Patent Publication Number: US-11653028-B2

Title: JVET coding block structure with asymmetrical Partitioning

Description:
CLAIM OF PRIORITY 
     This application claims priority to U.S. patent application Ser. No. 15/605,150 filed May 25, 2017 which claims the benefit of U.S. Provisional Application Ser. No. 62/341,325 filed May 25, 2016, all of which is hereby incorporated by reference. 
    
    
     TECHNICAL FIELD 
     The present disclosure relates to the field of video coding, particularly a block partitioning scheme for JVET that allows quadtree partitioning, symmetric binary partitioning, and asymmetric binary partitioning in a quadtree plus binary tree (QTBT) structure. 
     BACKGROUND 
     The technical improvements in evolving video coding standards illustrate the trend of increasing coding efficiency to enable higher bit-rates, higher resolutions, and better video quality. The Joint Video Exploration Team is developing a new video coding scheme referred to as JVET. Similar to other video coding schemes like HEVC (High Efficiency Video Coding), JVET is a block-based hybrid spatial and temporal predictive coding scheme. However, relative to HEVC, JVET includes many modifications to bitstream structure, syntax, constraints, and mapping for the generation of decoded pictures. JVET has been implemented in Joint Exploration Model (JEM) encoders and decoders. 
     SUMMARY 
     The present disclosure provides a method of partitioning a video coding block for JVET, the method comprising representing a JVET coding tree unit as a root node in a quadtree plus binary tree (QTBT) structure that can have a quadtree branching from the root node and binary trees branching from each of the quadtree&#39;s leaf nodes using asymmetric binary partitioning to split a coding unit represented by a quadtree leaf node into two child coding units of unequal size, representing the two child coding units as leaf nodes in a binary tree branching from the quadtree leaf node and coding the child coding units represented by leaf nodes of the binary tree with JVET, wherein further partitioning of child coding units split from quadtree leaf nodes via asymmetric binary partitioning is disallowed. 
     The present disclosure also provides a method of partitioning a video coding block for JVET, the method comprising representing a JVET coding tree unit as a root node in a quadtree plus binary tree (QTBT) structure that can have a quadtree branching from the root node and binary trees branching from each of the quadtree&#39;s leaf nodes, splitting a square block represented by a quadtree node with quadtree partitioning into four square blocks of equal size and representing them as quadtree nodes that can represent final coding units or be split again with quadtree partitioning, symmetric binary partitioning, or asymmetric binary partitioning, with symmetric binary partitioning into two blocks of equal size and representing them in a binary tree branching from the quadtree node as child nodes that can represent final coding units or be recursively split again with symmetric binary partitioning, or with asymmetric binary partitioning into two blocks of unequal size and representing them in a binary tree branching from the quadtree node as leaf nodes that represents final coding units and for which further splitting is disallowed, and coding the coding units represented by leaf nodes of the QTBT structure with JVET. 
     The present disclosure also provides a method of decoding a JVET bitstream, the method comprising receiving a bitstream indicating how a coding tree unit was partitioned into coding units according to a quadtree plus binary tree (QTBT) structure that allows quadtree nodes to be split with quadtree partitioning, symmetric binary partitioning, or asymmetric binary partitioning, identifying coding units represented by leaf nodes of the QTBT structure, wherein an indication that a node was split from a quadtree leaf node using asymmetric binary partitioning directly indicates that the node represents a final coding unit to be decoded, and decoding the identified coding units using JVET. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Further details of the present invention are explained with the help of the attached drawings in which: 
         FIG.  1    depicts division of a frame into a plurality of Coding Tree Units (CTUs). 
         FIG.  2    depicts an exemplary partitioning of a CTU into Coding Units (CUs) using quadtree partitioning and symmetric binary partitioning. 
         FIG.  3    depicts a quadtree plus binary tree (QTBT) representation of  FIG.  2   &#39;s partitioning. 
         FIG.  4    depicts four possible types of asymmetric binary partitioning of a CU into two smaller CUs. 
         FIG.  5    depicts an exemplary partitioning of a CTU into CUs using quadtree partitioning, symmetric binary partitioning, and asymmetric binary partitioning. 
         FIG.  6    depicts a QTBT representation of  FIG.  5   &#39;s partitioning. 
         FIG.  7    depicts a simplified block diagram for CU coding in a JVET encoder. 
         FIG.  8    depicts 67 possible intra prediction modes for luma components in JVET. 
         FIG.  9    depicts a simplified block diagram for CU coding in a JVET encoder. 
         FIG.  10    depicts an embodiment of a method of CU coding in a JVET encoder. 
         FIG.  11    depicts a simplified block diagram for CU coding in a JVET encoder. 
         FIG.  12    depicts a simplified block diagram for CU decoding in a JVET decoder. 
         FIG.  13    depicts an embodiment of a computer system adapted and/or configured to process a method of CU coding. 
         FIG.  14    depicts an embodiment of a coder/decoder system for CU coding/decoding in a JVET encoder/decoder. 
     
    
    
     DETAILED DESCRIPTION 
       FIG.  1    depicts division of a frame into a plurality of Coding Tree Units (CTUs)  100 . A frame can be an image in a video sequence. A frame can include a matrix, or set of matrices, with pixel values representing intensity measures in the image. Thus, a set of these matrices can generate a video sequence. Pixel values can be defined to represent color and brightness in full color video coding, where pixels are divided into three channels. For example, in a YCbCr color space pixels can have a luma value, Y, that represents gray level intensity in the image, and two chrominance values, Cb and Cr, that represent the extent to which color differs from gray to blue and red. In other embodiments, pixel values can be represented with values in different color spaces or models. The resolution of the video can determine the number of pixels in a frame. A higher resolution can mean more pixels and a better definition of the image, but can also lead to higher bandwidth, storage, and transmission requirements. 
     Frames of a video sequence can be encoded and decoded using JVET. JVET is a video coding scheme being developed by the Joint Video Exploration Team. Versions of JVET have been implemented in JEM (Joint Exploration Model) encoders and decoders. Similar to other video coding schemes like HEVC (High Efficiency Video Coding), JVET is a block-based hybrid spatial and temporal predictive coding scheme. During coding with JVET, a frame is first divided into square blocks called CTUs  100 , as shown in  FIG.  1   . For example, CTUs  100  can be blocks of 128×128 pixels. 
       FIG.  2    depicts an exemplary partitioning of a CTU  100  into CUs  102 . Each CTU  100  in a frame can be partitioned into one or more CUs (Coding Units)  102 . CUs  102  can be used for prediction and transform as described below. Unlike HEVC, in JVET the CUs  102  can be rectangular or square, and can be coded without further partitioning into prediction units or transform units. The CUs  102  can be as large as their root CTUs  100 , or be smaller subdivisions of a root CTU  100  as small as 4×4 blocks. 
     In JVET, a CTU  100  can be partitioned into CUs  102  according to a quadtree plus binary tree (QTBT) scheme in which the CTU  100  can be recursively split into square blocks according to a quadtree, and those square blocks can then be recursively split horizontally or vertically according to binary trees. Parameters can be set to control splitting according to the QTBT, such as the CTU size, the minimum sizes for the quadtree and binary tree leaf nodes, the maximum size for the binary tree root node, and the maximum depth for the binary trees. 
     In some embodiments JVET can limit binary partitioning in the binary tree portion of a QTBT to symmetric partitioning, in which blocks can be divided in half either vertically or horizontally along a midline. 
     By way of a non-limiting example,  FIG.  2    shows a CTU  100  partitioned into CUs  102 , with solid lines indicating quadtree splitting and dashed lines indicating symmetric binary tree splitting. As illustrated, the binary splitting allows symmetric horizontal splitting and vertical splitting to define the structure of the CTU and its subdivision into CUs. 
       FIG.  3    shows a QTBT representation of  FIG.  2   &#39;s partitioning. A quadtree root node represents the CTU  100 , with each child node in the quadtree portion representing one of four square blocks split from a parent square block. The square blocks represented by the quadtree leaf nodes can then be divided symmetrically zero or more times using binary trees, with the quadtree leaf nodes being root nodes of the binary trees. At each level of the binary tree portion, a block can be divided symmetrically, either vertically or horizontally. A flag set to “0” indicates that the block is symmetrically split horizontally, while a flag set to “1” indicates that the block is symmetrically split vertically. 
     In other embodiments JVET can allow either symmetric binary partitioning or asymmetric binary partitioning in the binary tree portion of a QTBT. Asymmetrical motion partitioning (AMP) was allowed in a different context in HEVC when partitioning prediction units (PUs). However, for partitioning CUs  102  in JVET according to a QTBT structure, asymmetric binary partitioning can lead to improved partitioning relative to symmetric binary partitioning when correlated areas of a CU  102  are not positioned on either side of a midline running through the center of the CU  102 . By way of a non-limiting example, when a CU  102  depicts one object proximate to the CU&#39;s center and another object at the side of the CU  102 , the CU  102  can be asymmetrically partitioned to put each object in separate smaller CUs  102  of different sizes. 
       FIG.  4    depicts four possible types of asymmetric binary partitioning in which a CU  102  is split into two smaller CU  102  along a line running across the length or height of the CU  102 , such that one of the smaller CUs  102  is 25% of the size of the parent CU  102  and the other is 75% of the size of the parent CU  102 . The four types of asymmetric binary partitioning shown in  FIG.  4    allow a CU  102  to be split along a line 25% of the way from the left side of the CU  102 , 25% of the way from the right side of the CU  102 , 25% of the way from the top of the CU  102 , or 25% of the way from the bottom of the CU  102 . In alternate embodiments an asymmetric partitioning line at which a CU  102  is split can be positioned at any other position such the CU  102  is not divided symmetrically in half. 
       FIG.  5    depicts a non-limiting example of a CTU  100  partitioned into CUs  102  using a scheme that allows both symmetric binary partitioning and asymmetric binary partitioning in the binary tree portion of a QTBT. In  FIG.  5   , dashed lines show asymmetric binary partitioning lines, in which a parent CU  102  was split using one of the partitioning types shown in  FIG.  4   . 
       FIG.  6    shows a QTBT representation of  FIG.  5   &#39;s partitioning. In  FIG.  6   , two solid lines extending from a node indicates symmetric partitioning in the binary tree portion of a QTBT, while two dashed lines extending from a node indicates asymmetric partitioning in the binary tree portion. 
     Syntax can be coded in the bitstream that indicates how a CTU  100  was partitioned into CUs  102 . By way of a non-limiting example, syntax can be coded in the bitstream that indicates which nodes were split with quadtree partitioning, which were split with symmetric binary partitioning, and which were split with asymmetric binary partitioning. Similarly, syntax can be coded in the bitstream for nodes split with asymmetric binary partitioning that indicates which type of asymmetric binary partitioning was used, such as one of the four types shown in  FIG.  4   . 
     In some embodiments the use of asymmetric partitioning can be limited to splitting CUs  102  at the leaf nodes of the quadtree portion of a QTBT. In these embodiments, CUs  102  at child nodes that were split from a parent node using quadtree partitioning in the quadtree portion can be final CUs  102 , or they can be further split using quadtree partitioning, symmetric binary partitioning, or asymmetric binary partitioning. Child nodes in the binary tree portion that were split using symmetric binary partitioning can be final CUs  102 , or they can be further split recursively one or more times using symmetric binary partitioning only. Child nodes in the binary tree portion that were split from a QT leaf node using asymmetric binary partitioning can be final CUs  102 , with no further splitting permitted. 
     In these embodiments, limiting the use of asymmetric partitioning to splitting quadtree leaf nodes can reduce search complexity and/or limit overhead bits. Because only quadtree leaf nodes can be split with asymmetric partitioning, the use of asymmetric partitioning can directly indicate the end of a branch of the QT portion without other syntax or further signaling. Similarly, because asymmetrically partitioned nodes cannot be split further, the use of asymmetric partitioning on a node can also directly indicate that its asymmetrically partitioned child nodes are final CUs  102  without other syntax or further signaling. 
     In alternate embodiments, such as when limiting search complexity and/or limiting the number of overhead bits is less of a concern, asymmetric partitioning can be used to split nodes generated with quadtree partitioning, symmetric binary partitioning, and/or asymmetric binary partitioning. 
     After quadtree splitting and binary tree splitting using either QTBT structure described above, the blocks represented by the QTBT&#39;s leaf nodes represent the final CUs  102  to be coded, such as coding using inter prediction or intra prediction. For slices or full frames coded with inter prediction, different partitioning structures can be used for luma and chroma components. For example, for an inter slice a CU  102  can have Coding Blocks (CBs) for different color components, such as such as one luma CB and two chroma CBs. For slices or full frames coded with intra prediction, the partitioning structure can be the same for luma and chroma components. 
     In alternate embodiments WET can use a two-level coding block structure as an alternative to, or extension of, the QTBT partitioning described above. In the two-level coding block structure, a CTU  100  can first be partitioned at a high level into base units (BUs). The BUs can then be partitioned at a low level into operating units (OUs). 
     In embodiments employing the two-level coding block structure, at the high level a CTU  100  can be partitioned into BUs according to one of the QTBT structures described above, or according to a quadtree (QT) structure such as the one used in HEVC in which blocks can only be split into four equally sized sub-blocks. By way of a non-limiting example, a CTU  102  can be partitioned into BUs according to the QTBT structure described above with respect to  FIGS.  5 - 6   , such that leaf nodes in the quadtree portion can be split using quadtree partitioning, symmetric binary partitioning, or asymmetric binary partitioning. In this example, the final leaf nodes of the QTBT can be BUs instead of CUs. 
     At the lower level in the two-level coding block structure, each BU partitioned from the CTU  100  can be further partitioned into one or more OUs. In some embodiments, when the BU is square, it can be split into OUs using quadtree partitioning or binary partitioning, such as symmetric or asymmetric binary partitioning. However, when the BU is not square, it can be split into OUs using binary partitioning only. Limiting the type of partitioning that can be used for non-square BUs can limit the number of bits used to signal the type of partitioning used to generate BUs. 
     Although the discussion below describes coding CUs  102 , BUs and OUs can be coded instead of CUs  102  in embodiments that use the two-level coding block structure. By way of a non-limiting examples, BUs can be used for higher level coding operations such as intra prediction or inter prediction, while the smaller OUs can be used for lower level coding operations such as transforms and generating transform coefficients. Accordingly, syntax for be coded for BUs that indicate whether they are coded with intra prediction or inter prediction, or information identifying particular intra prediction modes or motion vectors used to code the BUs. Similarly, syntax for OUs can identify particular transform operations or quantized transform coefficients used to code the OUs. 
       FIG.  7    depicts a simplified block diagram for CU coding in a JVET encoder. The main stages of video coding include partitioning to identify CUs  102  as described above, followed by encoding CUs  102  using prediction at  704  or  706 , generation of a residual CU  710  at  708 , transformation at  712 , quantization at  716 , and entropy coding at  720 . The encoder and encoding process illustrated in  FIG.  7    also includes a decoding process that is described in more detail below. 
     Given a current CU  102 , the encoder can obtain a prediction CU  702  either spatially using intra prediction at  704  or temporally using inter prediction at  706 . The basic idea of prediction coding is to transmit a differential, or residual, signal between the original signal and a prediction for the original signal. At the receiver side, the original signal can be reconstructed by adding the residual and the prediction, as will be described below. Because the differential signal has a lower correlation than the original signal, fewer bits are needed for its transmission. 
     A slice, such as an entire picture or a portion of a picture, coded entirely with intra-predicted CUs  102  can be an I slice that can be decoded without reference to other slices, and as such can be a possible point where decoding can begin. A slice coded with at least some inter-predicted CUs can be a predictive (P) or bi-predictive (B) slice that can be decoded based on one or more reference pictures. P slices may use intra-prediction and inter-prediction with previously coded slices. For example, P slices may be compressed further than the I-slices by the use of inter-prediction, but need the coding of a previously coded slice to code them. B slices can use data from previous and/or subsequent slices for its coding, using intra-prediction or inter-prediction using an interpolated prediction from two different frames, thus increasing the accuracy of the motion estimation process. In some cases P slices and B slices can also or alternately be encoded using intra block copy, in which data from other portions of the same slice is used. 
     As will be discussed below, intra prediction or inter prediction can be performed based on reconstructed CUs  734  from previously coded CUs  102 , such as neighboring CUs  102  or CUs  102  in reference pictures. 
     When a CU  102  is coded spatially with intra prediction at  704 , an intra prediction mode can be found that best predicts pixel values of the CU  102  based on samples from neighboring CUs  102  in the picture. 
     When coding a CU&#39;s luma component, the encoder can generate a list of candidate intra prediction modes. While HEVC had 35 possible intra prediction modes for luma components, in NET there are 67 possible intra prediction modes for luma components. These include a planar mode that uses a three dimensional plane of values generated from neighboring pixels, a DC mode that uses values averaged from neighboring pixels, and the 65 directional modes shown in  FIG.  8    that use values copied from neighboring pixels along the indicated directions. 
     When generating a list of candidate intra prediction modes for a CU&#39;s luma component, the number of candidate modes on the list can depend on the CU&#39;s size. The candidate list can include: a subset of HEVC&#39;s 35 modes with the lowest SATD (Sum of Absolute Transform Difference) costs; new directional modes added for NET that neighbor the candidates found from the HEVC modes; and modes from a set of six most probable modes (MPMs) for the CU  102  that are identified based on intra prediction modes used for previously coded neighboring blocks as well as a list of default modes. 
     When coding a CU&#39;s chroma components, a list of candidate intra prediction modes can also be generated. The list of candidate modes can include modes generated with cross-component linear model projection from luma samples, intra prediction modes found for luma CBs in particular collocated positions in the chroma block, and chroma prediction modes previously found for neighboring blocks. The encoder can find the candidate modes on the lists with the lowest rate distortion costs, and use those intra prediction modes when coding the CU&#39;s luma and chroma components. Syntax can be coded in the bitstream that indicates the intra prediction modes used to code each CU  102 . 
     After the best intra prediction modes for a CU  102  have been selected, the encoder can generate a prediction CU  402  using those modes. When the selected modes are directional modes, a 4-tap filter can be used to improve the directional accuracy. Columns or rows at the top or left side of the prediction block can be adjusted with boundary prediction filters, such as 2-tap or 3-tap filters. 
     The prediction CU  702  can be smoothed further with a position dependent intra prediction combination (PDPC) process that adjusts a prediction CU  702  generated based on filtered samples of neighboring blocks using unfiltered samples of neighboring blocks, or adaptive reference sample smoothing using 3-tap or 5-tap low pass filters to process reference samples. 
     When a CU  102  is coded temporally with inter prediction at  706 , a set of motion vectors (MVs) can be found that points to samples in reference pictures that best predict pixel values of the CU  102 . Inter prediction exploits temporal redundancy between slices by representing a displacement of a block of pixels in a slice. The displacement is determined according to the value of pixels in previous or following slices through a process called motion compensation. Motion vectors and associated reference indices that indicate pixel displacement relative to a particular reference picture can be provided in the bitstream to a decoder, along with the residual between the original pixels and the motion compensated pixels. The decoder can use the residual and signaled motion vectors and reference indices to reconstruct a block of pixels in a reconstructed slice. 
     In JVET, motion vector accuracy can be stored at 1/16 pel, and the difference between a motion vector and a CU&#39;s predicted motion vector can be coded with either quarter-pel resolution or integer-pel resolution. 
     In JVET motion vectors can be found for multiple sub-CUs within a CU  102 , using techniques such as advanced temporal motion vector prediction (ATMVP), spatial-temporal motion vector prediction (STMVP), affine motion compensation prediction, pattern matched motion vector derivation (PMMVD), and/or bi-directional optical flow (BIO). 
     Using ATMVP, the encoder can find a temporal vector for the CU  102  that points to a corresponding block in a reference picture. The temporal vector can be found based on motion vectors and reference pictures found for previously coded neighboring CUs  102 . Using the reference block pointed to by a temporal vector for the entire CU  102 , a motion vector can be found for each sub-CU within the CU  102 . 
     STMVP can find motion vectors for sub-CUs by scaling and averaging motion vectors found for neighboring blocks previously coded with inter prediction, together with a temporal vector. 
     Affine motion compensation prediction can be used to predict a field of motion vectors for each sub-CU in a block, based on two control motion vectors found for the top corners of the block. For example, motion vectors for sub-CUs can be derived based on top corner motion vectors found for each 4×4 block within the CU  102 . 
     PMMVD can find an initial motion vector for the current CU  102  using bilateral matching or template matching. Bilateral matching can look at the current CU  102  and reference blocks in two different reference pictures along a motion trajectory, while template matching can look at corresponding blocks in the current CU  102  and a reference picture identified by a template. The initial motion vector found for the CU  102  can then be refined individually for each sub-CU. 
     BIO can be used when inter prediction is performed with bi-prediction based on earlier and later reference pictures, and allows motion vectors to be found for sub-CUs based on the gradient of the difference between the two reference pictures. 
     In some situations local illumination compensation (LIC) can be used at the CU level to find values for a scaling factor parameter and an offset parameter, based on samples neighboring the current CU  102  and corresponding samples neighboring a reference block identified by a candidate motion vector. In JVET, the LIC parameters can change and be signaled at the CU level. 
     For some of the above methods the motion vectors found for each of a CU&#39;s sub-CUs can be signaled to decoders at the CU level. For other methods, such as PMMVD and BIO, motion information is not signaled in the bitstream to save overhead, and decoders can derive the motion vectors through the same processes. 
     After the motion vectors for a CU  102  have been found, the encoder can generate a prediction CU  702  using those motion vectors. In some cases, when motion vectors have been found for individual sub-CUs, Overlapped Block Motion Compensation (OBMC) can be used when generating a prediction CU  702  by combining those motion vectors with motion vectors previously found for one or more neighboring sub-CUs. 
     When bi-prediction is used, JVET can use decoder-side motion vector refinement (DMVR) to find motion vectors. DMVR allows a motion vector to be found based on two motion vectors found for bi-prediction using a bilateral template matching process. In DMVR, a weighted combination of prediction CUs  702  generated with each of the two motion vectors can be found, and the two motion vectors can be refined by replacing them with new motion vectors that best point to the combined prediction CU  702 . The two refined motion vectors can be used to generate the final prediction CU  702 . 
     At  708 , once a prediction CU  702  has been found with intra prediction at  704  or inter prediction at  706  as described above, the encoder can subtract the prediction CU  702  from the current CU  102  find a residual CU  710 . 
     The encoder can use one or more transform operations at  712  to convert the residual CU  710  into transform coefficients  714  that express the residual CU  710  in a transform domain, such as using a discrete cosine block transform (DCT-transform) to convert data into the transform domain. JVET allows more types of transform operations than HEVC, including DCT-II, DST-VII, DST-VII, DCT-VIII, DST-I, and DCT-V operations. The allowed transform operations can be grouped into sub-sets, and an indication of which sub-sets and which specific operations in those sub-sets were used can be signaled by the encoder. In some cases, large block-size transforms can be used to zero out high frequency transform coefficients in CUs  102  larger than a certain size, such that only lower-frequency transform coefficients are maintained for those CUs  102 . 
     In some cases a mode dependent non-separable secondary transform (MDNSST) can be applied to low frequency transform coefficients  714  after a forward core transform. The MDNSST operation can use a Hypercube-Givens Transform (HyGT) based on rotation data. When used, an index value identifying a particular MDNSST operation can be signaled by the encoder. 
     At  716 , the encoder can quantize the transform coefficients  714  into quantized transform coefficients  716 . The quantization of each coefficient may be computed by dividing a value of the coefficient by a quantization step, which is derived from a quantization parameter (QP). In some embodiments, the Qstep is defined as 2 (QP-4)/6 . Because high precision transform coefficients  714  can be converted into quantized transform coefficients  716  with a finite number of possible values, quantization can assist with data compression. Thus, quantization of the transform coefficients may limit an amount of bits generated and sent by the transformation process. However, while quantization is a lossy operation, and the loss by quantization cannot be recovered, the quantization process presents a trade-off between quality of the reconstructed sequence and an amount of information needed to represent the sequence. For example, a lower QP value can result in better quality decoded video, although a higher amount of data may be required for representation and transmission. In contrast, a high QP value can result in lower quality reconstructed video sequences but with lower data and bandwidth needs. 
     JVET can utilize variance-based adaptive quantization techniques, which allows every CU  102  to use a different quantization parameter for its coding process (instead of using the same frame QP in the coding of every CU  102  of the frame). The variance-based adaptive quantization techniques adaptively lowers the quantization parameter of certain blocks while increasing it in others. To select a specific QP for a CU  102 , the CU&#39;s variance is computed. In brief, if a CU&#39;s variance is higher than the average variance of the frame, a higher QP than the frame&#39;s QP may be set for the CU  102 . If the CU  102  presents a lower variance than the average variance of the frame, a lower QP may be assigned. 
     At  720 , the encoder can find final compression bits  722  by entropy coding the quantized transform coefficients  718 . Entropy coding aims to remove statistical redundancies of the information to be transmitted. In NET, CABAC (Context Adaptive Binary Arithmetic Coding) can be used to code the quantized transform coefficients  718 , which uses probability measures to remove the statistical redundancies. For CUs  102  with non-zero quantized transform coefficients  718 , the quantized transform coefficients  718  can be converted into binary. Each bit (“bin”) of the binary representation can then be encoded using a context model. A CU  102  can be broken up into three regions, each with its own set of context models to use for pixels within that region. 
     Multiple scan passes can be performed to encode the bins. During passes to encode the first three bins (bin 0 , bin 1 , and bin 2 ), an index value that indicates which context model to use for the bin can be found by finding the sum of that bin position in up to five previously coded neighboring quantized transform coefficients  718  identified by a template. 
     A context model can be based on probabilities of a bin&#39;s value being ‘0’ or ‘1’. As values are coded, the probabilities in the context model can be updated based on the actual number of ‘0’ and ‘1’ values encountered. While HEVC used fixed tables to re-initialize context models for each new picture, in NET the probabilities of context models for new inter-predicted pictures can be initialized based on context models developed for previously coded inter-predicted pictures. 
     The encoder can produce a bitstream that contains entropy encoded bits  722  of residual CUs  710 , prediction information such as selected intra prediction modes or motion vectors, indicators of how the CUs  102  were partitioned from a CTU  100  according to the QTBT structure, and/or other information about the encoded video. The bitstream can be decoded by a decoder as discussed below. 
     In addition to using the quantized transform coefficients  718  to find the final compression bits  722 , the encoder can also use the quantized transform coefficients  718  to generate reconstructed CUs  734  by following the same decoding process that a decoder would use to generate reconstructed CUs  734 . Thus, once the transformation coefficients have been computed and quantized by the encoder, the quantized transform coefficients  718  may be transmitted to the decoding loop in the encoder. After quantization of a CU&#39;s transform coefficients, a decoding loop allows the encoder to generate a reconstructed CU  734  identical to the one the decoder generates in the decoding process. Accordingly, the encoder can use the same reconstructed CUs  734  that a decoder would use for neighboring CUs  102  or reference pictures when performing intra prediction or inter prediction for a new CU  102 . Reconstructed CUs  102 , reconstructed slices, or full reconstructed frames may serve as references for further prediction stages. 
     At the encoder&#39;s decoding loop (and see below, for the same operations in the decoder) to obtain pixel values for the reconstructed image, a dequantization process may be performed. To dequantize a frame, for example, a quantized value for each pixel of a frame is multiplied by the quantization step, e.g., (Qstep) described above, to obtain reconstructed dequantized transform coefficients  726 . For example, in the decoding process shown in  FIG.  7    in the encoder, the quantized transform coefficients  718  of a residual CU  710  can be dequantized at  724  to find dequantized transform coefficients  726 . If an MDNSST operation was performed during encoding, that operation can be reversed after dequantization. 
     At  728 , the dequantized transform coefficients  726  can be inverse transformed to find a reconstructed residual CU  730 , such as by applying a DCT to the values to obtain the reconstructed image. At  732  the reconstructed residual CU  730  can be added to a corresponding prediction CU  702  found with intra prediction at  704  or inter prediction at  706 , in order to find a reconstructed CU  734 . 
     At  736 , one or more filters can be applied to the reconstructed data during the decoding process (in the encoder or, as described below, in the decoder), at either a picture level or CU level. For example, the encoder can apply a deblocking filter, a sample adaptive offset (SAO) filter, and/or an adaptive loop filter (ALF). The encoder&#39;s decoding process may implement filters to estimate and transmit to a decoder the optimal filter parameters that can address potential artifacts in the reconstructed image. Such improvements increase the objective and subjective quality of the reconstructed video. In deblocking filtering, pixels near a sub-CU boundary may be modified, whereas in SAO, pixels in a CTU  100  may be modified using either an edge offset or band offset classification. JVET&#39;s ALF can use filters with circularly symmetric shapes for each 2×2 block. An indication of the size and identity of the filter used for each 2×2 block can be signaled. 
     If reconstructed pictures are reference pictures, they can be stored in a reference buffer  738  for inter prediction of future CUs  102  at  706 . 
     During the above steps, JVET allows a content adaptive clipping operations to be used to adjust color values to fit between lower and upper clipping bounds. The clipping bounds can change for each slice, and parameters identifying the bounds can be signaled in the bitstream. 
       FIG.  9    depicts a simplified block diagram for CU coding in a JVET decoder. A JVET decoder can receive a bitstream containing information about encoded CUs  102 . The bitstream can indicate how CUs  102  of a picture were partitioned from a CTU  100  according to a QTBT structure. By way of a non-limiting example, the bitstream can identify how CUs  102  were partitioned from each CTU  100  in a QTBT using quadtree partitioning, symmetric binary partitioning, and/or asymmetric binary partitioning. The bitstream can also indicate prediction information for the CUs  102  such as intra prediction modes or motion vectors, and bits  902  representing entropy encoded residual CUs. 
     At  904  the decoder can decode the entropy encoded bits  902  using the CABAC context models signaled in the bitstream by the encoder. The decoder can use parameters signaled by the encoder to update the context models&#39; probabilities in the same way they were updated during encoding. 
     After reversing the entropy encoding at  904  to find quantized transform coefficients  906 , the decoder can dequantize them at  908  to find dequantized transform coefficients  910 . If an MDNSST operation was performed during encoding, that operation can be reversed by the decoder after dequantization. 
     At  912 , the dequantized transform coefficients  910  can be inverse transformed to find a reconstructed residual CU  914 . At  916 , the reconstructed residual CU  914  can be added to a corresponding prediction CU  926  found with intra prediction at  922  or inter prediction at  924 , in order to find a reconstructed CU  918 . 
     At  920 , one or more filters can be applied to the reconstructed data, at either a picture level or CU level. For example, the decoder can apply a deblocking filter, a sample adaptive offset (SAO) filter, and/or an adaptive loop filter (ALF). As described above, the in-loop filters located in the decoding loop of the encoder may be used to estimate optimal filter parameters to increase the objective and subjective quality of a frame. These parameters are transmitted to the decoder to filter the reconstructed frame at  920  to match the filtered reconstructed frame in the encoder. 
     After reconstructed pictures have been generated by finding reconstructed CUs  918  and applying signaled filters, the decoder can output the reconstructed pictures as output video  928 . If reconstructed pictures are to be used as reference pictures, they can be stored in a reference buffer  930  for inter prediction of future CUs  102  at  924 . 
       FIG.  10    depicts an embodiment of a method of CU coding  1000  in a JVET decoder. In the embodiment depicted in  FIG.  10   , in step  1002  an encoded bitstream  902  can be received and then in step  1004  the CABAC context model associated with the encoded bitstream  902  can be determined and the encoded bitstream  902  can then be decoded using the determined CABAC context model in step  1006 . 
     In step  1008 , the quantized transform coefficients  906  associated with the encoded bitstream  902  can be determined and de-quantized transform coefficients  910  can then be determined from the quantized transform coefficients  906  in step  1010 . 
     In step  1012 , it can be determined whether an MDNSST operation was performed during encoding and/or if the bitstream  902  contains indications that an MDNSST operation was applied to the bitstream  902 . If it is determined that an MDNSST operation was performed during the encoding process or the bitstream  902  contains indications that an MDNSST operation was applied to the bitstream  902 , then an inverse MDNSST operation  1014  can be implemented before an inverse transform operation  912  is performed on the bitstream  902  in step  1016 . Alternately, an inverse transform operation  912  can be performed on the bitstream  902  in step  1016  absent application of an inverse MDNSST operation in step  1014 . The inverse transform operation  912  in step  1016  can determine and/or construct a reconstructed residual CU  914 . 
     In step  1018 , the reconstructed residual CU  914  from step  1016  can be combined with a prediction CU  918 . The prediction CU  918  can be one of an intra-prediction CU  922  determined in step  1020  and an inter-prediction unit  924  determined in step  1022 . 
     In step  1024 , any one or more filters  920  can be applied to the reconstructed CU  914  and output in step  1026 . In some embodiments filters  920  may not be applied in step  1024 . 
     In some embodiments, in step  1028 , the reconstructed CU  918  can be stored in a reference buffer  930 . 
       FIG.  11    depicts a simplified block diagram  1100  for CU coding in a JVET encoder. In step  1102  a JVET coding tree unit can be represented as a root node in a quadtree plus binary tree (QTBT) structure. In some embodiments the QTBT can have a quadtree branching from the root node and/or binary trees branching from one or more of the quadtree&#39;s leaf nodes. The representation from step  1102  can proceed to step  1104 ,  1106  or  1108 . 
     In step  1104 , asymmetric binary partitioning can be employed to split a represented quadtree node into two blocks of unequal size. In some embodiments, the split blocks can be represented in a binary tree branching from the quadtree node as leaf nodes that can represent final coding units. In some embodiment, the binary tree branching from the quadtree node as leaf nodes represent final coding units in which further splitting is disallowed. In some embodiments the asymmetric partitioning can split a coding unit into blocks of unequal size, a first representing 25% of the quadtree node and a second representing 75% of the quadtree node. 
     In step  1106 , quadtree partitioning can be employed to split a represented quadtree note into four square blocks of equal size. In some embodiments the split blocks can be represented as quadtree notes that represent final coding units or can be represented as child nodes that can be split again with quadtree partitioning, symmetric binary partitioning, or asymmetric binary partitioning. 
     In step  1108  quadtree partitioning can be employed to split a represented quadtree note into two blocks of equal size. In some embodiments the split blocks can be represented as quadtree notes that represent final coding units or can be represented as child nodes that can be split again with quadtree partitioning, symmetric binary partitioning, or asymmetric binary partitioning. 
     In step  1110 , child nodes from step  1106  or step  1108  can be represented as child coding units configured to be encoded. In some embodiments the child coding units can be represented by leaf notes of the binary tree with JVET. 
     In step  1112 , coding units from step  1104  or  1110  can be encoded using JVET. 
       FIG.  12    depicts a simplified block diagram  1200  for CU decoding in a JVET decoder. In the embodiment depicted in  FIG.  12   , in step  1202  a bitstream indicating how a coding tree unit was partitioned into coding units according to a QTBT structure can be received. The bitstream can indicate how quadtree nodes are split with at least one of quadtree partitioning, symmetric binary partitioning or asymmetric binary partitioning. 
     In step  1204 , coding units, represented by leaf nodes of the QTBT structure can be identified. In some embodiments, the coding units can indicate whether a node was split from a quadtree leaf node using asymmetric binary partitioning. In some embodiments, the coding unit can indicate that the node represents a final coding unit to be decoded. 
     In step  1206 , the identified coding unit(s) can be decoded using JVET. 
     The execution of the sequences of instructions required to practice the embodiments can be performed by a computer system  1300  as shown in  FIG.  13   . In an embodiment, execution of the sequences of instructions is performed by a single computer system  1300 . According to other embodiments, two or more computer systems  1300  coupled by a communication link  1315  can perform the sequence of instructions in coordination with one another. Although a description of only one computer system  1300  will be presented below, however, it should be understood that any number of computer systems  1300  can be employed to practice the embodiments. 
     A computer system  1300  according to an embodiment will now be described with reference to  FIG.  13   , which is a block diagram of the functional components of a computer system  1300 . As used herein, the term computer system  1300  is broadly used to describe any computing device that can store and independently run one or more programs. 
     Each computer system  1300  can include a communication interface  1314  coupled to the bus  1306 . The communication interface  1314  provides two-way communication between computer systems  1300 . The communication interface  1314  of a respective computer system  1300  transmits and receives electrical, electromagnetic or optical signals that include data streams representing various types of signal information, e.g., instructions, messages and data. A communication link  1315  links one computer system  1300  with another computer system  1300 . For example, the communication link  1315  can be a LAN, in which case the communication interface  1314  can be a LAN card, or the communication link  1315  can be a PSTN, in which case the communication interface  1314  can be an integrated services digital network (ISDN) card or a modem, or the communication link  1315  can be the Internet, in which case the communication interface  1314  can be a dial-up, cable or wireless modem. 
     A computer system  1300  can transmit and receive messages, data, and instructions, including program, i.e., application, code, through its respective communication link  1315  and communication interface  1314 . Received program code can be executed by the respective processor(s)  1307  as it is received, and/or stored in the storage device  1310 , or other associated non-volatile media, for later execution. 
     In an embodiment, the computer system  1300  operates in conjunction with a data storage system  1331 , e.g., a data storage system  1331  that contains a database  1332  that is readily accessible by the computer system  1300 . The computer system  1300  communicates with the data storage system  1331  through a data interface  1333 . A data interface  1333 , which is coupled to the bus  1306 , transmits and receives electrical, electromagnetic or optical signals, that include data streams representing various types of signal information, e.g., instructions, messages and data. In embodiments, the functions of the data interface  1333  can be performed by the communication interface  1314 . 
     Computer system  1300  includes a bus  1306  or other communication mechanism for communicating instructions, messages and data, collectively, information, and one or more processors  1307  coupled with the bus  1306  for processing information. Computer system  1300  also includes a main memory  1308 , such as a random access memory (RAM) or other dynamic storage device, coupled to the bus  1306  for storing dynamic data and instructions to be executed by the processor(s)  1307 . The main memory  1308  also can be used for storing temporary data, i.e., variables, or other intermediate information during execution of instructions by the processor(s)  1307 . 
     The computer system  1300  can further include a read only memory (ROM)  1309  or other static storage device coupled to the bus  1306  for storing static data and instructions for the processor(s)  1307 . A storage device  1310 , such as a magnetic disk or optical disk, can also be provided and coupled to the bus  1306  for storing data and instructions for the processor(s)  1307 . 
     A computer system  1300  can be coupled via the bus  1306  to a display device  1311 , such as, but not limited to, a cathode ray tube (CRT) or a liquid-crystal display (LCD) monitor, for displaying information to a user. An input device  1312 , e.g., alphanumeric and other keys, is coupled to the bus  1306  for communicating information and command selections to the processor(s)  1307 . 
     According to one embodiment, an individual computer system  1300  performs specific operations by their respective processor(s)  1307  executing one or more sequences of one or more instructions contained in the main memory  1308 . Such instructions can be read into the main memory  1308  from another computer-usable medium, such as the ROM  1309  or the storage device  1310 . Execution of the sequences of instructions contained in the main memory  1308  causes the processor(s)  1307  to perform the processes described herein. In alternative embodiments, hard-wired circuitry can be used in place of or in combination with software instructions. Thus, embodiments are not limited to any specific combination of hardware circuitry and/or software. 
     The term “computer-usable medium,” as used herein, refers to any medium that provides information or is usable by the processor(s)  1307 . Such a medium can take many forms, including, but not limited to, non-volatile, volatile and transmission media. Non-volatile media, i.e., media that can retain information in the absence of power, includes the ROM  1309 , CD ROM, magnetic tape, and magnetic discs. Volatile media, i.e., media that can not retain information in the absence of power, includes the main memory  1308 . Transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise the bus  1306 . Transmission media can also take the form of carrier waves; i.e., electromagnetic waves that can be modulated, as in frequency, amplitude or phase, to transmit information signals. Additionally, transmission media can take the form of acoustic or light waves, such as those generated during radio wave and infrared data communications. 
     In the foregoing specification, the embodiments have been described with reference to specific elements thereof. It will, however, be evident that various modifications and changes can be made thereto without departing from the broader spirit and scope of the embodiments. For example, the reader is to understand that the specific ordering and combination of process actions shown in the process flow diagrams described herein is merely illustrative, and that using different or additional process actions, or a different combination or ordering of process actions can be used to enact the embodiments. The specification and drawings are, accordingly, to be regarded in an illustrative rather than restrictive sense. 
     It should also be noted that the present invention can be implemented in a variety of computer systems. The various techniques described herein can be implemented in hardware or software, or a combination of both. Preferably, the techniques are implemented in computer programs executing on programmable computers that each include a processor, a storage medium readable by the processor (including volatile and non-volatile memory and/or storage elements), at least one input device, and at least one output device. Program code is applied to data entered using the input device to perform the functions described above and to generate output information. The output information is applied to one or more output devices. Each program is preferably implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the programs can be implemented in assembly or machine language, if desired. In any case, the language can be a compiled or interpreted language. Each such computer program is preferably stored on a storage medium or device (e.g., ROM or magnetic disk) that is readable by a general or special purpose programmable computer for configuring and operating the computer when the storage medium or device is read by the computer to perform the procedures described above. The system can also be considered to be implemented as a computer-readable storage medium, configured with a computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner. Further, the storage elements of the exemplary computing applications can be relational or sequential (flat file) type computing databases that are capable of storing data in various combinations and configurations. 
       FIG.  14    is a high level view of a source device  1412  and destination device  1410  that may incorporate features of the systems and devices described herein. As shown in  FIG.  14   , example video coding system  1410  includes a source device  1412  and a destination device  1414  where, in this example, the source device  1412  generates encoded video data. Accordingly, source device  1412  may be referred to as a video encoding device. Destination device  1414  may decode the encoded video data generated by source device  1412 . Accordingly, destination device  1414  may be referred to as a video decoding device. Source device  1412  and destination device  1414  may be examples of video coding devices. 
     Destination device  1414  may receive encoded video data from source device  1412  via a channel  1416 . Channel  1416  may comprise a type of medium or device capable of moving the encoded video data from source device  1412  to destination device  1414 . In one example, channel  1416  may comprise a communication medium that enables source device  1412  to transmit encoded video data directly to destination device  1414  in real-time. 
     In this example, source device  1412  may modulate the encoded video data according to a communication standard, such as a wireless communication protocol, and may transmit the modulated video data to destination device  1414 . The communication medium may comprise a wireless or wired communication medium, such as a radio frequency (RF) spectrum or one or more physical transmission lines. The communication medium may form part of a packet-based network, such as a local area network, a wide-area network, or a global network such as the Internet. The communication medium may include routers, switches, base stations, or other equipment that facilitates communication from source device  1412  to destination device  1414 . In another example, channel  1416  may correspond to a storage medium that stores the encoded video data generated by source device  1412 . 
     In the example of  FIG.  14   , source device  1412  includes a video source  1418 , video encoder  1420 , and an output interface  1422 . In some cases, output interface  1428  may include a modulator/demodulator (modem) and/or a transmitter. In source device  1412 , video source  1418  may include a source such as a video capture device, e.g., a video camera, a video archive containing previously captured video data, a video feed interface to receive video data from a video content provider, and/or a computer graphics system for generating video data, or a combination of such sources. 
     Video encoder  1420  may encode the captured, pre-captured, or computer-generated video data. An input image may be received by the video encoder  1420  and stored in the input frame memory  1421 . The general purpose processor  1423  may load information from here and perform encoding. The program for driving the general purpose processor may be loaded from a storage device, such as the example memory modules depicted in  FIG.  14   . The general purpose processor may use processing memory  1422  to perform the encoding, and the output of the encoding information by the general processor may be stored in a buffer, such as output buffer  1426 . 
     The video encoder  1420  may include a resampling module  1425  which may be configured to code (e.g., encode) video data in a scalable video coding scheme that defines at least one base layer and at least one enhancement layer. Resampling module  1425  may resample at least some video data as part of an encoding process, wherein resampling may be performed in an adaptive manner using resampling filters. 
     The encoded video data, e.g., a coded bit stream, may be transmitted directly to destination device  1414  via output interface  1428  of source device  1412 . In the example of  FIG.  14   , destination device  1414  includes an input interface  1438 , a video decoder  1430 , and a display device  1432 . In some cases, input interface  1428  may include a receiver and/or a modem. Input interface  1438  of destination device  1414  receives encoded video data over channel  1416 . The encoded video data may include a variety of syntax elements generated by video encoder  1420  that represent the video data. Such syntax elements may be included with the encoded video data transmitted on a communication medium, stored on a storage medium, or stored a file server. 
     The encoded video data may also be stored onto a storage medium or a file server for later access by destination device  1414  for decoding and/or playback. For example, the coded bitstream may be temporarily stored in the input buffer  1431 , then loaded in to the general purpose processor  1433 . The program for driving the general purpose processor may be loaded from a storage device or memory. The general purpose processor may use a process memory  1432  to perform the decoding. The video decoder  1430  may also include a resampling module  1435  similar to the resampling module  1425  employed in the video encoder  1420 . 
       FIG.  14    depicts the resampling module  1435  separately from the general purpose processor  1433 , but it would be appreciated by one of skill in the art that the resampling function may be performed by a program executed by the general purpose processor, and the processing in the video encoder may be accomplished using one or more processors. The decoded image(s) may be stored in the output frame buffer  1436  and then sent out to the input interface  1438 . 
     Display device  1438  may be integrated with or may be external to destination device  1414 . In some examples, destination device  1414  may include an integrated display device and may also be configured to interface with an external display device. In other examples, destination device  1414  may be a display device. In general, display device  1438  displays the decoded video data to a user. 
     Video encoder  1420  and video decoder  1430  may operate according to a video compression standard. ITU-T VCEG (Q6/16) and ISO/IEC MPEG (JTC 1/SC 29/WG 11) are studying the potential need for standardization of future video coding technology with a compression capability that significantly exceeds that of the current High Efficiency Video Coding HEVC standard (including its current extensions and near-term extensions for screen content coding and high-dynamic-range coding). The groups are working together on this exploration activity in a joint collaboration effort known as the Joint Video Exploration Team (WET) to evaluate compression technology designs proposed by their experts in this area. A recent capture of JVET development is described in the “Algorithm Description of Joint Exploration Test Model 5 (JEM 5)”, JVET-E1001-V2, authored by J. Chen, E. Alshina, G. Sullivan, J. Ohm, J. Boyce. 
     Additionally or alternatively, video encoder  1420  and video decoder  1430  may operate according to other proprietary or industry standards that function with the disclosed JVET features. Thus, other standards such as the ITU-T H.264 standard, alternatively referred to as MPEG-4, Part 10, Advanced Video Coding (AVC), or extensions of such standards. Thus, while newly developed for JVET, techniques of this disclosure are not limited to any particular coding standard or technique. Other examples of video compression standards and techniques include MPEG-2, ITU-T H.263 and proprietary or open source compression formats and related formats. 
     Video encoder  1420  and video decoder  1430  may be implemented in hardware, software, firmware or any combination thereof. For example, the video encoder  1420  and decoder  1430  may employ one or more processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic, or any combinations thereof. When the video encoder  1420  and decoder  1430  are implemented partially in software, a device may store instructions for the software in a suitable, non-transitory computer-readable storage medium and may execute the instructions in hardware using one or more processors to perform the techniques of this disclosure. Each of video encoder  1420  and video decoder  1430  may be included in one or more encoders or decoders, either of which may be integrated as part of a combined encoder/decoder (CODEC) in a respective device. 
     Aspects of the subject matter described herein may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer, such as the general purpose processors  1423  and  1433  described above. Generally, program modules include routines, programs, objects, components, data structures, and so forth, which perform particular tasks or implement particular abstract data types. Aspects of the subject matter described herein may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices. 
     Examples of memory include random access memory (RAM), read only memory (ROM), or both. Memory may store instructions, such as source code or binary code, for performing the techniques described above. Memory may also be used for storing variables or other intermediate information during execution of instructions to be executed by a processor, such as processor  1423  and  1433 . 
     A storage device may also store instructions, instructions, such as source code or binary code, for performing the techniques described above. A storage device may additionally store data used and manipulated by the computer processor. For example, a storage device in a video encoder  1420  or a video decoder  1430  may be a database that is accessed by computer system  1423  or  1433 . Other examples of storage device include random access memory (RAM), read only memory (ROM), a hard drive, a magnetic disk, an optical disk, a CD-ROM, a DVD, a flash memory, a USB memory card, or any other medium from which a computer can read. 
     A memory or storage device may be an example of a non-transitory computer-readable storage medium for use by or in connection with the video encoder and/or decoder. The non-transitory computer-readable storage medium contains instructions for controlling a computer system to be configured to perform functions described by particular embodiments. The instructions, when executed by one or more computer processors, may be configured to perform that which is described in particular embodiments. 
     Also, it is noted that some embodiments have been described as a process which can be depicted as a flow diagram or block diagram. Although each may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be rearranged. A process may have additional steps not included in the figures. 
     Particular embodiments may be implemented in a non-transitory computer-readable storage medium for use by or in connection with the instruction execution system, apparatus, system, or machine. The computer-readable storage medium contains instructions for controlling a computer system to perform a method described by particular embodiments. The computer system may include one or more computing devices. The instructions, when executed by one or more computer processors, may be configured to perform that which is described in particular embodiments 
     As used in the description herein and throughout the claims that follow, “a”, “an”, and “the” includes plural references unless the context clearly dictates otherwise. Also, as used in the description herein and throughout the claims that follow, the meaning of “in” includes “in” and “on” unless the context clearly dictates otherwise. 
     Although exemplary embodiments of the invention have been described in detail and in language specific to structural features and/or methodological acts above, it is to be understood that those skilled in the art will readily appreciate that many additional modifications are possible in the exemplary embodiments without materially departing from the novel teachings and advantages of the invention. Moreover, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Accordingly, these and all such modifications are intended to be included within the scope of this invention construed in breadth and scope in accordance with the appended claims.