Patent Publication Number: US-2023156213-A1

Title: Spatial displacement vector prediction for intra picture block and string copying

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is a Continuation Application of U.S. Application No. 17/240,567 (filed Apr. 26, 2021), which claims priority based on U.S. Provisional Application No. 63/038,020 (filed Jun. 11, 2020), the entireties of which are incorporated by reference herein. 
    
    
     FIELD 
     This disclosure relates generally to field of data processing, and more particularly to video encoding and decoding. 
     BACKGROUND 
     Block based compensation from a different picture is also known as motion compensation. Similarly, a block compensation can also be done from a previously reconstructed area within the same picture. This is referred as intra picture block compensation, current picture referencing (CPR for short), or intra block copy (IBC for short). 
     SUMMARY 
     Embodiments relate to a method, system, and computer readable medium for video coding. According to one aspect, a method for video coding is provided. The method may include receiving video data including one or more blocks. A current block coded in intra block copy mode is predicted from among the one or more blocks based on a coded block vector or string offset vector corresponding to one or more spatial neighboring or non-neighboring blocks from among the one or more blocks. The video data is decoded based on the predicted current block. 
     According to another aspect, a computer system for video coding is provided. The computer system may include one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, whereby the computer system is capable of performing a method. The method may include receiving video data including one or more blocks. A current block coded in intra block copy mode is predicted from among the one or more blocks based on a coded block vector or string offset vector corresponding to one or more spatial neighboring or non-neighboring blocks from among the one or more blocks. The video data is decoded based on the predicted current block. 
     According to yet another aspect, a computer readable medium for video coding is provided. The computer readable medium may include one or more computer-readable storage devices and program instructions stored on at least one of the one or more tangible storage devices, the program instructions executable by a processor. The program instructions are executable by a processor for performing a method that may accordingly include receiving video data including one or more blocks. A current block coded in intra block copy mode is predicted from among the one or more blocks based on a coded block vector or string offset vector corresponding to one or more spatial neighboring or non-neighboring blocks from among the one or more blocks. The video data is decoded based on the predicted current block. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       These and other objects, features and advantages will become apparent from the following detailed description of illustrative embodiments, which is to be read in connection with the accompanying drawings. The various features of the drawings are not to scale as the illustrations are for clarity in facilitating the understanding of one skilled in the art in conjunction with the detailed description. In the drawings: 
         FIG.  1    illustrates a networked computer environment according to at least one embodiment; 
         FIG.  2 A  is a block diagram depicting intra block copy in a picture, according to at least one embodiment; 
         FIG.  2 B  is a block diagram of intra block compensation with a one coding tree unit (CTU) search range, according to at least one embodiment; 
         FIG.  2 C  is a block diagram of HEVC/VVC spatial merge candidates, according to at least one embodiment; 
         FIG.  2 D  is a block diagram of spatial blocks, according to at least one embodiment; 
         FIG.  3    is an operational flowchart illustrating the steps carried out by a program that encodes and decodes video data based on spatial displacement vectors, according to at least one embodiment; 
         FIG.  4    is a block diagram of internal and external components of computers and servers depicted in  FIG.  1    according to at least one embodiment; 
         FIG.  5    is a block diagram of an illustrative cloud computing environment including the computer system depicted in  FIG.  1   , according to at least one embodiment; and 
         FIG.  6    is a block diagram of functional layers of the illustrative cloud computing environment of  FIG.  5   , according to at least one embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     Detailed embodiments of the claimed structures and methods are disclosed herein; however, it can be understood that the disclosed embodiments are merely illustrative of the claimed structures and methods that may be embodied in various forms. Those structures and methods may, however, be embodied in many different forms and should not be construed as limited to the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete and will fully convey the scope to those skilled in the art. In the description, details of well-known features and techniques may be omitted to avoid unnecessarily obscuring the presented embodiments. 
     Embodiments relate generally to the field of data processing, and more particularly to video encoding and decoding. The following described exemplary embodiments provide a system, method and computer program to, among other things, encode and decode video data based on spatial displacement vectors. Therefore, some embodiments have the capacity to improve the field of computing by allowing for improved video coding based on the use of both spatial neighboring and non-neighboring blocks to a current block in video data. 
     As previously described, block based compensation from a different picture is also known as motion compensation. Similarly, a block compensation can also be done from a previously reconstructed area within the same picture. This is referred as intra picture block compensation, current picture referencing (CPR for short), or intra block copy (IBC for short). However, currently in VVC, the search range of CPR mode is constrained to be within the current CTU. The effective memory requirement to store reference samples for CPR mode is 1 CTU size of samples. Considering the existing reference sample memory to store reconstructed samples in current 64x64 region, 3 more 64x64 sized reference sample memory are required. It may be advantageous, therefore, to extends the effective search range of the CPR mode to some part of the left CTU while the total memory requirement for storing reference pixels are kept unchanged. 
     Aspects are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer readable media according to the various embodiments. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions. 
     The following described exemplary embodiments provide a system, method and computer program that encodes and decodes video data based on spatial displacement vectors. Referring now to  FIG.  1   , a functional block diagram of a networked computer environment illustrating a video coding system  100  (hereinafter “system”) for encoding and decoding video data based on spatial displacement vectors. It should be appreciated that  FIG.  1    provides only an illustration of one implementation and does not imply any limitations with regard to the environments in which different embodiments may be implemented. Many modifications to the depicted environments may be made based on design and implementation requirements. 
     The system  100  may include a computer  102  and a server computer  114 . The computer  102  may communicate with the server computer  114  via a communication network  110  (hereinafter “network”). The computer  102  may include a processor  104  and a software program  108  that is stored on a data storage device  106  and is enabled to interface with a user and communicate with the server computer  114 . As will be discussed below with reference to  FIG.  4    the computer  102  may include internal components  800 A and external components  900 A, respectively, and the server computer  114  may include internal components  800 B and external components  900 B, respectively. The computer  102  may be, for example, a mobile device, a telephone, a personal digital assistant, a netbook, a laptop computer, a tablet computer, a desktop computer, or any type of computing devices capable of running a program, accessing a network, and accessing a database. 
     The server computer  114  may also operate in a cloud computing service model, such as Software as a Service (SaaS), Platform as a Service (PaaS), or Infrastructure as a Service (laaS), as discussed below with respect to  FIGS.  5  and  6   . The server computer  114  may also be located in a cloud computing deployment model, such as a private cloud, community cloud, public cloud, or hybrid cloud. 
     The server computer  114 , which may be used for video coding is enabled to run a Video Coding Program  116  (hereinafter “program”) that may interact with a database  112 . The Video Coding Program method is explained in more detail below with respect to  FIG.  3   . In one embodiment, the computer  102  may operate as an input device including a user interface while the program  116  may run primarily on server computer  114 . In an alternative embodiment, the program  116  may run primarily on one or more computers  102  while the server computer  114  may be used for processing and storage of data used by the program  116 . It should be noted that the program  116  may be a standalone program or may be integrated into a larger video coding program. 
     It should be noted, however, that processing for the program  116  may, in some instances be shared amongst the computers  102  and the server computers  114  in any ratio. In another embodiment, the program  116  may operate on more than one computer, server computer, or some combination of computers and server computers, for example, a plurality of computers  102  communicating across the network  110  with a single server computer  114 . In another embodiment, for example, the program  116  may operate on a plurality of server computers  114  communicating across the network  110  with a plurality of client computers. Alternatively, the program may operate on a network server communicating across the network with a server and a plurality of client computers. 
     The network  110  may include wired connections, wireless connections, fiber optic connections, or some combination thereof. In general, the network  110  can be any combination of connections and protocols that will support communications between the computer  102  and the server computer  114 . The network  110  may include various types of networks, such as, for example, a local area network (LAN), a wide area network (WAN) such as the Internet, a telecommunication network such as the Public Switched Telephone Network (PSTN), a wireless network, a public switched network, a satellite network, a cellular network (e.g., a fifth generation (5G) network, a long-term evolution (LTE) network, a third generation (3G) network, a code division multiple access (CDMA) network, etc.), a public land mobile network (PLMN), a metropolitan area network (MAN), a private network, an ad hoc network, an intranet, a fiber optic-based network, or the like, and/or a combination of these or other types of networks. 
     The number and arrangement of devices and networks shown in  FIG.  1    are provided as an example. In practice, there may be additional devices and/or networks, fewer devices and/or networks, different devices and/or networks, or differently arranged devices and/or networks than those shown in  FIG.  1   . Furthermore, two or more devices shown in  FIG.  1    may be implemented within a single device, or a single device shown in  FIG.  1    may be implemented as multiple, distributed devices. Additionally, or alternatively, a set of devices (e.g., one or more devices) of system  100  may perform one or more functions described as being performed by another set of devices of system  100 . 
     Referring now to  FIG.  2 A , a block diagram depicting intra block copy in a picture  200 A is depicted. The picture  200 A may include a current block  202 A, a reference block  202 B, and a block vector BV. The block vector VB may be a displacement vector that may indicate an offset between the current block  202 A and the reference block  202 B. Different from a motion vector in motion compensation, which can be at any value (positive or negative, at either x or y direction), the block vector BV has a few constraints such that it is ensured that the pointed reference block  202 B is available and already reconstructed. Also, for parallel processing consideration, some reference area that is tile boundary or wavefront ladder shape boundary is also excluded. 
     The coding of a block vector could be either explicit or implicit. In the explicit mode (or referred as AMVP mode in inter coding), the difference between a block vector and its predictor is signaled in the implicit mode, the block vector is recovered purely from its predictor, in a similar way as a motion vector in merge mode. The resolution of a block vector, in some implementations, is restricted to integer positions; in other systems, it may be allowed to point to fractional positions 
     The use of intra block copy at block level, can be signaled using a block level flag, refer as an IBC flag. In one embodiment, this flag is signaled when the current block  202 A is not coded in merge mode. Or it can be signaled by a reference index approach. This is done by treating the current decoded picture as a reference picture. In HEVC SCC, such a reference picture is put in the last position of the list. This special reference picture is also managed together with other temporal reference pictures in the DPB. 
     There are also some variations for intra block copy, such as treating the intra block copy as a third mode, which is different from either intra or inter prediction mode. By doing this, the block vector prediction in merge mode and AMVP mode are separated from regular inter mode. For example, a separate merge candidate list is defined for intra block copy mode, where all the entries in the list are all block vectors. Similarly, the block vector prediction list in intra block copy AMVP mode only consists of block vectors. The general rules applied to both lists are: they may follow the same logic as inter merge candidate list or AMVP predictor list in terms of candidate derivation process. For example, the 5 spatial neighboring locations in HEVC or VVC inter merge mode are accessed for intra block copy to derive its own merge candidate list. 
     Referring now to  FIG.  2 B , a block diagram  200 B of intra block compensation with a one coding tree unit (CTU) search range is depicted. The search may progress through stages 204A-D. Currently in VVC, the search range of CPR mode is constrained to be within the current CTU. The effective memory requirement to store reference samples for CPR mode is 1 CTU size of samples. Considering the existing reference sample memory to store reconstructed samples in current 64x64 region C, 3 more 64x64 sized reference samples S may be used. Accordingly, the effective search range of the CPR mode may be extended to some part of the left CTU while the total memory requirement for storing reference pixels are kept unchanged (1 CTU size, 4 64x64 reference sample memory in total). The bitstream conformance conditions that a valid block vector (mvL, in 1/16 -pel resolution) should follow are listed as follows. For example, the luma motion vector mvL may obey one or more constraints. 
     A1: When the derivation process for block availability as specified in the neighbouring blocks availability checking process is invoked with the current luma location ( xCurr, yCurr ) set equal to ( xCb, yCb ) and the neighbouring luma location ( xCb + (mvL[ 0 ] » 4 ), yCb + (mvL[ 1 ] » 4 ) ) as inputs, and the output shall be equal to TRUE. 
     A2: When the derivation process for block availability as specified in the neighbouring blocks availability checking process is invoked with the current luma location ( xCurr, yCurr ) set equal to ( xCb, yCb ) and the neighbouring luma location ( xCb + (mvL[ 0 ] » 4 ) + cbWidth - 1, yCb + ( mvL[ 1 ] » 4 ) + cbHeight - 1 ) as inputs, and the output shall be equal to TRUE. 
     B1: One or both the following conditions shall be true. The value of ( mvL[ 0 ] » 4 ) + cbWidth is less than or equal to 0. The value of ( mvL[ 1 ] » 4 ) + cbHeight is less than or equal to 0. 
     C1: The following conditions shall be true:
     ( yCb + (mvL[ 1 ] » 4 ) ) » CtbLog2SizeY = yCb » CtbLog2SizeY   ( yCb + (mvL[ 1 ] » 4 ) + cbHeight - 1) » CtbLog2SizeY = yCb » CtbLog2SizeY   ( xCb + (mvL[ 0 ] » 4 ) ) » CtbLog2SizeY &gt;= ( xCb » CtbLog2SizeY ) - 1   ( xCb + (mvL[ 0 ] » 4 ) + cbWidth - 1) » CtbLog2SizeY &lt;= ( xCb » CtbLog2SizeY )   

     C2: When ( xCb + (mvL[ 0 ] » 4 ) ) » CtbLog2SizeY is equal to ( xCb » CtbLog2SizeY ) - 1, the derivation process for block availability as specified in the neighbouring blocks availability checking process is invoked with the current luma location( xCurr, yCurr ) set equal to ( xCb, yCb ) and the neighbouring luma location ( ( ( xCb + (mvL[ 0 ] » 4 ) + CtbSizeY ) » ( CtbLog2SizeY - 1 ) ) « ( CtbLog2SizeY - 1 ), ( ( yCb + (mvL[ 1 ] » 4 ) ) » ( CtbLog2SizeY - 1 ) ) « ( CtbLog2SizeY - 1 ) ) as inputs, and the output shall be equal to FALSE. 
     Referring now to  FIG.  2 C , a block diagram  200 C of HEVC/VVC spatial merge candidates is depicted. The five spatial merge candidates for HEVC and VVC may include A0, A1, B0, B1, and B2. The order of forming a candidate list from these positions may be A0-&gt;B0-&gt;B1-&gt;A1-&gt;B2. 
     History-based MVP (HMVP) merge candidates are added to merge list after the spatial MVP and TMVP. In this method, the motion information of a previously coded block is stored in a table and used as MVP for the current CU. The table with multiple HMVP candidates is maintained during the encoding/decoding process. The table is reset (emptied) when a new CTU row is encountered. Whenever there is a non-subblock inter-coded CU, the associated motion information is added to the last entry of the table as a new HMVP candidate. 
     In VTM3 the HMVP table size S is set to be 6, which indicates up to 6 History-based MVP (HMVP) candidates may be added to the table. When inserting a new motion candidate to the table, a constrained first-in-first-out (FIFO) rule is utilized wherein redundancy check is firstly applied to find whether there is an identical HMVP in the table. If found, the identical HMVP is removed from the table and all the HMVP candidates afterwards are moved forward. 
     HMVP candidates could be used in the merge candidate list construction process. The latest several HMVP candidates in the table are checked in order and inserted to the candidate list after the TMVP candidate. Redundancy check is applied on the HMVP candidates to the spatial or temporal merge candidate. 
     To reduce the number of redundancy check operations, one or more simplifications are introduced. A number of HMVP candidates is used for merge list generation is set as (N &lt;= 4) ? M: (8 - N), wherein N indicates number of existing candidates in the merge list and M indicates number of available HMVP candidates in the table. Once the total number of available merge candidates reaches the maximally allowed merge candidates minus 1, the merge candidate list construction process from HMVP is terminated. 
     When intra block copy operates as a separate mode from inter mode, a separate history buffer, referred as HBVP, will be used for storing previously coded intra block copy block vectors. 
     As a separate mode from inter prediction, it is desirable to have a simplified block vector derivation process for intra block copy mode. A similar history-based block vector predictor buffer can be used to perform BV prediction. In the following, some information is provided for some specific usage of such a HBVP. 
     A HBVP buffer is established to record the previously IBC coded blocks’ BV information, including some other side information such as block size, block location, etc. 
     Based on the recorded information, for each current block, BVs in the HBVP that meet the following conditions are classified into corresponding categories:
     Class 0: The area of coded block (width * height) is greater than or equal to the threshold (64 pixels);   Class 1: The frequency of the BV is greater than or equal to 2;   Class 2: The coded block coordinates (upper left corner) are to the left of the current block;   Class 3: The coded block coordinates (upper left corner) are above the current block;   Class 4: The coded block coordinates (upper left corner) are at the upper left side of the current block;   Class 5: The coded block coordinates (upper left corner) are at the top right side of the current block;   Class 6: The coded block coordinates (upper left corner) are at the bottom left side of the current block.   

     For each category, the BV of the most recently coded block is derived as the BV predictor candidate. A CBVP list is constructed by appending the BV predictor of each category in the order from 0 to 6. 
     A coded block may be divided into several continuous strings, each of which is followed by the next string along a scan order. The scan order can be raster scan or traverse scan. For each string, an string offset vector (SV) and the length of the string are signalled. The SV is used to indicate where the reference string is from in the reference area. The length is used to indicate how long the current/reference string is. If a sample in the current block cannot find its match in the reference area, an escape sample is signaled, and its value is coded directly. 
     Referring now to  FIG.  2 D , a block diagram  200 D of spatial blocks is depicted. The spatial blocks may include spatial neighboring blocks A0-E0 and spatial non-adjacent blocks A1-E1, A2-E2, and A3-E3. Vector prediction includes both block vector prediction for IBC mode and SV prediction for string matching mode, and the prediction can refer to skip mode, direct/merge mode or vector prediction with difference coding. Spatial neighboring blocks A0-E0 may refer to already coded blocks that are next to a current block. The other positions along the top row or left column to the current block may also be considered as spatial neighboring positions. Spatial non-neighboring blocks A1-E1, A2-E2, and A3-E3, on the contrary, refer to the previously coded blocks that are not spatial neighboring blocks (those can be found along the top row or left column to the current block). 
     According to one or more embodiments, a coded BV or SV in spatial neighboring or spatial non-neighboring blocks may be used to predict a current block coded in IBC mode. In one embodiment, only spatial non-neighboring blocks coded either in IBC mode or string matching mode are considered as candidates to predict the BV of the current block coded in IBC mode. In another embodiment, only spatial non-neighboring blocks coded in IBC mode are considered as candidates to predict the BV of the current block coded in IBC mode. Both spatial neighboring blocks and spatial non-neighboring blocks coded in string matching mode are considered as candidates to predict the BV of the current block coded in IBC mode. 
     According to one or more embodiments, a coded BV or SV in spatial neighboring or spatial non-neighboring blocks may be used to predict a current block coded in string matching mode. In one embodiment, only spatial non-neighboring blocks coded either in IBC mode or string matching mode are considered as candidate to predict the SV of the current block coded in string matching mode. In another embodiment, spatial neighboring blocks coded either in IBC mode or string matching mode are considered as candidates to predict the SV of the current block coded in string matching mode. In another embodiment, both BV and SV in spatial neighboring blocks and spatial non-neighboring blocks coded either in IBC mode or string matching mode are considered as candidates to predict the SV of the current block coded in string matching mode. 
     According to one or more embodiments, the above-discussed spatial candidates for BV or SV prediction can be put in front of a history-based BV or SV candidates in a BV or SV predictor list. Or, the above-discussed spatial candidates for BV or SV prediction can be put after a history-based BV or SV candidates in a BV or SV predictor list. When class based prediction is used, as is mentioned in the Introduction part, putting a spatial neighboring or non-neighboring block into the list may require the associated location and size information with the candidates. With the information, a new spatial candidate may be able to put into the right class of predictors. Therefore, the information is also needed for storing each of spatial neighboring or spatial non-neighboring blocks, in addition to the BV or SV information. 
     According to one or more embodiments, when putting several spatial candidates into a prediction list, some order is followed to access the designated spatial locations. For example, to predict an SV in string matching mode with only spatial non-neighboring blocks are considered. Then locations A1, B1, C1, D1, E1 may be accessed in order. If one of the blocks is coded in either IBC or string matching mode. The vector (either BV or SV) associated with the block may be used to predict the SV in the current block. Similar examples can be derived for prediction a BV in IBC coded current block. 
     Referring now to  FIG.  3   , an operational flowchart illustrating the steps of a method  300  carried out by a program that encodes and decodes video data based on spatial displacement vectors is depicted. 
     At  302 , the method  300  may include receiving video data including one or more blocks. 
     At  304 , the method  300  may include predicting a displacement vector of a current block coded in intra block copy mode or string matching mode from among the one or more blocks based on a coded block vector or a string offset vector corresponding to one or more spatial neighboring or non-neighboring blocks from among the one or more blocks. 
     At  306 , the method  300  may include decoding the video data based on the predicted displacement vector of the current block. 
     It may be appreciated that  FIG.  3    provides only an illustration of one implementation and does not imply any limitations with regard to how different embodiments may be implemented. Many modifications to the depicted environments may be made based on design and implementation requirements. 
       FIG.  4    is a block diagram  400  of internal and external components of computers depicted in  FIG.  1    in accordance with an illustrative embodiment. It should be appreciated that  FIG.  4    provides only an illustration of one implementation and does not imply any limitations with regard to the environments in which different embodiments may be implemented. Many modifications to the depicted environments may be made based on design and implementation requirements. 
     Computer  102  ( FIG.  1   ) and server computer  114  ( FIG.  1   ) may include respective sets of internal components  800 A,B and external components  900 A,B illustrated in  FIG.  5   . Each of the sets of internal components  800  include one or more processors  820 , one or more computer-readable RAMs  822  and one or more computer-readable ROMs  824  on one or more buses  826 , one or more operating systems  828 , and one or more computer-readable tangible storage devices  830 . 
     Processor  820  is implemented in hardware, firmware, or a combination of hardware and software. Processor  820  is a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), a microprocessor, a microcontroller, a digital signal processor (DSP), a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or another type of processing component. In some implementations, processor  820  includes one or more processors capable of being programmed to perform a function. Bus  826  includes a component that permits communication among the internal components  800 A,B. 
     The one or more operating systems  828 , the software program  108  ( FIG.  1   ) and the Video Coding Program  116  ( FIG.  1   ) on server computer  114  ( FIG.  1   ) are stored on one or more of the respective computer-readable tangible storage devices  830  for execution by one or more of the respective processors  820  via one or more of the respective RAMs  822  (which typically include cache memory). In the embodiment illustrated in  FIG.  4   , each of the computer-readable tangible storage devices  830  is a magnetic disk storage device of an internal hard drive. Alternatively, each of the computer-readable tangible storage devices  830  is a semiconductor storage device such as ROM  824 , EPROM, flash memory, an optical disk, a magneto-optic disk, a solid state disk, a compact disc (CD), a digital versatile disc (DVD), a floppy disk, a cartridge, a magnetic tape, and/or another type of non-transitory computer-readable tangible storage device that can store a computer program and digital information. 
     Each set of internal components  800 A,B also includes a R/W drive or interface  832  to read from and write to one or more portable computer-readable tangible storage devices  936  such as a CD-ROM, DVD, memory stick, magnetic tape, magnetic disk, optical disk or semiconductor storage device. A software program, such as the software program  108  ( FIG.  1   ) and the Video Coding Program  116  ( FIG.  1   ) can be stored on one or more of the respective portable computer-readable tangible storage devices  936 , read via the respective R/W drive or interface  832  and loaded into the respective hard drive  830 . 
     Each set of internal components  800 A,B also includes network adapters or interfaces  836  such as a TCP/IP adapter cards; wireless Wi-Fi interface cards; or 3G, 4G, or 5G wireless interface cards or other wired or wireless communication links. The software program  108  ( FIG.  1   ) and the Video Coding Program  116  ( FIG.  1   ) on the server computer  114  ( FIG.  1   ) can be downloaded to the computer  102  ( FIG.  1   ) and server computer  114  from an external computer via a network (for example, the Internet, a local area network or other, wide area network) and respective network adapters or interfaces  836 . From the network adapters or interfaces  836 , the software program  108  and the Video Coding Program  116  on the server computer  114  are loaded into the respective hard drive  830 . The network may comprise copper wires, optical fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. 
     Each of the sets of external components  900 A,B can include a computer display monitor  920 , a keyboard  930 , and a computer mouse  934 . External components  900 A,B can also include touch screens, virtual keyboards, touch pads, pointing devices, and other human interface devices. Each of the sets of internal components  800 A,B also includes device drivers  840  to interface to computer display monitor  920 , keyboard  930  and computer mouse  934 . The device drivers  840 , R/W drive or interface  832  and network adapter or interface  836  comprise hardware and software (stored in storage device  830  and/or ROM  824 ). 
     It is understood in advance that although this disclosure includes a detailed description on cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, some embodiments are capable of being implemented in conjunction with any other type of computing environment now known or later developed. 
     Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models. 
     Characteristics are as follows: 
     On-demand self-service: a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with the service’s provider. 
     Broad network access: capabilities are available over a network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs). 
     Resource pooling: the provider’s computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter). 
     Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time. 
     Measured service: cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported providing transparency for both the provider and consumer of the utilized service. 
     Service Models are as follows: 
     Software as a Service (SaaS): the capability provided to the consumer is to use the provider’s applications running on a cloud infrastructure. The applications are accessible from various client devices through a thin client interface such as a web browser (e.g., web-based e-mail). The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings. 
     Platform as a Service (PaaS): the capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages and tools supported by the provider. The consumer does not manage or control the underlying cloud infrastructure including networks, servers, operating systems, or storage, but has control over the deployed applications and possibly application hosting environment configurations. 
     Infrastructure as a Service (laaS): the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls). 
     Deployment Models are as follows: 
     Private cloud: the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises. 
     Community cloud: the cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises. 
     Public cloud: the cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services. 
     Hybrid cloud: the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds). 
     A cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure comprising a network of interconnected nodes. 
     Referring to  FIG.  5   , illustrative cloud computing environment  500  is depicted. As shown, cloud computing environment  500  comprises one or more cloud computing nodes  10  with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone  54 A, desktop computer  54 B, laptop computer  54 C, and/or automobile computer system  54 N may communicate. Cloud computing nodes  10  may communicate with one another. They may be grouped (not shown) physically or virtually, in one or more networks, such as Private, Community, Public, or Hybrid clouds as described hereinabove, or a combination thereof. This allows cloud computing environment  500  to offer infrastructure, platforms and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device. It is understood that the types of computing devices  54 A-N shown in  FIG.  5    are intended to be illustrative only and that cloud computing nodes  10  and cloud computing environment  500  can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser). 
     Referring to  FIG.  6   , a set of functional abstraction layers  600  provided by cloud computing environment  500  ( FIG.  5   ) is shown. It should be understood in advance that the components, layers, and functions shown in  FIG.  6    are intended to be illustrative only and embodiments are not limited thereto. As depicted, the following layers and corresponding functions are provided: 
     Hardware and software layer  60  includes hardware and software components. Examples of hardware components include: mainframes  61 ; RISC (Reduced Instruction Set Computer) architecture based servers  62 ; servers  63 ; blade servers  64 ; storage devices  65 ; and networks and networking components  66 . In some embodiments, software components include network application server software  67  and database software  68 . 
     Virtualization layer  70  provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers  71 ; virtual storage  72 ; virtual networks  73 , including virtual private networks; virtual applications and operating systems  74 ; and virtual clients  75 . 
     In one example, management layer  80  may provide the functions described below. Resource provisioning  81  provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. Metering and Pricing  82  provide cost tracking as resources are utilized within the cloud computing environment, and billing or invoicing for consumption of these resources. In one example, these resources may comprise application software licenses. Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources. User portal  83  provides access to the cloud computing environment for consumers and system administrators. Service level management  84  provides cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment  85  provide pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA. 
     Workloads layer  90  provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation  91 ; software development and lifecycle management  92 ; virtual classroom education delivery  93 ; data analytics processing  94 ; transaction processing  95 ; and Video Coding  96 . Video Coding  96  may encode and decode video data based on spatial displacement vectors. 
     Some embodiments may relate to a system, a method, and/or a computer readable medium at any possible technical detail level of integration. The computer readable medium may include a computer-readable non-transitory storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out operations. 
     The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. 
     Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device. 
     Computer readable program code/instructions for carrying out operations may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user’s computer, partly on the user’s computer, as a stand-alone software package, partly on the user’s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user’s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects or operations. 
     These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks. 
     The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer readable media according to various embodiments. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). The method, computer system, and computer readable medium may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in the Figures. In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be executed concurrently or substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions. 
     It will be apparent that systems and/or methods, described herein, may be implemented in different forms of hardware, firmware, or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems and/or methods is not limiting of the implementations. Thus, the operation and behavior of the systems and/or methods were described herein without reference to specific software code-it being understood that software and hardware may be designed to implement the systems and/or methods based on the description herein. 
     No element, act, or instruction used herein should be construed as critical or essential unless explicitly described as such. Also, as used herein, the articles “a” and “an” are intended to include one or more items, and may be used interchangeably with “one or more.” Furthermore, as used herein, the term “set” is intended to include one or more items (e.g., related items, unrelated items, a combination of related and unrelated items, etc.), and may be used interchangeably with “one or more.” Where only one item is intended, the term “one” or similar language is used. Also, as used herein, the terms “has,” “have,” “having,” or the like are intended to be open-ended terms. Further, the phrase “based on” is intended to mean “based, at least in part, on” unless explicitly stated otherwise. 
     The descriptions of the various aspects and embodiments have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Even though combinations of features are recited in the claims and/or disclosed in the specification, these combinations are not intended to limit the disclosure of possible implementations. In fact, many of these features may be combined in ways not specifically recited in the claims and/or disclosed in the specification. Although each dependent claim listed below may directly depend on only one claim, the disclosure of possible implementations includes each dependent claim in combination with every other claim in the claim set. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.