US20060285590A1 - Nonlinear, prediction filter for hybrid video compression - Google Patents

Nonlinear, prediction filter for hybrid video compression Download PDF

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US20060285590A1
US20060285590A1 US11/471,741 US47174106A US2006285590A1 US 20060285590 A1 US20060285590 A1 US 20060285590A1 US 47174106 A US47174106 A US 47174106A US 2006285590 A1 US2006285590 A1 US 2006285590A1
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transform coefficients
transform
prediction
motion compensated
linear
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Onur Guleryuz
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NTT Docomo Inc
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Docomo Communications Labs USA Inc
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Assigned to DOCOMO COMMUNICATIONS LABORATORIES USA, INC. reassignment DOCOMO COMMUNICATIONS LABORATORIES USA, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: GULERYUZ, ONUR G.
Priority to PCT/US2006/024270 priority patent/WO2007002265A2/en
Priority to JP2008518377A priority patent/JP5259396B2/ja
Assigned to NTT DOCOMO, INC. reassignment NTT DOCOMO, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: DOCOMO COMMUNICATIONS LABORATORIES USA, INC.
Publication of US20060285590A1 publication Critical patent/US20060285590A1/en
Priority to US13/153,292 priority patent/US20110293005A1/en
Priority to US13/153,294 priority patent/US8625682B2/en
Priority to US13/153,299 priority patent/US20110235718A1/en
Priority to US13/153,296 priority patent/US20110235717A1/en
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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
    • H04N19/523—Motion estimation or motion compensation with sub-pixel accuracy
    • 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
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/103—Selection of coding mode or of prediction mode
    • H04N19/105—Selection of the reference unit for prediction within a chosen coding or prediction mode, e.g. adaptive choice of position and number of pixels used for prediction
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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    • 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
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/117—Filters, e.g. for pre-processing or post-processing
    • H—ELECTRICITY
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    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
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    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/172—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
    • 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
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
    • H—ELECTRICITY
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    • 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
    • H04N19/192—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 the adaptation method, adaptation tool or adaptation type being iterative or recursive
    • 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
    • H04N19/46—Embedding additional information in the video signal during the compression process
    • 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
    • H04N19/48—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using compressed domain processing techniques other than decoding, e.g. modification of transform coefficients, variable length coding [VLC] data or run-length data
    • 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
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/61—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding in combination with predictive coding
    • H04N19/615—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding in combination with predictive coding using motion compensated temporal filtering [MCTF]

Definitions

  • the present invention relates to the field of compression and decompression; more particularly, the present invention relates to non-linear prediction filtering in video compression and decompression processing.
  • Hybrid video compression consists of encoding an anchor video frame and then predicatively encoding a set of predicted frames. Predictive encoding uses motion compensated prediction with respect to previously coded frames in order to obtain a prediction error frame followed by the encoding of this prediction error frame (i.e., the residual frame). Anchor frames and prediction errors are encoded using transform coders.
  • FIG. 1 is a block diagram of a video encoder.
  • a motion compensated (MC) prediction module generates a motion compensated prediction from a previously decoded frame.
  • a first adder subtracts the motion compensated prediction from a current frame to obtain a residual frame.
  • a transform coder converts a residual frame to a coded differential, for example by using a combination of a transform, a quantizer, and an entropy encoder.
  • a transform decoder converts the coded differential to a reconstructed residual frame, for example by using a combination of an entropy decoder, an inverse quantizer, and an inverse transform.
  • a second adder adds the reconstructed residual frame to the motion compensated prediction to obtain a reconstructed frame.
  • a delay element “Z ⁇ 1 ” stores the reconstructed frame for future reference by the MC prediction module.
  • the generic motion compensated prediction operation is limited to forming predictors for the current frame by using blocks from previously coded frames directly, or by using low-pass filter based interpolations of these blocks. This process forms a good mechanism for exploiting temporal correlations.
  • the method comprises performing motion compensation to generate a motion compensated prediction using a block from a previously coded frame, performing non-linear filtering on the motion compensated prediction in the transform domain with a non-linear filter as part of a fractional interpolation process to generate a motion compensated non-linear prediction, subtracting the motion compensated non-linear prediction from a block in a current frame to produce a residual frame, and coding the residual frame.
  • FIG. 1 is a block diagram of a video encoder.
  • FIGS. 2A and 2B is a block diagram of an enhanced video encoder.
  • FIG. 3 is a flow diagram of a traditional motion compensated prediction formation process.
  • FIG. 4 is a flow diagram of one embodiment of a process for performing nonlinear prediction formation.
  • FIG. 5 is a flow diagram of one embodiment for nonlinear prediction process.
  • FIG. 6 is a flow diagram of one embodiment of a nonlinear prediction process.
  • FIG. 7 is a flow diagram of one embodiment of a nonlinear prediction formation process.
  • FIG. 8 is a block diagram of an exemplary computer system that may perform ore of the operations described herein.
  • a method, apparatus and article of manufacture for nonlinear filtering of video frames that enables better hybrid video compression performance are described.
  • the techniques described herein augment the motion compensated prediction process by supplying nonlinear filtering options beyond the well-known low-pass filter based interpolators.
  • a traditional hybrid encoder will choose one of a set of fractional interpolators implemented using low-pass filters.
  • Additional prediction modifiers take the same blocks from the previously coded frames and apply different nonlinear filters to form better predictors of the current frame.
  • nonlinear filtering options implemented in transform domain to this set.
  • these nonlinear prediction options are generated by utilizing transform coefficient thresholding, coefficient magnitude based ranking, and their combinations to derive nonlinear filtered predictions in spatial domain.
  • Nonlinear filtering options are efficiently captured in parameters that are sent to the decoder as part of the coded bit stream.
  • the described techniques are robust and general, being able to effectively handle a multitude of image region types and a multitude of compression techniques.
  • the derived nonlinear prediction filters adaptively and autonomously develop the proper frequency selectivity for the multitude of image region types by developing low-pass selectivity in smooth image regions, high-pass selectivity in high-frequency regions, etc.
  • the present invention also relates to apparatus for performing the operations herein.
  • This apparatus may be specially constructed for the required purposes, or it may comprise a general purpose computer selectively activated or reconfigured by a computer program stored in the computer.
  • a computer program may be stored in a computer readable storage medium, such as, but is not limited to, any type of disk including floppy disks, optical disks, CD-ROMs, and magnetic-optical disks, read-only memories (ROMs), random access memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, or any type of media suitable for storing electronic instructions, and each coupled to a computer system bus.
  • a machine-readable medium includes any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer).
  • a machine-readable medium includes read only memory (“ROM”); random access memory (“RAM”); magnetic disk storage media; optical storage media; flash memory devices; electrical, optical, acoustical or other form of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.); etc.
  • a candidate block from the previously coded frames is obtained.
  • this candidate block can be of larger size than the block to be predicted.
  • a candidate block of a size larger than the predicted block is reduced to the same size as the predicted block at the end of the filtering operation.
  • the candidate block is first transformed using a linear transform to obtain its transform coefficients.
  • An overcomplete set of linear transforms can also be used to generate transform coefficients.
  • Candidate block transform coefficients are non-linearly modified in P different ways to produce P sets of coefficients that correspond to P different blocks. Each such set of coefficients is inverse transformed and then possibly reduced in size to obtain P prediction blocks for the block to be predicted.
  • each of these P prediction blocks is compared to the block to be predicted. The best prediction is chosen and a corresponding prediction parameter is determined.
  • the encoder then considers standard prediction options in addition to this non-linear prediction and signals the decoder as to which to use. Based on this signal, the decoder replicates the prediction process and obtains the same prediction block as the encoder.
  • the non-linear modifications of candidate block coefficients take the form of thresholding the coefficients, sorting the coefficients based on magnitude and only retaining the largest R percent, indexing the coefficients and only retaining those having the prescribed indices (or those belonging to a given index set), and scaling the coefficients.
  • Various combinations of these operations, while including at least one nonlinear operation, can be applied.
  • a parameter is determined that is sent to the decoder as to which operation has been performed in the case that the encoder decides to use the nonlinear prediction. This parameter can take P different values, i.e., there are P different combined operations that can be done on a candidate block.
  • the techniques described herein include a parameter overhead control operation in the form of a prediction scanning and elimination operation is incorporated to determine which of the P operations produce significant differences in the candidate block.
  • a parameter overhead control operation in the form of a prediction scanning and elimination operation is incorporated to determine which of the P operations produce significant differences in the candidate block.
  • the decision to use non-linear prediction is made at a block level, where the size of the block is determined by the transform used in the transform coding operation of the hybrid video coder.
  • the linear transform applied to the candidate blocks as discussed above is an orthonormal transform, such as, for example, a block nxn DCT.
  • Other transforms such as, for example, non-orthogonal transforms and non-block transforms can also be applied. It is desirable but not necessary for this transform to have a fast implementation so that computations can be carried out in an efficient manner.
  • x (arranged into an Mx 1 vector) denote the block to be predicted.
  • y (arranged into an Nx 1 vector) denote a candidate block from the frame used in predicting x.
  • the candidate block y can be of size larger than x so that various filtering and interpolation opeartions are well defined.
  • this set is augmented by defining a further set of predictions ⁇ circumflex over (x) ⁇ F+1 , ⁇ circumflex over (x) ⁇ F+2 , ⁇ circumflex over (x) ⁇ F+Q based on nonlinear filtering as follows.
  • T 1 , T 2 , . . . , T K denote a set of thresholds and let R 1 , R 2 , . . . , R L denote a set of percentages.
  • Nonlinear prediction ⁇ circumflex over (x) ⁇ F+j , j 1, . . .
  • the predictions are generated iteratively by adding correction terms to the generated predictions, and reapplying the above operations to the corrected predictions, and so on until a specific number of iterations is carried out.
  • the parameters can be changed in each iteration in a prescribed way.
  • a scanning and elimination operation is used.
  • One such operation is as follows. Each generated prediction is compared to applying the identity predictor to y, i.e., the predictor obtained by not modifying y in any way except for a possible size reduction, to the predictions ⁇ circumflex over (x) ⁇ 1 , ⁇ circumflex over (x) ⁇ 2 , . . . , ⁇ circumflex over (x) ⁇ F , and to predictions that were found to be valid up to that point. If the generated prediction is sufficiently different from these predictions, then it becomes a valid prediction; otherwise, it is deleted from the set of predictors. The remaining Q predictions form as set ⁇ circumflex over (x) ⁇ F+1 , ⁇ circumflex over (x) ⁇ F+2 , . . . , ⁇ circumflex over (x) ⁇ F+Q .
  • the decoder needs to be notified which of F+Q predictions it should construct rather than just the F predictions in the traditional case.
  • the decoder can implement the scanning and elimination operation in parallel and determine the Q additional predictors.
  • Some parameters such as, for example, the values of the thresholds, percentages, and scaling coefficients can also be signaled to the decoder. Such signaling can be done in a manner well-known in the art.
  • each of these transforms is used in a filtering procedure of its own to produce prediction estimates ⁇ circumflex over (x) ⁇ F+j , ⁇ circumflex over (x) ⁇ F+j , ⁇ circumflex over (x) ⁇ F+j,U . These individual prediction estimates are then combined to form an overall prediction ⁇ circumflex over (x) ⁇ F+j that is better than each of the prediction estimates.
  • a video encoder comprises a motion compensation prediction module to perform motion compensation to generate a motion compensated prediction using a block from a previously coded frame, a non-linear prediction filter to perform non-linear filtering on the block in the transform domain with a non-linear filter as part of a fractional interpolation process, an adder (subtractor) to subtract the motion compensated non-linear prediction from a block in a current frame to produce a residual frame, and a coder to code the residual frame.
  • a motion compensation prediction module to perform motion compensation to generate a motion compensated prediction using a block from a previously coded frame
  • a non-linear prediction filter to perform non-linear filtering on the block in the transform domain with a non-linear filter as part of a fractional interpolation process
  • an adder subtractor
  • FIG. 2A is a block diagram of an enhanced video encoder.
  • a motion compensated (MC) prediction module 216 generates a motion compensated prediction from a previously decoded frame 203 .
  • a non-linear prediction filter 217 that augments the motion compensated prediction as described herein to produce better predictions of the frame to be coded.
  • Adder 211 subtracts the augmented motion compensated prediction from a current frame 201 to obtain a residual frame.
  • a transform coder 212 converts a residual frame to a coded differential 202 by, for example, using a combination of a transform, a quantizer, and an entropy encoder.
  • a transform decoder 213 converts the coded differential to a reconstructed residual frame by, for example, using a combination of an entropy decoder, an inverse quantizer, and an inverse transform.
  • Adder 214 adds the reconstructed residual frame to the augmented motion compensated prediction to obtain a reconstructed frame.
  • a delay element “Z ⁇ 1 ” 215 stores the reconstructed frame for future reference by MC prediction module 216 .
  • a video decoder comprises a motion compensation unit to generate a predicted block using a block from a previously decoded frame, a non-linear prediction filter to perform non-linear filtering on the predicted block in the transform domain with a non-linear prediction filter as part of a fractional interpolation process to generate a non-linear prediction, a decoder to decode a residual frame, and an adder to add the residual frame to the non-linear prediction
  • FIG. 2B is a block diagram of an enhanced video decoder.
  • a MC prediction module 224 generates a motion compensated prediction from a previously decoded frame 233 .
  • a non-linear prediction filter 223 augments the motion compensated prediction to produce better predictions of the frame to be decoded. This is done in response to prediction parameters 232 received from the coded bitstream.
  • a transform decoder 221 converts the coded differential 231 to a reconstructed residual frame by, for example, using a combination of an entropy decoder, an inverse quantizer, and an inverse transform.
  • Adder 222 adds the reconstructed residual frame to the augmented motion compensated prediction to obtain a reconstructed frame that is output from the video decoder. The output may be sent to a display.
  • a delay element “Z ⁇ 1 ” 225 also stores the filtered frame for future reference by MC prediction module 224 .
  • the non-linear prediction filter comprises a forward transform module to apply a transform to the motion compensated prediction to obtain a first set of transform coefficients, a module to perform a non-linear filtering operation in the transform domain to obtain a second set of transform coefficients from the first set, and an inverse transform module to apply an inverse transform to the second set of transform coefficients to generate the motion compensated non-linear prediction.
  • the module to perform a non-linear filtering operation in the transform domain comprises a module to perform thresholding on each transform coefficient based on a threshold to identify a set of one or more transform coefficients to change and to modify the first set of transform coefficients to create a second set of transform coefficients by changing transform coefficients in the set of one or more transform coefficients.
  • the module to perform a non-linear filtering operation in the transform domain comprises a module to sort transform coefficients based on magnitude to identify transform coefficients to change and to modify those transform coefficients to create a second set of transform coefficients.
  • the module to perform a non-linear filtering operation in the transform domain comprises a module to perform percentage filtering on each transform coefficient of the block to identify a set of one or more transform coefficients to change and to modify those transform coefficients to create the second set of transform coefficients.
  • the module to perform a non-linear filtering operation in the transform domain comprises a module to assign an index to each transform coefficient in the block, identify a set of one or more transform coefficients to change based on the indices, and modify the first set of transform coefficients to create the second set of transform coefficients by changing transform coefficients in the set of one or more transform coefficients.
  • the module to perform a non-linear filtering operation in the transform domain comprises a module to scale one or more transform coefficients to create the second set of transform coefficients.
  • the linear transforms are given by a nxn block DCT and all of its n 2 spatial translations, and n is determined by the size of the video frame.
  • n is determined by the size of the video frame.
  • n is expected to get larger for higher resolution video frames.
  • FIG. 3 is a flow diagram of a traditional motion compensated prediction formation process.
  • the process includes obtaining a candidate block y from the previously decoded framed (processing block 301 ).
  • the interpolation predictions ⁇ circumflex over (x) ⁇ l . . . ⁇ circumflex over (x) ⁇ F are output (processing block 303 ). Thereafter, that process ends.
  • FIG. 4 is a flow diagram of one embodiment of a process for performing nonlinear prediction formation.
  • the process is performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both.
  • the process is performed by a nonlinear prediction filter.
  • the process begins by obtaining a candidate block y from the previously decoded frames (processing block 401 ) and obtaining F traditional motion compensated predictors ⁇ circumflex over (x) ⁇ l . . . ⁇ circumflex over (x) ⁇ F (processing block 402 ).
  • processing logic obtains an identity predictor (processing block 403 ), which is stored along with the traditional motion compensated predictors ⁇ circumflex over (x) ⁇ l . . . ⁇ circumflex over (x) ⁇ F in prediction dictionary storage 409 .
  • processing logic constructs K thresholding predictions ⁇ circumflex over (x) ⁇ F+i (processing block 404 ) and constructs L percentage predictions ⁇ circumflex over (x) ⁇ F+K+l (processing block 405 ).
  • Processing logic constructs the thresholding predictions using parameters thresholds T l , . . . , T K and transforms H l , . . . , H U ( 408 ).
  • processing logic constructs L percentage predictions using percentages R l , . . . , R L and transforms H l , . . . , H U ( 406 ).
  • thresholding is implemented by hard-thresholding each transform coefficient of y. If transform coefficient has magnitude greater than the threshold, it is unchanged; otherwise it is set to zero.
  • K and thresholds T 1 , T 2 , . . . , T K are determined by the encoder for every frame to be encoded and signaled to the decoder.
  • L and percentages R 1 , R 2 , . . . , R L are determined by the encoder for every frame to be encoded and signaled to the decoder.
  • processing logic compares each constructed prediction to the predictions stored in prediction dictionary storage 409 . More specifically, in one embodiment, processing logic tests whether the differences are less than threshold T Q .
  • T Q can be an increasing function of the quantizer step-size. If not, the prediction is invalid and it is discarded. If the prediction is sufficiently different from all the dictionary elements, based on its comparison to threshold T Q , then processing logic declares it valid and adds it to the dictionary to be used in further comparisons.
  • processing logic outputs non-linear predictions ⁇ circumflex over (x) ⁇ F+1 , ⁇ circumflex over (x) ⁇ F+2 , . . . , ⁇ circumflex over (x) ⁇ F+Q (processing block 410 ) and the process ends.
  • nonlinear predictors are compared to the identity predictor, to ⁇ circumflex over (x) ⁇ 1 , ⁇ circumflex over (x) ⁇ 2 , . . . , ⁇ circumflex over (x) ⁇ F and to predictions that were found to be valid up to that point as follows.
  • a dictionary is constructed using the identity predictor, ⁇ circumflex over (x) ⁇ 1 , ⁇ circumflex over (x) ⁇ 2 , . . . , ⁇ circumflex over (x) ⁇ F .
  • Each prediction is compared with each element of the dictionary by calculating the squared error between the prediction and the dictionary element. This squared error is then compared to a threshold T Q .
  • threshold T Q is determined as a multiple of the quantizer step size squared; other equivalent parameters may be used.
  • FIG. 5 is a flow diagram of one embodiment for nonlinear prediction process.
  • the process is performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both.
  • the nonlinear prediction processing is performed inside the encoding loop.
  • processing begins by processing logic performing traditional motion compensated prediction formation (processing block 501 ) and nonlinear formation (processing block 502 ) to generate predictions for the frame to be encoded in response to decompressed video frames 510 .
  • processing logic performs the nonlinear prediction formation using transforms H l , . . . , H U , thresholds T l , . . . , T K and percentages R l , . . . , R L
  • processing logic chooses the best prediction (processing block 503 ). This is done in response to the frames to be predicted ( 512 ). Then processing logic notifies the decoder the chosen prediction 514 and prediction parameters, thresholds T l , . . . , T K and percentages R l , . . . , R L ( 513 ). Thereafter, the process ends.
  • FIG. 6 is a flow diagram of one embodiment of a nonlinear prediction process.
  • the process is performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both.
  • the nonlinear prediction process is performed in a coding loop of a video decoder.
  • the process begins by processing logic determining a filter for each block to be predicted (processing block 601 ). In one embodiment, this determination is performed in response to decompressed video frame 610 and prediction parameters 611 included in the bitstream by the encoder.
  • processing logic After determining the filter, processing logic performs traditional motion compensation prediction formation (processing block 602 ).
  • the traditional motion compensation prediction formation is performed on the blocks requiring traditional prediction 612 .
  • Processing logic also performs nonlinear prediction formation (processing block 603 ). In such a case, the nonlinear prediction formation is performed on blocks requiring nonlinear prediction 613 and transforms H l , . . . , H U , prediction parameters, thresholds T l , . . . , T K and percentages R l , . . . , R L ( 614 ).
  • prediction 615 is the appropriate prediction for each block in the frame to be decoded.
  • FIG. 7 is a flow diagram of one embodiment of a nonlinear prediction formation process.
  • the process is performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both.
  • the process as described generates nonlinear predictions on candidate block y using an overcomplete transform.
  • the present invention is not limited to using overcomplete transforms; other transforms may be used.
  • the process begins by applying a forward transform to a candidate block to generate a first set of transform coefficients d i , applying thresholding (or another filtering technique such as, for example, percentage filtering) to modify one or more of the coefficients in the set of coefficients d i , and then applying an inverse transform to the transform coefficients of d i to generate the prediction (processing block 701 ).
  • this operation is performed for all blocks in a frame and is done in response to transforms H l , . . . , H U , threshold T K and percentage R K .
  • threshold T K is 2, 3.5, 7.2, or some number ⁇ times the quantizer step-size, i.e., ⁇ , where ⁇ could be 0.2, 1, 3.45, 23, etc.
  • the result is a non-linear prediction estimate. This is performed U times, such that U prediction estimates are formed.
  • U can be n 2
  • U can be set so that the U transforms provide a translation invariant decomposition, or U can be set based on computational complexity constraints.
  • processing logic After performing the filtering operation, processing logic combines the prediction estimates to produce an overall nonlinear prediction ⁇ circumflex over (x) ⁇ K (processing block 702 ).
  • the combination is given by weighted averaging of the individual predictions ⁇ circumflex over (x) ⁇ F+j.1 , ⁇ circumflex over (x) ⁇ F+j.2 , . . . , ⁇ circumflex over (x) ⁇ F+j.U . This can be done with equal weights or using more sophisticated weight determination techniques known in the art, such as those described in, for example, Onur G. Guleryuz, “Weighted Overcomplete Denoising,” Proc. Asilomar Conference on Signals and Systems, Pacific Grove, Calif., November 2003.
  • FIG. 8 is a block diagram of an exemplary computer system that may perform one or more of the operations described herein.
  • computer system 800 may comprise an exemplary client or server computer system.
  • Computer system 800 comprises a communication mechanism or bus 811 for communicating information, and a processor 812 coupled with bus 811 for processing information.
  • Processor 812 includes a microprocessor, but is not limited to a microprocessor, such as, for example, PentiumTM, PowerPCTM, AlphaTM, etc.
  • System 800 further comprises a random access memory (RAM), or other dynamic storage device 804 (referred to as main memory) coupled to bus 811 for storing information and instructions to be executed by processor 812 .
  • main memory 804 also may be used for storing temporary variables or other intermediate information during execution of instructions by processor 812 .
  • Computer system 800 also comprises a read only memory (ROM) and/or other static storage device 806 coupled to bus 811 for storing static information and instructions for processor 812 , and a data storage device 807 , such as a magnetic disk or optical disk and its corresponding disk drive.
  • ROM read only memory
  • Data storage device 807 is coupled to bus 811 for storing information and instructions.
  • Computer system 800 may further be coupled to a display device 821 , such as a cathode ray tube (CRT) or liquid crystal display (LCD), coupled to bus 811 for displaying information to a computer user.
  • a display device 821 such as a cathode ray tube (CRT) or liquid crystal display (LCD)
  • An alphanumeric input device 822 may also be coupled to bus 811 for communicating information and command selections to processor 812 .
  • An additional user input device is cursor control 823 , such as a mouse, trackball, trackpad, stylus, or cursor direction keys, coupled to bus 811 for communicating direction information and command selections to processor 812 , and for controlling cursor movement on display 821 .
  • bus 811 Another device that may be coupled to bus 811 is hard copy device 824 , which may be used for marking information on a medium such as paper, film, or similar types of media.
  • hard copy device 824 Another device that may be coupled to bus 811 is a wired/wireless communication capability 825 to communication to a phone or handheld palm device.
  • system 800 any or all of the components of system 800 and associated hardware may be used in the present invention. However, it can be appreciated that other configurations of the computer system may include some or all of the devices.

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