WO2002093934A1 - Compression et transmission d'images - Google Patents

Compression et transmission d'images Download PDF

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Publication number
WO2002093934A1
WO2002093934A1 PCT/GB2002/002236 GB0202236W WO02093934A1 WO 2002093934 A1 WO2002093934 A1 WO 2002093934A1 GB 0202236 W GB0202236 W GB 0202236W WO 02093934 A1 WO02093934 A1 WO 02093934A1
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WO
WIPO (PCT)
Prior art keywords
motion vectors
array
hash values
frame
generating
Prior art date
Application number
PCT/GB2002/002236
Other languages
English (en)
Inventor
Farrukh N. Alavi
G. M. Megson
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Salgen Systems Limited
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Publication date
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Publication of WO2002093934A1 publication Critical patent/WO2002093934A1/fr

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Classifications

    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M7/00—Conversion of a code where information is represented by a given sequence or number of digits to a code where the same, similar or subset of information is represented by a different sequence or number of digits
    • H03M7/30—Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction
    • H03M7/3084—Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction using adaptive string matching, e.g. the Lempel-Ziv method
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • G06T9/008—Vector quantisation
    • 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
    • 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
    • H04N19/517—Processing of motion vectors by encoding
    • 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
    • H04N19/90—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using coding techniques not provided for in groups H04N19/10-H04N19/85, e.g. fractals
    • H04N19/94—Vector quantisation

Definitions

  • This invention relates to a method and apparatus for compression of images, in particular moving images such as video sequences and the like, for transmission across a communication network.
  • Digital video has been developed to a great extent over recent years, and in view of the large range of applications to which it lends itself-, particularly with the very high uptake- and- growth in personal computers and workstations and the popularity of the global Internet, substantial research and development has been dedicated to the development of techniques for compression, decompression and transmission of video. In general, the aim is to improve efficiency of compression as well as the effectiveness of the transport medium.
  • the main aim is to reduce both storage and transmission costs, i.e. to improve coding efficiency.
  • one of the main concerns is the inherent trade-off between coding efficiency and video fidelity.
  • Industry standards such as H.261 and MPEG define standard formats for compressed video data (but not implementations) , such that video fidelity can be improved as better codecs are developed without having to redefine the standard.
  • the defined standards enable a range of bitrates to be supported so that the quality of the reproduced video becomes a function of the cost of the hardware that the user can afford.
  • MPEG specifies both a syntax and a semantics for a legal video bitstream at the encoder stage, and a definition for synchronisation and demultiplexing of the bitstream into its constituent parts (i.e. video, audio and other data) at the decoder stage, the latter permitting the video playback quality to scale with the abilities of the target hardware.
  • the video algorithms defined by MPEG are based on a class of video compression algorithms that aim to maximally reduce the natural spatio-temporal redundancy both within and between video frames in order to deliver compression.
  • a key feature to exploit in such redundancy elimination is that of the motion of rigid bodies in a sequence of frames .
  • Algorithms which attempt to achieve this effect are known as motion compensation algorithms.
  • BMA block-matching algorithms
  • the block matching algorithm (BMA) remains the most widely used, primarily for the simplicity of its concept and its hardware realisability.
  • the BMA typically begins by partitioning a frame of video pixels into non-overlapping macroblocks of size N x N. Each macroblock in the frame being encoded (the 'current block') is compared with potential matches ('candidate blocks') in the previous, or reference, frame. For a maximum vector displacement of &> pixels, a given macroblock is searched within a search window of size (N+2to)x (N+2&) , as shown in Figure 1 of the drawings. The range of the motion vector is constrained by controlling the size of the search window.
  • the displacement is taken to be that comparison which maximises or minimises a function, a distortion measure, representing the matching criterion.
  • a function a distortion measure
  • Many such functions have been proposed, such as the cross-correlation function (CCF) , the mean square error (MSE) , the mean absolute error (MAE) and the cross-search algorithm (CSA) .
  • block matching algorithms represent a tradeoff between block reconstruction accuracy and hardware/computational expense vis a vis pel-recursive techniques.
  • the magnitude of the motion vectors generated by means of block-matching can be relatively large, which is counter-productive within a compression strategy, especially in the case where the video data is to be transmitted at a relatively low bitrate, in which case the proportion of the transmission burst assigned to motion vectors can become disproportionate. It is for this reason that residuals from motion estimation are first compressed themselves (by means of a lossy transform encoder and an entropy encoder) before transmission.
  • This encoding scheme has been adopted by the MPEG, H.261 and H.263 standards.
  • a method of compressing image data comprising the steps of generating a set of motion vectors representative of one or more image frames, generating, by means of a predetermined hash function a set of hash values corresponding to said motion vectors, and storing as a codebook said hash values in the form .of a table or array.
  • an apparatus for compressing image data comprising means, for generating a set of motion vectors representative of one or more image frames, means for generating, using a predetermined hash function, a set of hash values corresponding to said motion vectors, and codebook means for storing said hash values in the form of a table or array.
  • a method of compressing image data comprising the steps of generating a set of motion vectors representative of one or more image frames, storing as a codebook data representative of said motion vectors in the form of a table or array, and using vector quantisation to index the data stored in said table or array for retrieval of said data by decoding means .
  • an apparatus for compressing image data comprising means for generating a set of motion vectors representative of one or more image frames, codebook means for storing data representative of said motion vectors in the form of a table or array, and vector quantisation means for indexing the data stored in said table or array so that it can be retrieved.
  • Figure 1 is a schematic diagram illustrating a macroblock and search window used in a BMA compression technique according to the prior art
  • Figure 2 Is a schematic diagram illustrating the integration of a vector quantiser codebook with a hash table, the diagram showing a hash table with buckets, each with M slots per bucket ;
  • FIG. 3 is a schematic diagram illustrating an exemplary embodiment of hardware for Vector Quantised Hashing (VQH) the name of our proposed algorithm for motion estimation; and
  • look-up table The concept of a look-up table is well-known in engineering, and may be defined as a set of (name, attribute) pairings for storing data items. There are three basic operations which may be required to be performed on such a look-up table :
  • hash table For the purpose of the present description, assume that the size of the hash table is fixed (i.e. 'static hashing' as opposed to 'dynamic hashing' in which the table size may vary) .
  • the address of a data item x stored within the hash table may be computed by evaluating the hash function h (x) .
  • VQ vector quantisation
  • VQ is essentially the multi-dimensional generalisation of scalar quantisation, as is commonly employed in analog-to- digital conversion processes.
  • X is an N-dimensional source vector
  • VQ is a mapping such that:
  • C is an L-dimensional set, L ⁇ N, such that
  • C is usually termed the 'codebook', and the Y ⁇ the 'code vectors'.
  • the VQ operator Q partitions £ N into L disjoint and exhaustive regions ⁇ ⁇ l f . . . P ⁇ , each of which has a single coarse-grained representation.
  • X may be taken to be a pixel macroblock that is quantised under the operation Q into a finite codebook.
  • The. latter is generated once, and a copy is provided to both the encoder and the decoder. It is then sufficient to merely store or transmit the output of the codebook in order to represent any source vector.
  • the technique operates as a pattern matching algorithm. It is well-known in engineering literature and is an integral part of MPEG's repertoire of routines.
  • a source vector X is mapped by Q into a bucket, and occupies a unique, but arbitary, slot position.
  • Each bucket therefore holds all the source vectors that are sufficiently close to the appropriate code vector which is their quantised representation within the source regions P j ,.
  • Q is usually a dimensionality-reduction operator.
  • the combination of VQ and a hash table loaded in the manner described above provide a way for non-lossy representation of a source frame. This combined structure will be hereinafter referred to as a 'Vector Quantised Hash Table' or VQHT.
  • MPEG In order to support motion compensation, MPEG classifies video frames into three categories as follows.
  • P (redicted) -frames, which exploit motion compensation in order to improve compression.
  • a predicted frame is coded with reference to a preceding I- or P-frame.
  • B idirectional -frames which rely upon both preceding and subsequent frames . Such frames use bidirectional interpolation between I- and P-frames, but are not used for coding other frames. They also have the highest compression efficiency.
  • MPEG specifies two parameters, N and M, which keep a count of the frame distance (i.e. number of frames) between, respectively, two successive I-frames (also-know -as GOP or 'Group of Pictures') and two successive P-frames.
  • N is a function of the number of such cuts in a video.
  • M is not defined by MPEG, and is left to the discretion of the encoder.
  • the generation of P-frames is crucial for efficient coding, but is also the most expensive part of MPEG, since motion estimation is directly involved.
  • the decoding process uses a macroblock and a motion vector to reconstruct a P-frame, based on a closest match search of the preceding frame. Note that the use of the word 'preceding' does not imply frame adjacency, since B-frames typically interleave I- and P-frames.
  • MPEG does not specify how a closest match should be implemented; encoders have the task therefore of minimising the difference between a predicted and an actual macroblock.
  • both forward-predicted and bidirectionally-predicted frames are referred to as P-frames in the following description.
  • the process begins by encoding an I-frame (or a P-frame from which a subsequent P-frame is to be deduced) into a VQHT. As described above, this provides a complete and non-lossy representation of an I-frame. From an implementation perspective, encoding involves a two-stage process:
  • Codebook generation in which a decision is made on the number of bucket entries L in the codebook C. Representative code vectors from the I-frame are computed
  • Hash Table loading in which the VQHT bucket slots are filled up by feeding every possible source vector (macroblock) from the I-frame through the hash function and storing it (together with its co-ordinates) in its appropriate bucket. Bucket slots are filled up sequentially in this manner.
  • a set of motion vectors are required for those macroblocks which will be predicted during the decoding stage.
  • the generation of motion vectors using the VQHT involves the simple act of a hash table lookup.
  • the P- frame macroblock whose motion vector is required is hashed directly into a bucket entry.
  • the corresponding motion vector is then obtained simply by searching all slots for that I-frame macroblock which minimises a distance metric.
  • the co-ordinate difference between the P-frame and I-frame macroblock so found defines the motion vector. This can now be DCT-encoded before being transmitted to the decoder in the usual MPEG manner.
  • VQH The encoder structures required in a hardware implementation of VQH can be partitioned into pre-processing and postprocessing stages.
  • pre-processing all that is required is a vector quantiser (which is normally a part of MPEG anyway) and some local buffer memory which stores the buckets and slots comprising the VQHT. It is possible to construct control logic that will directly fill up the VQHT from the vector quantiser's output when it is given an I-frame to encode. This, however, could also be done in software without incurring a significant performance penalty.
  • a shift register array which takes as its input a linearised macroblock from a P-frame that is to be encoded.
  • the geometry of this array is arranged such that the outputs are simply equal to the inputs, but with each component staggered by one computational cycle from its predecessor;
  • a codebook buffer which contains the code vectors which will be filled in by the hardware vector quantiser
  • a VQHT buffer which contains the representation of the I-frame, and is filled in during the pre-processing stage
  • a systolic sorter the P-frame macroblock that is to be encoded needs to be hashed into its appropriate bucket, and the corresponding I-frame macroblock with the least distance metric needs to be found. For this reason, a systolic sorter is included, the function of which is two-fold. Firstly, it sorts the output metrics from the codebook array in order to find the corresponding bucket . Secondly, it sorts the output metrics from the bucket in order to find those with the least distortion; An array of comparators: the distortions from the sorter array need not be unique, particularly if the macroblock is representing a region of low spatial gradient (i.e. minimum motion) . Thus it is necessary to compare the sorted outputs with each other in order to tag all those which are equal.
  • the comparator performs this task; and A mean absolute differencer: at this stage, there exists a set of bucket entries which have an identical (and minimum) distance metric between the P-frame macroblock to.be encoded and the I-frame. It now remains to find from these entries that unique entry which minimises the co-ordinate metric.
  • the 2-dimensional differencer performs this task. It takes as its input the ⁇ x, y) coordinates of the P-frame macroblock to be encoded as well as the outputs from the comparator array. It then performs a metric computation (an L 2 -norm) between this coordinate and the coordinates of all candidate I-frame macroblocks. The resulting calculation tags the coordinates of the best-matching I-frame macroblock.

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)

Abstract

Procédé de compression de données d'images comprenant les étapes suivantes: générer un ensemble de vecteurs de mouvement représentatifs d'une ou plusieurs trames d'images, générer au moyen d'une fonction de hachage prédéterminée un ensemble de valeurs de hachage, répondre audits vecteurs de mouvement et stocker les valeurs de hachage comme une table de codage sous la forme d'une table ou d'un réseau. On peut utiliser la quantification des vecteurs pour indexer les valeurs de hachage dans la table ou le réseau pour permettre leur récupération par un décodeur.
PCT/GB2002/002236 2001-05-14 2002-05-14 Compression et transmission d'images WO2002093934A1 (fr)

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GB0111627A GB2375673A (en) 2001-05-14 2001-05-14 Image compression method using a table of hash values corresponding to motion vectors

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Cited By (19)

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WO2009143120A2 (fr) * 2008-05-19 2009-11-26 Citrix Systems, Inc. Systèmes et procédés de codage d'image amélioré
WO2015142829A1 (fr) * 2014-03-17 2015-09-24 Qualcomm Incorporated Recherche de codeur à base de hachage pour copie de bloc intra
TWI548266B (zh) * 2014-06-24 2016-09-01 愛爾達科技股份有限公司 多媒體檔案儲存系統與相關裝置
EP3061233A4 (fr) * 2013-10-25 2016-10-12 Microsoft Technology Licensing Llc Représentation de blocs à l'aide de valeurs de hachage dans le codage et le décodage vidéo et d'images
US9786270B2 (en) 2015-07-09 2017-10-10 Google Inc. Generating acoustic models
US9858922B2 (en) 2014-06-23 2018-01-02 Google Inc. Caching speech recognition scores
US10204619B2 (en) 2014-10-22 2019-02-12 Google Llc Speech recognition using associative mapping
US10229672B1 (en) 2015-12-31 2019-03-12 Google Llc Training acoustic models using connectionist temporal classification
US10264290B2 (en) 2013-10-25 2019-04-16 Microsoft Technology Licensing, Llc Hash-based block matching in video and image coding
US10368092B2 (en) 2014-03-04 2019-07-30 Microsoft Technology Licensing, Llc Encoder-side decisions for block flipping and skip mode in intra block copy prediction
US10390039B2 (en) 2016-08-31 2019-08-20 Microsoft Technology Licensing, Llc Motion estimation for screen remoting scenarios
US10403291B2 (en) 2016-07-15 2019-09-03 Google Llc Improving speaker verification across locations, languages, and/or dialects
US10567754B2 (en) 2014-03-04 2020-02-18 Microsoft Technology Licensing, Llc Hash table construction and availability checking for hash-based block matching
US10681372B2 (en) 2014-06-23 2020-06-09 Microsoft Technology Licensing, Llc Encoder decisions based on results of hash-based block matching
US10706840B2 (en) 2017-08-18 2020-07-07 Google Llc Encoder-decoder models for sequence to sequence mapping
EP3613014A4 (fr) * 2017-04-21 2020-07-22 Zenimax Media Inc. Compensation de mouvement d'entrée d'un joueur par anticipation de vecteurs de mouvement
US11025923B2 (en) 2014-09-30 2021-06-01 Microsoft Technology Licensing, Llc Hash-based encoder decisions for video coding
US11095877B2 (en) 2016-11-30 2021-08-17 Microsoft Technology Licensing, Llc Local hash-based motion estimation for screen remoting scenarios
US11202085B1 (en) 2020-06-12 2021-12-14 Microsoft Technology Licensing, Llc Low-cost hash table construction and hash-based block matching for variable-size blocks

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WO2009143120A3 (fr) * 2008-05-19 2010-04-01 Citrix Systems, Inc. Systèmes et procédés de codage d'image amélioré
US8295617B2 (en) 2008-05-19 2012-10-23 Citrix Systems, Inc. Systems and methods for enhanced image encoding
WO2009143120A2 (fr) * 2008-05-19 2009-11-26 Citrix Systems, Inc. Systèmes et procédés de codage d'image amélioré
US10264290B2 (en) 2013-10-25 2019-04-16 Microsoft Technology Licensing, Llc Hash-based block matching in video and image coding
US11076171B2 (en) 2013-10-25 2021-07-27 Microsoft Technology Licensing, Llc Representing blocks with hash values in video and image coding and decoding
EP3061233A4 (fr) * 2013-10-25 2016-10-12 Microsoft Technology Licensing Llc Représentation de blocs à l'aide de valeurs de hachage dans le codage et le décodage vidéo et d'images
US10567754B2 (en) 2014-03-04 2020-02-18 Microsoft Technology Licensing, Llc Hash table construction and availability checking for hash-based block matching
US10368092B2 (en) 2014-03-04 2019-07-30 Microsoft Technology Licensing, Llc Encoder-side decisions for block flipping and skip mode in intra block copy prediction
WO2015142829A1 (fr) * 2014-03-17 2015-09-24 Qualcomm Incorporated Recherche de codeur à base de hachage pour copie de bloc intra
CN106105197A (zh) * 2014-03-17 2016-11-09 高通股份有限公司 针对帧内块复制的基于散列的编码器搜索
US9715559B2 (en) 2014-03-17 2017-07-25 Qualcomm Incorporated Hash-based encoder search for intra block copy
CN106105197B (zh) * 2014-03-17 2019-01-15 高通股份有限公司 针对帧内块复制的基于散列的编码器搜索
US10681372B2 (en) 2014-06-23 2020-06-09 Microsoft Technology Licensing, Llc Encoder decisions based on results of hash-based block matching
US9858922B2 (en) 2014-06-23 2018-01-02 Google Inc. Caching speech recognition scores
TWI548266B (zh) * 2014-06-24 2016-09-01 愛爾達科技股份有限公司 多媒體檔案儲存系統與相關裝置
US11025923B2 (en) 2014-09-30 2021-06-01 Microsoft Technology Licensing, Llc Hash-based encoder decisions for video coding
US10204619B2 (en) 2014-10-22 2019-02-12 Google Llc Speech recognition using associative mapping
US9786270B2 (en) 2015-07-09 2017-10-10 Google Inc. Generating acoustic models
US11341958B2 (en) 2015-12-31 2022-05-24 Google Llc Training acoustic models using connectionist temporal classification
US10229672B1 (en) 2015-12-31 2019-03-12 Google Llc Training acoustic models using connectionist temporal classification
US11769493B2 (en) 2015-12-31 2023-09-26 Google Llc Training acoustic models using connectionist temporal classification
US10803855B1 (en) 2015-12-31 2020-10-13 Google Llc Training acoustic models using connectionist temporal classification
US11594230B2 (en) 2016-07-15 2023-02-28 Google Llc Speaker verification
US11017784B2 (en) 2016-07-15 2021-05-25 Google Llc Speaker verification across locations, languages, and/or dialects
US10403291B2 (en) 2016-07-15 2019-09-03 Google Llc Improving speaker verification across locations, languages, and/or dialects
US10390039B2 (en) 2016-08-31 2019-08-20 Microsoft Technology Licensing, Llc Motion estimation for screen remoting scenarios
US11095877B2 (en) 2016-11-30 2021-08-17 Microsoft Technology Licensing, Llc Local hash-based motion estimation for screen remoting scenarios
EP3723370A1 (fr) * 2017-04-21 2020-10-14 Zenimax Media Inc. Compensation de mouvement d'entrée de lecteur par anticipation de vecteurs de mouvement
US11323740B2 (en) 2017-04-21 2022-05-03 Zenimax Media Inc. Systems and methods for player input motion compensation by anticipating motion vectors and/or caching repetitive motion vectors
US11330291B2 (en) 2017-04-21 2022-05-10 Zenimax Media Inc. Systems and methods for player input motion compensation by anticipating motion vectors and/or caching repetitive motion vectors
EP3723045A1 (fr) * 2017-04-21 2020-10-14 Zenimax Media Inc. Compensation de mouvement d'entrée d'un joueur par anticipation de vecteurs de mouvement
US11503332B2 (en) 2017-04-21 2022-11-15 Zenimax Media Inc. Systems and methods for player input motion compensation by anticipating motion vectors and/or caching repetitive motion vectors
US11533504B2 (en) 2017-04-21 2022-12-20 Zenimax Media Inc. Systems and methods for player input motion compensation by anticipating motion vectors and/or caching repetitive motion vectors
US11601670B2 (en) 2017-04-21 2023-03-07 Zenimax Media Inc. Systems and methods for player input motion compensation by anticipating motion vectors and/or caching repetitive motion vectors
US11695951B2 (en) 2017-04-21 2023-07-04 Zenimax Media Inc. Systems and methods for player input motion compensation by anticipating motion vectors and/or caching repetitive motion vectors
EP3613014A4 (fr) * 2017-04-21 2020-07-22 Zenimax Media Inc. Compensation de mouvement d'entrée d'un joueur par anticipation de vecteurs de mouvement
US10706840B2 (en) 2017-08-18 2020-07-07 Google Llc Encoder-decoder models for sequence to sequence mapping
US11776531B2 (en) 2017-08-18 2023-10-03 Google Llc Encoder-decoder models for sequence to sequence mapping
US11202085B1 (en) 2020-06-12 2021-12-14 Microsoft Technology Licensing, Llc Low-cost hash table construction and hash-based block matching for variable-size blocks

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