus for generating prediction parameters for a digital coding technique, the apparatus comprising: an estimator for estimating a plurality of initial prediction parameters, a buffer for storing the initial prediction parameters, and a re-estimator for re-estimating the or each initial prediction parameter in dependence on one or more other said initial prediction parameters, characterised in that the re-estimating step is repeated one or more times to generate the prediction parameters.
- An advantage of the present invention lies in the fact that a set of motion vectors can be iteratively improved by using neighbouring (spatial or temporal) motion vectors in the prediction process. This effectively means that the motion vectors in the top left corner of the frame are influenced by motion vectors in the bottom right hand corner, or by motion vectors in future and past frames. As a result, the motion vectors represent the true motion in the video sequence and can be coded using fewer bits.
- Advantageously the present invention can be used in motion compensated noise reduction techniques which require a good estimate of the underlying video motion for optimum performance. The present invention provides an estimate of this motion by being robust to the noise corruption which in the prior art causes neighbouring motion vectors to be radically different. Radically different motion vectors need a higher bandwidth for transmission.
- Reference will now be made, by way of example, to the accompanying drawings, in which:
- FIG. 1 is a simplified diagram of a broadcast system according to one aspect of the present invention;
- FIG. 2 is a block diagram of a digital video encoder in the FIG. 1 system;
- FIG. 3 is a block diagram of one embodiment of the present invention;
- FIG. 4 is an explanatory diagram to illustrate how motion vectors make use of temporal redundancy in a digital video sequence;
- FIG. 5 is an explanatory diagram showing the problems associated with selecting motion vectors using a minimum distortion criterion;
- FIG. 6 is an explanatory diagram showing one effect of the present invention on motion vector estimation.
- FIG. 7 is a diagram showing a comparison of the present invention with the prior art.
- A broadcast system is illustrated in FIG. 1 and includes an encoder11 and a
decoder 15. An input digital video signal is passed to the encoder 11, which produces a compressed outputdigital signal 12. The compressed outputdigital signal 12 requires less bandwidth for transmission. Thecompressed signal 12 is transmitted to areceiver 14 where it is passed to adecoder 15. Thedecoder 15 produces anuncompressed video signal 16. In FIG. 1, the transmission from the encoder 11 to thedecoder 15 is via asatellite 13. Clearly other means of transmission could be used to replace satellite transmission. - FIG. 2 shows a simplified block diagram of a digital video encoder. A current frame (not shown in the diagram) in the
video input signal 10 is passed to amotion estimator 20. Themotion estimator 20 generatesmotion vectors 21 for the current frame relative to a previous frame (reference frame) that is stored in themotion estimator 20. The motion vector selection is explained in FIG. 4. Thesemotion vectors 21 are passed to amotion compensator 22. Themotion compensator 22 generates a predicted frame (not shown in the diagram) using themotion vectors 21 and a stored reference frame. - The predicted frame is passed from the
motion compensator 22 to asubtractor 24 and subtracted from the current frame in the inputdigital video signal 10. This subtraction removes temporal redundancy in the signal. The resultingresidual signal 25 is passed to acompression unit 26. Thecompression unit 26 removes spatial redundancy in the signal, reducing the required bandwidth still further. Thecompressed output signal 27 from thecompression unit 26 is passed to theoutput buffer 28. The amount of compression applied in thecompression unit 26 is controlled by acontrol signal 29. Thecontrol signal 29 varies the amount of compression to prevent theoutput buffer 28 from overflowing or underflowing. - A
decompressed signal 30 from thecompression unit 26 is passed to themotion compensator 22. Thisdecompressed signal 30 is used to generate a reference frame in themotion compensator 22 for subsequent frames. Themotion vectors 21 generated by themotion estimator 20 are also passed to a motion vector variable length coder 23 (MV VLC). The motion vectorvariable length coder 23 compresses themotion vectors 21 by assuming that adjacent motion vectors are similar. Thecoder 23 exploits this similarity by coding the difference between adjacent motion vectors. However, if neighbouring motion vectors are radically different, then this type of coding can prove to be highly inefficient. The coded output from the motion vectorvariable length coder 23 is passed to theoutput buffer 28 for onward transmission. It will be appreciated by those skilled in the art that motion vector estimation could also be performed using alternative embodiments. - FIG. 3 shows one embodiment of the present invention. A current frame in the
video input signal 10 is passed to amotion estimator 20 which again generatesmotion vectors 21 for the current frame relative to a reference frame. Themotion vectors 21 are not passed directly to amotion compensator 22 or to a motion vectorvariable length coder 23. Instead themotion vectors 21 for the current frame are stored in amotion vector buffer 31. The motion vectors in thebuffer 31 are iteratively updated in are-estimator 32 as described with reference to FIG. 6. The updatedmotion vectors 33 are stored again in themotion vector buffer 31 for use in subsequent updates. The number of iterations can be set to a fixed number in acontroller 35 or can be controlled by measuring the effect of each successive update on the motion. Only then will thecontroller 35 indicate that the updatedmotion vectors 34 are to be passed to themotion compensator 22 and to the motion vectorvariable length coder 23. The functionality of the remaining blocks in the video encoder are as described with reference to FIG. 2. - FIG. 4 introduces the concept of using motion estimation to improve the compression of a video signal. Consider the simple case of a video sequence showing a moving
ball 40. FIG. 4 shows twoadjacent frames current frame 41 from thereference frame 42 using motion vectors. In order to estimate the motion vectors for thecurrent frame 41, it is first partitioned into smaller blocks 43 (current blocks). The motion estimator searches for the closest match (reference block) in thereference frame 42 for each of the current blocks 43. In ISO/IEC 13818 (MPEG-2), the search can either be performed in the previous reconstructed frame (P frames) or in future reconstructed frames (B frames) or a combination of the two. Having located the closest match for each block in the current frame, thecurrent blocks 43 are then assignedmotion vector 44 indicating where the reference blocks are located, as demonstrated for one such block in FIG. 4. - Any errors between the current and reference blocks are coded as a residual error signal and transmitted with the motion vectors to allow correct reconstruction. Rather than coding and transmitting each frame independently, better data compression can be achieved by coding and transmitting the frames as a set of motion vectors and a residual frame error signal.
-
- where n is the block index. fm is the pixel value at location m in block Bn. Pm-d
n is the pixel value from the reference frame at location m in block Bn offset by the motion vector dn. The absolute difference of fm and pm-dn is calculated and summed over all the pixels in the block to provide a measure of distortion between the current block and the reference block. The SAD is calculated for all blocks in the search area, and the block with the lowest SAD is used as the reference block for reconstruction. The location of the reference block in relation to the current block is recorded as a motion vector. - The set of motion vectors for each frame is coded differentially, from one motion vector to the next. This improves compression still further, due to the assumption that neighbouring current blocks will have motion vectors to neighbouring reference blocks. Unfortunately, in the presence of noise this is not always the case and neighbouring current blocks can have radically different motion vectors, even though the true underlying motion for that portion of the picture is constant from one block to the next.
- FIG. 5 illustrates this problem. There is shown a series of neighbouring blocks A, B, C and D in the
current frame 50. Blocks A, B, C and D are predicted from blocks A′, B′, C′ and D′ respectively in a reference frame 51. However, it can be seen that reference block C′ is spatially separate from the other reference blocks and block X′ would initially appear to be the better choice. Reference block C′ is selected as it matches block C slightly better than block X′. However the small coding advantage that this would afford is outweighed by the larger codeword required to represent the dramatic change in the associated motion vector. This example is illustrative of how the selection of motion vectors based purely on the closest match may give less than the optimum performance. - These problems can be overcome using the inventive method described in FIG. 6. The motion vectors are represented by a series of arrows on the picture, showing the magnitude and direction of the motion. In an initial pass, the motion vectors are calculated as previously described using SAD or MSE as the block matching criterion. This may produce a set of motion vectors as illustrated in FIG. 6(a). These motion vectors form the basis for the regularisation cycle, where each motion vector is biased towards the motion vectors for the surrounding blocks. By performing this additional cycle, the motion vector choice is now influenced by the surrounding motion vectors. This improves on the previous method by reducing the chance of selecting a motion vector that is in a radically different location over an adjacent motion vector of slightly inferior SAD. The motion vector choice is also biased towards motion vectors of zero length. This ensures start-up and recovery in situations where there are several blocks of exactly equal quality in the search area, e.g. in the case of monochromatic areas.
-
- where α and β are biasing constants, ||dn|| is the length of the current motion vector, ||dn−dm|| is the absolute difference between the current and neighbouring motion vectors. Dn is the set of motion vectors for neighbouring blocks and ln,mε{1,0}, describes the connection between the motion vectors dn and dm. When ln,m= 1, an edge is assumed to lie between the two vectors and vice versa. The threshold at which an edge is inserted is controlled using the parameter δ. When ||dn−dm||>δ it is better to insert an edge and vice-versa. It should be appreciated by someone skilled in the art, that other biasing measures could be used in the error function to obtain similar advantages.
- In summary; the term SAD(dn) biases the selection towards the closest match, the term ||dn|| biases the selection towards small motion vectors and the term ||dn−dm|| biases the selection towards neighbouring motion vectors which encourages smoothness, except across boundaries where ln,m=1. It is also possible to achieve an acceptable performance without this boundary breaking. Performance can also be improved by initialising the vector estimates to the results from the previous frame.
- This update cycle can be further explained with the help of FIG. 6(b), which represents a subsection of FIG. 6(a). The motion vector estimate, dn can be improved by regularisation. The spatially surrounding motion vectors, di,dj,dk,dl are chosen as the neighbouring motion vectors, although it would be equally as valid to chose other motion vectors, including those that are temporally adjacent. The motion vector dn is updated to that shown in FIG. 6(c) using the error function described earlier. dn has been modified to include the neighbouring motion vector estimates and as such, the regularisation step has produced a smoother set of motion vectors. This regularisation step is repeated for the entire update cycle. Note that the updated motion vector dn is subsequently used as a neighbouring motion vector for dk, for example. This update cycle can be repeated to iteratively improve the motion vector estimates over the entire frame. The number of iterations can be set to a fixed number or can be controlled by measuring the effect of each successive update on the motion, as described with reference to FIG. 3.
- The advantage of using this iterative method is demonstrated in FIG. 7. A frame in a video sequence entitled “Renata with Scarf” illustrates the difference between using a minimum distortion criterion in FIG. 7(a) and using the iterative method in FIG. 7(b). The motion vectors are represented by a series of lines on the picture, showing the magnitude and direction of the motion. As demonstrated to the right of the calendar in FIG. 7(a), the motion vectors are pointing in various directions and there appears to be no order to the motion. This is caused by the motion estimator selecting the block with the minimum SAD, regardless if it is representative of true motion in the video sequence. However the motion vectors in FIG. 7(b) are iteratively updated to produce an improved set of motion vectors. It can be seen that regularising the motion vector field produces a smoother overall result which represents the true underlying motion of objects in the video sequence, thus improving the coding efficiency.
- This invention is of use in the estimation of motion vectors for improving digital video compression. In particular, with reference to FIG. 3, the set of
motion vectors 34 can be compressed more efficiently in the motion vectorvariable length coder 23. The compressed signal from the motion vectorvariable length coder 23 is passed to thebuffer 28 for onward transmission. This means that theoutput signal 16 can be transmitted to the receiver using less bandwidth. - This iterative method is also directly applicable to hierarchical motion search strategies where the motion vectors are iteratively refined at each stage of the search. Other potential applications for this iterative approach include motion compensated noise reduction where it is necessary to correctly detect the true underlying motion of the picture.
Claims (22)
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
GB9712651 | 1997-06-18 | ||
GBGB9712651.0A GB9712651D0 (en) | 1997-06-18 | 1997-06-18 | Improvements in or relating to encoding digital signals |
GBGB9712651.0 | 1997-06-18 |
Publications (2)
Publication Number | Publication Date |
---|---|
US20010002205A1 true US20010002205A1 (en) | 2001-05-31 |
US6421383B2 US6421383B2 (en) | 2002-07-16 |
Family
ID=10814372
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/088,831 Expired - Lifetime US6421383B2 (en) | 1997-06-18 | 1998-06-02 | Encoding digital signals |
Country Status (4)
Country | Link |
---|---|
US (1) | US6421383B2 (en) |
EP (1) | EP0886445A3 (en) |
JP (1) | JPH11168387A (en) |
GB (1) | GB9712651D0 (en) |
Cited By (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6580812B1 (en) * | 1998-12-21 | 2003-06-17 | Xerox Corporation | Methods and systems for automatically adding motion lines representing motion to a still image |
US20040028134A1 (en) * | 2002-08-06 | 2004-02-12 | Raghavan Subramaniyan | Method and apparatus for determining block match quality |
US20040156435A1 (en) * | 2003-02-11 | 2004-08-12 | Yuji Itoh | Motion estimation using early decision for goodness of estimation with quick convergence feedback |
US6917651B1 (en) * | 2000-01-28 | 2005-07-12 | Samsung Electronics Co., Ltd. | Variable length coding method and apparatus |
US20050226328A1 (en) * | 2004-03-31 | 2005-10-13 | Raju Hormis | Shared logic for decoding and deinterlacing of compressed video |
US20080170617A1 (en) * | 2007-01-12 | 2008-07-17 | Samsung Electronics Co., Ltd | Apparatus for and method of estimating motion vector |
US20100061458A1 (en) * | 2008-09-11 | 2010-03-11 | General Instrument Corporation | Method and apparatus for fast motion estimation |
CN101841718A (en) * | 2003-09-07 | 2010-09-22 | 微软公司 | Advanced bi-directional predictive coding of interlaced video |
US20110129015A1 (en) * | 2007-09-04 | 2011-06-02 | The Regents Of The University Of California | Hierarchical motion vector processing method, software and devices |
US20110206110A1 (en) * | 2010-02-19 | 2011-08-25 | Lazar Bivolarsky | Data Compression for Video |
US20110206118A1 (en) * | 2010-02-19 | 2011-08-25 | Lazar Bivolarsky | Data Compression for Video |
US20110206131A1 (en) * | 2010-02-19 | 2011-08-25 | Renat Vafin | Entropy Encoding |
US20110206117A1 (en) * | 2010-02-19 | 2011-08-25 | Lazar Bivolarsky | Data Compression for Video |
US8416344B2 (en) | 2007-03-28 | 2013-04-09 | Entropic Communications, Inc. | Iterative method for interpolating video information values |
US20140177716A1 (en) * | 2012-12-21 | 2014-06-26 | Nvidia Corporation | Using an average motion vector for a motion search |
US9313526B2 (en) | 2010-02-19 | 2016-04-12 | Skype | Data compression for video |
Families Citing this family (18)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2000034920A1 (en) * | 1998-12-07 | 2000-06-15 | Koninklijke Philips Electronics N.V. | Motion vector estimation |
US6735249B1 (en) * | 1999-08-11 | 2004-05-11 | Nokia Corporation | Apparatus, and associated method, for forming a compressed motion vector field utilizing predictive motion coding |
EP1128678A1 (en) * | 2000-02-24 | 2001-08-29 | Koninklijke Philips Electronics N.V. | Motion estimation apparatus and method |
US6825885B2 (en) * | 2001-02-13 | 2004-11-30 | Koninklijke Philips Electronics N.V. | Motion information coding and decoding method |
ES2222079B1 (en) * | 2003-02-10 | 2006-04-01 | Fundacion Ibit | APPLIANCE PROVIDER OF IMAGES. |
US7471724B2 (en) * | 2003-06-23 | 2008-12-30 | Vichip Corp. Limited | Method and apparatus for adaptive multiple-dimensional signal sequences encoding/decoding |
US20050013498A1 (en) | 2003-07-18 | 2005-01-20 | Microsoft Corporation | Coding of motion vector information |
US7616692B2 (en) * | 2003-09-07 | 2009-11-10 | Microsoft Corporation | Hybrid motion vector prediction for interlaced forward-predicted fields |
US7567617B2 (en) | 2003-09-07 | 2009-07-28 | Microsoft Corporation | Predicting motion vectors for fields of forward-predicted interlaced video frames |
US7623574B2 (en) * | 2003-09-07 | 2009-11-24 | Microsoft Corporation | Selecting between dominant and non-dominant motion vector predictor polarities |
US7724827B2 (en) | 2003-09-07 | 2010-05-25 | Microsoft Corporation | Multi-layer run level encoding and decoding |
US7860158B2 (en) * | 2004-08-27 | 2010-12-28 | Mitsubishi Electric Research Laboratories Inc. | Coding correlated images using syndrome bits |
US20060233258A1 (en) * | 2005-04-15 | 2006-10-19 | Microsoft Corporation | Scalable motion estimation |
DE102005025634A1 (en) | 2005-06-03 | 2006-12-07 | Micronas Gmbh | Method and device for determining motion vectors |
US8494052B2 (en) * | 2006-04-07 | 2013-07-23 | Microsoft Corporation | Dynamic selection of motion estimation search ranges and extended motion vector ranges |
US8155195B2 (en) * | 2006-04-07 | 2012-04-10 | Microsoft Corporation | Switching distortion metrics during motion estimation |
US20070268964A1 (en) * | 2006-05-22 | 2007-11-22 | Microsoft Corporation | Unit co-location-based motion estimation |
JP4697276B2 (en) * | 2008-07-30 | 2011-06-08 | ソニー株式会社 | Motion vector detection apparatus, motion vector detection method, and program |
Family Cites Families (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
SE469866B (en) | 1991-04-12 | 1993-09-27 | Dv Sweden Ab | Method for estimating motion content in video signals |
US5398068A (en) * | 1993-09-02 | 1995-03-14 | Trustees Of Princeton University | Method and apparatus for determining motion vectors for image sequences |
US5539469A (en) * | 1994-12-30 | 1996-07-23 | Daewoo Electronics Co., Ltd. | Apparatus for determining motion vectors through the use of an adaptive median filtering technique |
US6160846A (en) * | 1995-10-25 | 2000-12-12 | Sarnoff Corporation | Apparatus and method for optimizing the rate control in a coding system |
-
1997
- 1997-06-18 GB GBGB9712651.0A patent/GB9712651D0/en not_active Ceased
-
1998
- 1998-06-02 EP EP98110047A patent/EP0886445A3/en not_active Withdrawn
- 1998-06-02 US US09/088,831 patent/US6421383B2/en not_active Expired - Lifetime
- 1998-06-17 JP JP10205733A patent/JPH11168387A/en active Pending
Cited By (30)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6580812B1 (en) * | 1998-12-21 | 2003-06-17 | Xerox Corporation | Methods and systems for automatically adding motion lines representing motion to a still image |
US6917651B1 (en) * | 2000-01-28 | 2005-07-12 | Samsung Electronics Co., Ltd. | Variable length coding method and apparatus |
US20040028134A1 (en) * | 2002-08-06 | 2004-02-12 | Raghavan Subramaniyan | Method and apparatus for determining block match quality |
US7023921B2 (en) * | 2002-08-06 | 2006-04-04 | Motorola, Inc. | Method and apparatus for determining block match quality |
US7720151B2 (en) * | 2003-02-11 | 2010-05-18 | Texas Instruments Incorporated | Motion estimation using early decision for goodness of estimation with quick convergence feedback |
US20040156435A1 (en) * | 2003-02-11 | 2004-08-12 | Yuji Itoh | Motion estimation using early decision for goodness of estimation with quick convergence feedback |
CN101841718B (en) * | 2003-09-07 | 2013-05-01 | 微软公司 | Advanced bi-directional predictive coding of interlaced video |
CN101841718A (en) * | 2003-09-07 | 2010-09-22 | 微软公司 | Advanced bi-directional predictive coding of interlaced video |
US20050226328A1 (en) * | 2004-03-31 | 2005-10-13 | Raju Hormis | Shared logic for decoding and deinterlacing of compressed video |
US7965770B2 (en) * | 2004-03-31 | 2011-06-21 | Intel Corporation | Shared logic for decoding and deinterlacing of compressed video |
US20080170617A1 (en) * | 2007-01-12 | 2008-07-17 | Samsung Electronics Co., Ltd | Apparatus for and method of estimating motion vector |
US8416344B2 (en) | 2007-03-28 | 2013-04-09 | Entropic Communications, Inc. | Iterative method for interpolating video information values |
US20110129015A1 (en) * | 2007-09-04 | 2011-06-02 | The Regents Of The University Of California | Hierarchical motion vector processing method, software and devices |
US8605786B2 (en) * | 2007-09-04 | 2013-12-10 | The Regents Of The University Of California | Hierarchical motion vector processing method, software and devices |
US20100061458A1 (en) * | 2008-09-11 | 2010-03-11 | General Instrument Corporation | Method and apparatus for fast motion estimation |
US8798152B2 (en) * | 2008-09-11 | 2014-08-05 | General Instrument Corporation | Method and apparatus for fast motion estimation |
US20110206131A1 (en) * | 2010-02-19 | 2011-08-25 | Renat Vafin | Entropy Encoding |
US20110206110A1 (en) * | 2010-02-19 | 2011-08-25 | Lazar Bivolarsky | Data Compression for Video |
US20110206119A1 (en) * | 2010-02-19 | 2011-08-25 | Lazar Bivolarsky | Data Compression for Video |
US20110206117A1 (en) * | 2010-02-19 | 2011-08-25 | Lazar Bivolarsky | Data Compression for Video |
US20110206118A1 (en) * | 2010-02-19 | 2011-08-25 | Lazar Bivolarsky | Data Compression for Video |
US8681873B2 (en) | 2010-02-19 | 2014-03-25 | Skype | Data compression for video |
US9819358B2 (en) | 2010-02-19 | 2017-11-14 | Skype | Entropy encoding based on observed frequency |
US20110206113A1 (en) * | 2010-02-19 | 2011-08-25 | Lazar Bivolarsky | Data Compression for Video |
US8913661B2 (en) | 2010-02-19 | 2014-12-16 | Skype | Motion estimation using block matching indexing |
US9078009B2 (en) | 2010-02-19 | 2015-07-07 | Skype | Data compression for video utilizing non-translational motion information |
US9313526B2 (en) | 2010-02-19 | 2016-04-12 | Skype | Data compression for video |
US9609342B2 (en) | 2010-02-19 | 2017-03-28 | Skype | Compression for frames of a video signal using selected candidate blocks |
US20140177716A1 (en) * | 2012-12-21 | 2014-06-26 | Nvidia Corporation | Using an average motion vector for a motion search |
US10602175B2 (en) * | 2012-12-21 | 2020-03-24 | Nvidia Corporation | Using an average motion vector for a motion search |
Also Published As
Publication number | Publication date |
---|---|
US6421383B2 (en) | 2002-07-16 |
JPH11168387A (en) | 1999-06-22 |
GB9712651D0 (en) | 1997-08-20 |
EP0886445A3 (en) | 2001-02-07 |
EP0886445A2 (en) | 1998-12-23 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US6421383B2 (en) | Encoding digital signals | |
US6628711B1 (en) | Method and apparatus for compensating for jitter in a digital video image | |
US4727422A (en) | Method and apparatus for efficiently communicating image sequence having improved motion compensation | |
US4661849A (en) | Method and apparatus for providing motion estimation signals for communicating image sequences | |
US7801215B2 (en) | Motion estimation technique for digital video encoding applications | |
US6289052B1 (en) | Methods and apparatus for motion estimation using causal templates | |
US5587741A (en) | Apparatus and method for detecting motion vectors to half-pixel accuracy | |
US6591015B1 (en) | Video coding method and apparatus with motion compensation and motion vector estimator | |
EP1378124B1 (en) | Motion information coding and decoding method | |
KR100301833B1 (en) | Error concealment method | |
US20020057741A1 (en) | Video coding system for estimating a motion vector field by using a series of motion estimators of verying complexity | |
EP0734165A2 (en) | Image processing system using pixel-by-pixel motion estimation and frame decimation | |
JPH08242453A (en) | Movement vector presumption device | |
EP0869682A1 (en) | Decoding and coding method of moving image signal, and decoding and coding apparatus of moving image signal using the same | |
US4794455A (en) | Method and apparatus employing adaptive filtering for efficiently communicating image sequences | |
US5001560A (en) | Method and apparatus employing adaptive filtering for efficiently communicating image sequences | |
US20050078751A1 (en) | Method and apparatus for compensating for erroneous motion vectors in image and video data | |
US5612745A (en) | Method and apparatus for detecting occlusion | |
US7324698B2 (en) | Error resilient encoding method for inter-frames of compressed videos | |
US7394855B2 (en) | Error concealing decoding method of intra-frames of compressed videos | |
US9781446B2 (en) | Method for coding and method for decoding a block of an image and corresponding coding and decoding devices | |
US20050074059A1 (en) | Coding images | |
KR100243865B1 (en) | Motion Vector | |
KR100388802B1 (en) | apparatus and method for concealing error | |
KR100209133B1 (en) | Imgae decoder having functions for reconstructing error of motion vectors |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: NDS LIMITED, UNITED KINGDOM Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:BEATTIE, ROBERT;REEL/FRAME:009364/0970 Effective date: 19980713 |
|
AS | Assignment |
Owner name: TANDBERG TELEVISION ASA, NORWAY Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:NDS LIMITED;REEL/FRAME:011419/0628 Effective date: 20001113 |
|
STCF | Information on status: patent grant |
Free format text: PATENTED CASE |
|
FPAY | Fee payment |
Year of fee payment: 4 |
|
AS | Assignment |
Owner name: ERICSSON AB, SWEDEN Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:TANDBERG TELEVISION ASA;REEL/FRAME:022646/0821 Effective date: 20070501 |
|
FPAY | Fee payment |
Year of fee payment: 8 |
|
FPAY | Fee payment |
Year of fee payment: 12 |
|
AS | Assignment |
Owner name: LEONE MEDIA INC., DELAWARE Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:ERICSSON AB;REEL/FRAME:050237/0248 Effective date: 20190131 |
|
AS | Assignment |
Owner name: MK SYSTEMS US SUB-HOLDCO INC., DELAWARE Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:MK SYSTEMS US HOLDCO INC.;REEL/FRAME:050272/0448 Effective date: 20190808 Owner name: MK SYSTEMS US HOLDCO INC., DELAWARE Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:LEONE MEDIA INC.;REEL/FRAME:050265/0490 Effective date: 20190808 |
|
AS | Assignment |
Owner name: MK SYSTEMS USA INC., DELAWARE Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:MK SYSTEMS US SUB-HOLDCO INC.;REEL/FRAME:050277/0946 Effective date: 20190808 |