Bi-directional optical flow method with simplified gradient derivation

Abstract

To provide a video coding apparatus for bi-directional optical flow (BDOF).SOLUTION: The video coding device may be configured to perform a directional BDOF refinement on a coding unit (CU). The apparatus may determine a direction in which to perform a directional BDOF refinement. The apparatus may calculate a vertical gradient difference and a horizontal gradient difference for the CU. The vertical gradient difference can indicate a difference between the vertical gradient for the first reference picture and the vertical gradient for the second reference picture. The horizontal direction gradient difference can indicate a difference between the horizontal gradient for the first reference picture and the horizontal gradient for the second reference picture. The video coding device may determine the direction of performing directional BDOF refinement based on the vertical gradient difference and the horizontal gradient difference. The video coding device may perform directional BDOF refinement in the determined direction.SELECTED DRAWING: Figure 12

Description

[Technical Field]

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 62 / 653,674, filed April 6, 2018, the contents of which are incorporated herein by reference. [Background technology]

[0002] Video coding systems are widely used to compress digital video signals to reduce the storage requirements and / or transmission bandwidth of such signals. Video coding systems such as block-based systems, wavelet-based systems, and object-based systems, as well as hybrid block-based video coding systems, are widely used and deployed. Examples of block-based video coding systems may include international video coding standards such as MPEG1 / 2 / 4 part 2, H.264 / MPEG-4 part 10, AVC, VC-1, and High Efficiency Video Coding (HEVC). Summary of the Invention

[0003] A video encoding device may be configured to perform directional bidirectional optical flow (BDOF) refinement on a coding unit (CU). The video encoding device may be or may include an encoder and / or a decoder. Video encoding may also be referred to as encoding and / or decoding. The device may determine a direction in which to perform the directional BDOF refinement. The device may calculate a vertical gradient difference and a horizontal gradient difference for the CU. The vertical gradient difference may indicate a difference between a vertical gradient for a first reference picture and a vertical gradient for a second reference picture. The horizontal gradient difference may indicate a difference between a horizontal gradient for the first reference picture and a horizontal gradient for the second reference picture. The video encoding device may determine a direction in which to perform the directional BDOF refinement based on the vertical gradient difference and the horizontal gradient difference. The video encoding device may perform the directional BDOF refinement in the determined direction. For example, directional BDOF refinement may include performing BDOF refinement in the vertical direction or performing BDOF refinement in the horizontal direction.

[0004] The video encoding device may be configured to determine a direction in which directional BDOF refinement is performed. As described herein, the direction in which directional BDOF refinement is performed may be based on a vertical gradient difference associated with a CU and a horizontal gradient difference associated with the CU. The video encoding device may compare the gradient difference with a threshold (e.g., a first threshold and / or a second threshold). The video encoding device may perform directional BDOF refinement in the vertical direction if the vertical gradient difference associated with the CU is greater than the first threshold. The video encoding device may perform directional BDOF refinement in the horizontal direction if the horizontal gradient difference associated with the CU is greater than the second threshold. The first and second thresholds may be variable, static (e.g., pre-configured), or quasi-static. For example, the first and second thresholds may be variable, the first threshold may be or include a horizontal gradient difference, and the second threshold may be or include a vertical gradient difference.

[0005] The video encoding device may be configured to determine whether to perform BDOF refinement on a CU, which may include performing directional BDOF refinement in the vertical direction, performing directional BDOF refinement in the horizontal direction, or performing BDOF refinement in the horizontal and vertical directions. The video encoding device may be configured to determine whether to perform BDOF refinement on a CU based on one or more characteristics associated with the CU. The video encoding device may be configured to determine whether to perform BDOF refinement based on an inter coding mode associated with the CU and / or a size associated with the CU. For example, the video encoding device may determine to skip BDOF refinement if the inter coding mode associated with the CU supports sub-CU prediction.

[0006] The video encoding device may be configured to determine to perform BDOF refinement on the CU. The video encoding device may identify a motion vector associated with a reference CU for the CU. The motion vector may include one or more motion components (e.g., a first motion component and a second motion component). The motion components may include integer motion components or non-integer (e.g., fractional) motion components. For example, the motion components may include fractional motion components. The device may calculate a directional gradient associated with the CU, for example, by applying a gradient filter to reference samples at integer positions of the reference CU. For example, if the motion components include fractional motion components, the video encoding device may identify integer positions corresponding to the fractional motion components. The video encoding device may apply a gradient filter to reference samples at integer positions of the reference CU in a first direction. For example, one or more reference sample(s) at integer positions associated with the reference CU may approximate their corresponding sample(s) at fractional positions within the reference CU. The directional gradient associated with the CU may be used to calculate a vertical gradient difference for the CU or a horizontal gradient difference associated with the CU. [Brief explanation of the drawings]

[0007] [Figure 1A] 1 is a system diagram illustrating an example communication system in which one or more disclosed embodiments may be implemented. [Figure 1B] 1B is a system diagram illustrating an example wireless transmit / receive unit (WTRU) that may be used within the communication system shown in FIG. 1A, according to an embodiment. [Figure 1C] 1B is a system diagram illustrating an example radio access network (RAN) and an example core network (CN) that can be used within the communication system shown in FIG. 1A, according to an embodiment. [Figure 1D] 1B is a system diagram illustrating a further exemplary RAN and a further exemplary CN that may be used within the communication system illustrated in FIG. 1A, according to an embodiment. [Figure 2] 1 shows a block diagram of a video encoder. [Figure 3] 1 shows a block diagram of a video decoder. [Figure 4] An embodiment associated with bidirectional optical flow (BDOF) is shown. [Figure 5A] An example of gradient derivation in BDOF with 1 / 16 pixel (pel) motion accuracy is shown. [Figure 5B] An example of gradient derivation in BDOF with 1 / 16 pixel (pel) motion accuracy is shown. [Figure 6A] 10 illustrates an example of memory access for BDOF without a block extension constraint. [Figure 6B] An example of memory access in BDOF with block extension constraints will be described. [Figure 7] 1 illustrates an embodiment of Advanced Temporal Motion Vector Prediction (ATMVP). [Figure 8] 1 illustrates an example of spatial-temporal motion vector prediction (STMVP). [Figure 9A] An example of frame rate up-conversion (FRUC) using template matching is shown. [Figure 9B] An example of FRUC using bilateral matching is shown below. [Figure 10A] 1 shows a diagram of an affine mode and a simplified affine model. [Figure 10B] 1 shows an illustration of affine modes and sub-block level motion derivation for affine blocks. [Figure 11] 1 shows a diagram of BDOF refinement for a prediction unit (PU). [Figure 12] An illustration of directional BDOF refinement is shown. DETAILED DESCRIPTION OF THE INVENTION

[0008] 1A illustrates an exemplary communication system 100 in which one or more disclosed embodiments may be implemented. The communication system 100 may be a multiple-access system that provides content, such as voice, data, video, messaging, broadcast, etc., to multiple wireless users. The communication system 100 may enable the multiple wireless users to access such content through sharing of system resources, including wireless bandwidth. For example, the communication system 100 may utilize one or more channel access methods, such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal FDMA (OFDMA), single-carrier FDMA (SC-FDMA), zero-tailed unique word discrete Fourier transform spread OFDM (ZT UW DTS-S-OFDM), unique word OFDM (UW-OFDM), resource block filtered OFDM, and filter bank multicarrier (FBMC).

[0009] 1A illustrates an exemplary communication system 100 in which one or more disclosed embodiments may be implemented. The communication system 100 may be a multiple-access system that provides content, such as voice, data, video, messaging, broadcast, etc., to multiple wireless users. The communication system 100 may enable the multiple wireless users to access such content through sharing of system resources, including wireless bandwidth. For example, the communication system 100 may utilize one or more channel access methods, such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal FDMA (OFDMA), single-carrier FDMA (SC-FDMA), zero-tailed unique word discrete Fourier transform spread OFDM (ZT UW DTS-S-OFDM), unique word OFDM (UW-OFDM), resource block filtered OFDM, and filter bank multicarrier (FBMC).

[0010] 1A, communications system 100 may include wireless transmit / receive units (WTRUs) 102a, 102b, 102c, 102d, RAN 104 / 113, CN 106, public switched telephone network (PSTN) 108, Internet 110, and other networks 112, although it will be appreciated that the disclosed embodiments contemplate any number of WTRUs, base stations, networks, and / or network elements. Each of WTRUs 102a, 102b, 102c, 102d may be any type of device configured to operate and / or communicate in a wireless environment. By way of example, the WTRUs 102a, 102b, 102c, 102d, any of which may be referred to as a “station” and / or “STA,” may be configured to transmit and / or receive wireless signals and may include user equipment (UE), mobile stations, fixed or mobile subscriber units, subscription-based units, pagers, cellular phones, personal digital assistants (PDAs), smartphones, laptops, netbooks, personal computers, wireless sensors, hotspot or Mi-Fi devices, Internet of Things (IoT) devices, watches or other wearables, head-mounted displays (HMDs), vehicles, drones, medical devices and applications (e.g., remote surgery), industrial devices and applications (e.g., robots and / or other wireless devices operating in industrial and / or automated processing chain situations), consumer electronics devices, and devices operating on commercial and / or industrial wireless networks. Any of the WTRUs 102a, 102b, 102c, 102d may be referred to interchangeably as a UE.

[0011] The communications system 100 may also include a base station 114a and / or a base station 114b. Each of the base stations 114a, 114b may be any type of device configured to wirelessly interface with at least one of the WTRUs 102a, 102b, 102c, 102d to facilitate access to one or more communications networks, such as the CN 106, the Internet 110, and / or other networks 112. By way of example, the base stations 114a, 114b may be a base transceiver station (BTS), a NodeB, an eNodeB, a Home NodeB, a Home eNodeB, a gNB, an NR NodeB, a site controller, an access point (AP), a wireless router, etc. Although the base stations 114a, 114b are each depicted as a single element, it will be understood that the base stations 114a, 114b may include any number of interconnected base stations and / or network elements.

[0012] The base station 114a may be part of the RAN 104 / 113, which may also include other base stations and / or network elements (not shown), such as a base station controller (BSC), a radio network controller (RNC), relay nodes, etc. The base station 114a and / or base station 114b may be configured to transmit and / or receive wireless signals on one or more carrier frequencies, which may be referred to as a cell (not shown). These frequencies may be in the licensed spectrum, the unlicensed spectrum, or a combination of the licensed and unlicensed spectrum. A cell may provide coverage for wireless services in a particular geographic area, which may be relatively fixed or may change over time. A cell may be further divided into cell sectors. For example, the cell associated with the base station 114a may be divided into three sectors. Thus, in one embodiment, the base station 114a may include three transceivers, one for each sector of the cell. In an embodiment, the base station 114a may utilize multiple-input multiple-output (MIMO) technology and may utilize multiple transceivers for each sector of the cell. For example, beamforming may be used to transmit and / or receive signals in desired spatial directions.

[0013] The base stations 114a, 114b may communicate with one or more of the WTRUs 102a, 102b, 102c, 102d over the air interface 116, which may be any suitable wireless communication link (e.g., radio frequency (RF), microwave, centimeter wave, micrometer wave, infrared (IR), ultraviolet (UV), visible light, etc.). The air interface 116 may be established using any suitable radio access technology (RAT).

[0014] More specifically, as described above, the communication system 100 may be a multiple-access system and may employ one or more channel access schemes, such as CDMA, TDMA, FDMA, OFDMA, and SC-FDMA. For example, the base station 114a and the WTRUs 102a, 102b, and 102c in the RAN 104 / 113 may establish the air interface 116 using Wideband CDMA (WCDMA) or may implement a radio technology such as Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access (UTRA). WCDMA may include communication protocols such as High Speed ​​Packet Access (HSPA) and / or Evolved HSPA (HSPA+). HSPA may include High Speed ​​Downlink (DL) Packet Access (HSDPA) and / or High Speed ​​Uplink (UL) Packet Access (HSUPA).

[0015] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as Evolved UMTS Terrestrial Radio Access (E-UTRA), which may establish the air interface 116 using Long Term Evolution (LTE), and / or LTE Advanced (LTE-A), and / or LTE Advanced Pro (LTE-A Pro).

[0016] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as New Radio (NR) radio access, which may establish the air interface 116 using NR.

[0017] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement multiple radio access technologies. For example, the base station 114a and the WTRUs 102a, 102b, 102c may implement both LTE radio access and NR radio access, e.g., using a dual connectivity (DC) principle. Thus, the air interface utilized by the WTRUs 102a, 102b, 102c may be characterized by multiple types of radio access technologies and / or transmissions sent to / from multiple types of base stations (e.g., eNBs and gNBs).

[0018] In other embodiments, the base station 114a and the WTRUs 102a, 102b, 102c may implement a wireless technology such as IEEE 802.11 (i.e., Wireless Fidelity (WiFi)), IEEE 802.16 (i.e., Worldwide Interoperability for Microwave Access (WiMAX)), CDMA2000, CDMA2000 1X, CDMA2000 EV-DO, Interim Standard 2000 (IS-2000), Interim Standard 95 (IS-95), Interim Standard 856 (IS-856), Global System for Mobile Communications (GSM), Enhanced Data Rates for GSM Evolution (EDGE), and GSM EDGE (GERAN).

[0019] 1A may be, for example, a wireless router, a Home NodeB, a Home eNodeB, or an access point and may utilize any suitable RAT to facilitate wireless connectivity in a localized area, such as a business, a home, a vehicle, a campus, an industrial facility, an air corridor (e.g., used by drones), and a roadway. In one embodiment, the base station 114b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.11 to establish a wireless local area network (WLAN). In an embodiment, the base station 114b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.15 to establish a wireless personal area network (WPAN). In yet another embodiment, the base station 114b and the WTRUs 102c, 102d may utilize a cellular-based RAT (e.g., WCDMA, CDMA2000, GSM, LTE, LTE-A, LTE-A Pro, NR, etc.) to establish a picocell or femtocell. 1A, the base station 114b may have a direct connection to the Internet 110. Therefore, the base station 114b may not need to access the Internet 110 through the CN 106.

[0020] The RAN 104 / 113 may communicate with the CN 106 / 115, which may be any type of network configured to provide voice, data, application, and / or Voice over Internet Protocol (VoIP) services to one or more of the WTRUs 102a, 102b, 102c, 102d. The data may have various quality of service (QoS) requirements, such as different throughput, delay, error resilience, reliability, data throughput, and mobility requirements. The CN 106 / 115 may provide call control, billing services, mobile location-based services, prepaid calling, Internet connectivity, video distribution, etc., and / or perform high-level security functions, such as user authentication. Although not shown in FIG. 1A , it will be understood that the RAN 104 / 113 and / or the CN 106 / 115 may communicate directly or indirectly with other RANs that utilize the same RAT as the RAN 104 / 113 or a different RAT. For example, in addition to being connected to the RAN 104 / 113, which may utilize NR radio technology, the CN 106 / 115 may also communicate with another RAN (not shown) that utilizes GSM, UMTS, CDMA2000, WiMAX, E-UTRA, or WiFi radio technology.

[0021] The CN 106 / 115 may also serve as a gateway for the WTRUs 102a, 102b, 102c, 102d to access the PSTN 108, the Internet 110, and / or other networks 112. The PSTN 108 may include a circuit-switched telephone network providing plain old telephone service (POTS). The Internet 110 may include a global system of interconnected computer networks and devices that use common communication protocols, such as Transmission Control Protocol (TCP), User Datagram Protocol (UDP), and / or Internet Protocol (IP) in the TCP / IP Internet protocol suite. The network 112 may include wired and / or wireless communication networks owned and / or operated by other service providers. For example, the network 112 may include another CN connected to one or more RANs that may utilize the same RAT as the RAN 104 / 113 or a different RAT.

[0022] Some or all of the WTRUs 102a, 102b, 102c, 102d in communication system 100 may include multi-mode capabilities (e.g., WTRUs 102a, 102b, 102c, 102d may include multiple transceivers for communicating with different wireless networks over different wireless links.) For example, WTRU 102c shown in FIG. 1A may be configured to communicate with base station 114a, which may employ cellular-based wireless technology, and with base station 114b, which may utilize IEEE 802.11 wireless technology.

[0023] 1B is a system diagram illustrating an example WTRU 102. As shown in FIG. 1B, the WTRU 102 may include, among other things, a processor 118, a transceiver 120, a transmit / receive element 122, a speaker / microphone 124, a keypad 126, a display / touchpad 128, non-removable memory 130, removable memory 132, a power source 134, a global positioning system (GPS) chipset 136, and / or other peripherals 138. It will be understood that the WTRU 102 may include any subcombination of the above elements while remaining consistent with an embodiment.

[0024] The processor 118 may be a general-purpose processor, a special-purpose processor, a conventional processor, a digital signal processor (DSP), multiple microprocessors, one or more microprocessors in conjunction with a DSP core, a controller, a microcontroller, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) circuit, any other type of integrated circuit (IC), a state machine, etc. The processor 118 may perform signal coding, data processing, power control, input / output processing, and / or any other functionality that enables the WTRU 102 to operate in a wireless environment. The processor 118 may be coupled to the transceiver 120, which may be coupled to the transmit / receive element 122. While FIG. 1B depicts the processor 118 and the transceiver 120 as separate components, it will be understood that the processor 118 and the transceiver 120 may be integrated together in an electronic package or chip.

[0025] The transmit / receive element 122 may be configured to transmit signals to or receive signals from a base station (e.g., base station 114a) over the air interface 116. For example, in one embodiment, the transmit / receive element 122 may be an antenna configured to transmit and / or receive RF signals. In an embodiment, the transmit / receive element 122 may be an emitter / detector configured to transmit and / or receive IR, UV, or visible light signals, for example. In yet another embodiment, the transmit / receive element 122 may be configured to transmit and / or receive both RF and light signals. It will be understood that the transmit / receive element 122 may be configured to transmit and / or receive any combination of wireless signals.

[0026] 1B, the transmit / receive element 122 is depicted as a single element, the WTRU 102 may include any number of transmit / receive elements 122. More specifically, the WTRU 102 may utilize MIMO technology. Thus, in one embodiment, the WTRU 102 may include two or more transmit / receive elements 122 (e.g., multiple antennas) for transmitting and receiving wireless signals over the air interface 116.

[0027] The transceiver 120 may be configured to modulate signals to be transmitted by the transmit / receive element 122 and demodulate signals received by the transmit / receive element 122. As mentioned above, the WTRU 102 may have multi-mode capabilities. Thus, the transceiver 120 may include multiple transceivers to enable the WTRU 102 to communicate via multiple RATs, such as, for example, NR and IEEE 802.11.

[0028] The processor 118 of the WTRU 102 may be coupled to and may receive user input data from a speaker / microphone 124, a keypad 126, and / or a display / touchpad 128 (e.g., a liquid crystal display (LCD) display unit or an organic light emitting diode (OLED) display unit). The processor 118 may output user data to the speaker / microphone 124, the keypad 126, and / or the display / touchpad 128. Additionally, the processor 118 may obtain information from and store data in any type of suitable memory, such as non-removable memory 130 and / or removable memory 132. The non-removable memory 130 may include random access memory (RAM), read-only memory (ROM), a hard disk, or any other type of memory storage device. The removable memory 132 may include a subscriber identity module (SIM) card, a memory stick, a secure digital (SD) memory card, etc. In other embodiments, the processor 118 may access information from, and store data in, memory that is not physically located on the WTRU 102, such as located on a server or home computer (not shown).

[0029] The processor 118 may receive power from the power source 134 and may be configured to distribute and / or control the power to other components within the WTRU 102. The power source 134 may be any suitable device for powering the WTRU 102. For example, the power source 134 may include one or more dry batteries (e.g., nickel-cadmium (NiCd), nickel-zinc (NiZn), nickel-metal hydride (NiMH), lithium-ion (Li-ion), etc.), solar cells, fuel cells, etc.

[0030] The processor 118 may also be coupled to a GPS chipset 136, which may be configured to provide location information (e.g., longitude and latitude) regarding the current location of the WTRU 102. In addition to, or instead of, information from the GPS chipset 136, the WTRU 102 may receive location information over the air interface 116 from base stations (e.g., base stations 114a, 114b) and / or may determine its location based on the timing of signals received from two or more nearby base stations. It will be appreciated that the WTRU 102 may obtain location information using any suitable location determination method while remaining consistent with an embodiment.

[0031] The processor 118 may further be coupled to other peripherals 138, which may include one or more software and / or hardware modules that provide additional features, functionality, and / or wired or wireless connectivity. For example, the peripherals 138 may include an accelerometer, an e-compass, a satellite transceiver, a digital camera (for photos and / or videos), a universal serial bus (USB) port, a vibration device, a television transceiver, a hands-free headset, a Bluetooth module, a frequency modulation (FM) radio unit, a digital music player, a media player, a video game player module, an internet browser, a virtual reality and / or augmented reality (VR / AR) device, an activity tracker, and the like. The peripheral device 138 may include one or more sensors, which may be one or more of a gyroscope, an accelerometer, a Hall effect sensor, a magnetometer, an orientation sensor, a proximity sensor, a temperature sensor, a time sensor, a geolocation sensor, an altimeter, a light sensor, a touch sensor, a magnetometer, a barometer, a gesture sensor, a biometric sensor, and / or a humidity sensor.

[0032] The WTRU 102 may include a full-duplex radio where transmission and reception of some or all of the signals associated with a particular subframe (e.g., for both the UL (e.g., for transmission) and the downlink (e.g., for reception)) may be parallel and / or simultaneous. The full-duplex radio may include an interference management unit 139 to reduce and / or substantially eliminate self-interference via hardware (e.g., a choke) or via signal processing via a processor (e.g., a separate processor (not shown) or the processor 118). In an embodiment, the WTRU 102 may include a half-duplex radio for transmission and reception of some or all of the signals (e.g., associated with a particular subframe for either the UL (e.g., for transmission) or the downlink (e.g., for reception)).

[0033] 1C is a system diagram illustrating the RAN 104 and the CN 106, according to an embodiment. As described above, the RAN 104 may employ E-UTRA radio technology to communicate with the WTRUs 102a, 102b, 102c over the air interface 116. The RAN 104 may also communicate with the CN 106.

[0034] The RAN 104 may include eNodeBs 160a, 160b, and 160c, although it will be understood that the RAN 104 may include any number of eNodeBs while remaining consistent with an embodiment. The eNodeBs 160a, 160b, and 160c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, and 102c over the air interface 116. In one embodiment, the eNodeBs 160a, 160b, and 160c may implement MIMO technology. Thus, the eNodeB 160a, for example, may use multiple antennas to transmit wireless signals to and / or receive wireless signals from the WTRU 102a.

[0035] Each of the eNodeBs 160a, 160b, 160c may be associated with a particular cell (not shown) and may be configured to handle radio resource management decisions, handover decisions, scheduling of users in the UL and / or DL, etc. As shown in FIG. 1C, the eNodeBs 160a, 160b, 160c may communicate with each other over an X2 interface.

[0036] 1C may include a mobility management entity (MME) 162, a serving gateway (SGW) 164, and a packet data network (PDN) gateway (or PGW) 166. While each of the above elements is depicted as part of the CN 106, it will be understood that any of these elements may be owned and / or operated by an entity different from the CN operator.

[0037] The MME 162 may be connected to each of the eNodeBs 160a, 160b, 160c in the RAN 104 via an S1 interface and may act as a control node. For example, the MME 162 may be responsible for authenticating users of the WTRUs 102a, 102b, 102c, bearer activation / deactivation, selecting a particular serving gateway during initial attach of the WTRUs 102a, 102b, 102c, etc. The MME 162 may provide a control plane function for switching between the RAN 104 and other RANs (not shown) that employ other radio technologies, such as GSM and / or WCDMA.

[0038] The SGW 164 may be connected to each of the eNodeBs 160a, 160b, 160c in the RAN 104 via an S1 interface. The SGW 164 may generally route and forward user data packets to / from the WTRUs 102a, 102b, 102c. The SGW 164 may perform other functions, such as anchoring the user plane during inter-eNodeB handover, triggering paging when DL data is available to the WTRUs 102a, 102b, 102c, and managing and storing the context of the WTRUs 102a, 102b, 102c.

[0039] The SGW 164 may be connected to a PGW 166, which may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 110, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices.

[0040] The CN 106 may facilitate communications with other networks. For example, the CN 106 may provide the WTRUs 102a, 102b, 102c with access to circuit-switched networks, such as the PSTN 108, to facilitate communications between the WTRUs 102a, 102b, 102c and traditional landline communication devices. For example, the CN 106 may include or communicate with an IP gateway (e.g., an IP Multimedia Subsystem (IMS) server) that serves as an interface between the CN 106 and the PSTN 108. In addition, the CN 106 may provide the WTRUs 102a, 102b, 102c with access to other networks 112, which may include other wired and / or wireless networks owned and / or operated by other service providers.

[0041] Although in Figures 1A-1D the WTRU is described as a wireless terminal, it is contemplated that in certain representative embodiments such a terminal may use a wired communication interface (e.g., temporary or permanent) with a communication network.

[0042] In an exemplary embodiment, the other network 112 may be a WLAN.

[0043] A WLAN in infrastructure basic service set (BSS) mode may have an access point (AP) for the BSS and one or more stations (STAs) associated with the AP. The AP may have access to or interface with a distribution system (DS) or another type of wired / wireless network that carries traffic within and / or outside the BSS. Traffic originating from outside the BSS to a STA may arrive through the AP and be delivered to the STA. Traffic originating from a STA to a destination outside the BSS may be sent to the AP for delivery to the respective destination. Traffic between STAs within the BSS may be sent through the AP; for example, a source STA may send traffic to the AP, and the AP may deliver the traffic to the destination STA. Traffic between STAs within the BSS may be considered and / or referred to as peer-to-peer traffic. Peer-to-peer traffic may be sent (e.g., directly) between a source STA and a destination STA using direct link setup (DLS). In certain representative embodiments, the DLS may use 802.11e DLS or 802.11z Tunneled DLS (TDLS). A WLAN using an Independent BSS (IBSS) mode may not have an AP, and STAs within or using an IBSS (e.g., all of the STAs) may communicate directly with each other. IBSS mode communication may sometimes be referred to herein as "ad hoc" mode communication.

[0044] When using the 802.11ac infrastructure mode of operation or a similar mode of operation, an AP may transmit beacons on a fixed channel, such as a primary channel. The primary channel may be a fixed width (e.g., a 20 MHz wide bandwidth) or a width dynamically set via signaling. The primary channel may be the operating channel of the BSS and may be used by STAs to establish a connection with the AP. In one representative embodiment, for example, in an 802.11 system, carrier sense multiple access with collision avoidance (CSMA / CA) may be implemented. With CSMA / CA, STAs (e.g., every STA), including the AP, may sense the primary channel. If the primary channel is sensed / detected and / or determined to be busy by a particular STA, the particular STA may back off. Within a given BSS, one STA (e.g., only one station) may transmit at any given time.

[0045] A high-throughput (HT) STA may use a 40-megahertz-wide channel for communication, for example, by combining a primary 20-megahertz channel with an adjacent or non-adjacent 20-megahertz channel to form a 40-megahertz-wide channel.

[0046] A very high throughput (VHT) STA may support channels that are 20 MHz, 40 MHz, 80 MHz, and / or 160 MHz wide. A 40 MHz and / or 80 MHz channel may be formed by combining contiguous 20 MHz channels. A 160 MHz channel may be formed by combining eight contiguous 20 MHz channels or two non-contiguous 80 MHz channels, which may be referred to as an 80+80 configuration. In the 80+80 configuration, after channel encoding, the data may be passed through a segment parser that may split the data into two streams. Inverse fast Fourier transform (IFFT) processing and time-domain processing may be performed separately on each stream. The streams may be mapped onto two 80 MHz channels, and the data may be transmitted by the transmitting STA. At the receiver of the receiving STA, the operations described above for the 80+80 configuration may be reversed and the combined data may be sent to the Medium Access Control (MAC).

[0047] Sub-1 GHz mode operation is supported by 802.11af and 802.11ah. Channel operating bandwidths and carriers are reduced in 802.11af and 802.11ah compared to those used in 802.11n and 802.11ac. 802.11af supports 5 MHz, 10 MHz, and 20 MHz bandwidths in the TV White Space (TVWS) spectrum, while 802.11ah supports 1 MHz, 2 MHz, 4 MHz, 8 MHz, and 16 MHz bandwidths using non-TVWS spectrum. According to a representative embodiment, 802.11ah may support meter-type control / machine-type communication, such as MTC devices in macro coverage areas. MTC devices may have limited functionality, including, for example, support for certain bandwidths and / or limited bandwidths (e.g., only support for them). The MTC device may include a battery with a battery life above a threshold (eg, to maintain a very long battery life).

[0048] WLAN systems capable of supporting multiple channels and channel bandwidths, such as 802.11n, 802.11ac, 802.11af, and 802.11ah, include a channel that may be designated as a primary channel. The primary channel may have a bandwidth equal to the largest common operating bandwidth supported by all STAs in a BSS. The bandwidth of the primary channel may be set and / or limited by a STA that supports the smallest bandwidth operating mode among all STAs operating in the BSS. In the example of 802.11ah, for a STA (e.g., an MTC-type device) that supports (e.g., only supports) 1 MHz mode, the primary channel may be 1 MHz wide, even if the AP and other STAs in the BSS support 2 MHz, 4 MHz, 8 MHz, 16 MHz, and / or other channel bandwidth operating modes. Carrier sensing and / or network allocation vector (NAV) setting may depend on the status of the primary channel. For example, if the primary channel is busy because a STA (that only supports a 1 MHz operating mode) is transmitting to the AP, the entire available frequency band may be considered busy, even though most of the frequency band may remain idle and available for use.

[0049] In the United States, the available frequency bands that may be used by 802.11ah are 902 MHz to 928 MHz. In South Korea, the available frequency bands are 917.5 MHz to 923.5 MHz. In Japan, the available frequency bands are 916.5 MHz to 927.5 MHz. The total available bandwidth for 802.11ah is 6 MHz to 26 MHz, depending on country regulations.

[0050] 1D is a system diagram illustrating the RAN 113 and the CN 115, according to an embodiment. As described above, the RAN 113 may communicate with the WTRUs 102a, 102b, and 102c over the air interface 116 using NR radio technology. The RAN 113 may also communicate with the CN 115.

[0051] The RAN 113 may include gNBs 180a, 180b, and 180c, although it will be understood that the RAN 113 may include any number of gNBs while remaining consistent with an embodiment. The gNBs 180a, 180b, and 180c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, and 102c over the air interface 116. In one embodiment, the gNBs 180a, 180b, and 180c may implement MIMO technology. For example, the gNB 180a, 180b may utilize beamforming to transmit signals to and / or receive signals from the gNBs 180a, 180b, and 180c. Thus, the gNB 180a may, for example, transmit wireless signals to and / or receive wireless signals from the WTRU 102a using multiple antennas. In an embodiment, the gNBs 180a, 180b, 180c may implement carrier aggregation technology. For example, the gNB 180a may transmit multiple component carriers to the WTRU 102a (not shown). A subset of these component carriers may be on an unlicensed spectrum, while the remaining component carriers may be on a licensed spectrum. In an embodiment, the gNBs 180a, 180b, 180c may implement coordinated multipoint (CoMP) technology. For example, the WTRU 102a may receive coordinated transmissions from the gNBs 180a and 180b (and / or 180c).

[0052] The WTRUs 102a, 102b, 102c may communicate with the gNBs 180a, 180b, 180c using transmissions associated with a scalable numerology. For example, the OFDM symbol spacing and / or OFDM subcarrier spacing may vary for different transmissions, different cells, and / or different portions of the wireless transmission spectrum. The WTRUs 102a, 102b, 102c may communicate with the gNBs 180a, 180b, 180c using subframes or transmission time intervals (TTIs) of different or scalable lengths (e.g., including different numbers of OFDM symbols and / or lasting for different lengths of absolute time).

[0053] The gNBs 180a, 180b, 180c may be configured to communicate with the WTRUs 102a, 102b, 102c in a standalone configuration and / or a non-standalone configuration. In a standalone configuration, the WTRUs 102a, 102b, 102c may communicate with the gNBs 180a, 180b, 180c without accessing another RAN (e.g., eNodeBs 160a, 160b, 160c). In a standalone configuration, the WTRUs 102a, 102b, 102c may utilize one or more of the gNBs 180a, 180b, 180c as mobility anchor points. In a standalone configuration, the WTRUs 102a, 102b, 102c may communicate with the gNBs 180a, 180b, 180c using signals in unlicensed bands. In a non-standalone configuration, the WTRUs 102a, 102b, 102c may communicate with / connect to a gNB 180a, 180b, 180c while also communicating with / connecting to another RAN, such as an eNodeB 160a, 160b, 160c. For example, the WTRUs 102a, 102b, 102c may implement the DC principle to communicate with one or more gNBs 180a, 180b, 180c and one or more eNodeBs 160a, 160b, 160c substantially simultaneously. In a non-standalone configuration, the eNodeBs 160a, 160b, 160c may act as mobility anchors for the WTRUs 102a, 102b, 102c, and the gNBs 180a, 180b, 180c may provide additional coverage and / or throughput for serving the WTRUs 102a, 102b, 102c.

[0054] Each of the gNBs 180a, 180b, 180c may be associated with a particular cell (not shown) and may be configured to handle radio resource management decisions, handover decisions, scheduling of users in the UL and / or DL, support for network slicing, dual connectivity, interworking between NR and E-UTRA, routing of user plane data to User Plane Functions (UPFs) 184a, 184b and routing of control plane information to Access and Mobility Management Functions (AMFs) 182a, 182b, etc. As shown in FIG. 1D , the gNBs 180a, 180b, 180c may communicate with each other over the Xn interface.

[0055] 1D may include at least one AMF 182a, 182b, at least one UPF 184a, 184b, at least one Session Management Function (SMF) 183a, 183b, and possibly a Data Network (DN) 185a, 185b. While each of the above elements is depicted as part of the CN 115, it will be understood that any of these elements may be owned and / or operated by an entity different from the CN operator.

[0056] The AMF 182a, 182b may be connected to one or more of the gNBs 180a, 180b, 180c in the RAN 113 via an N2 interface and may act as a control node. For example, the AMF 182a, 182b may be responsible for authenticating users of the WTRUs 102a, 102b, 102c, supporting network slicing (e.g., handling different PDU sessions with different requirements), selecting a particular SMF 183a, 183b, managing registration areas, terminating NAS signaling, and mobility management. Network slicing may be used by the AMF 182a, 182b to customize CN support for the WTRUs 102a, 102b, 102c based on the type of service utilized by the WTRUs 102a, 102b, 102c. Different network slices may be established for different use cases, such as services relying on Ultra-Reliable Low-Latency (URLLC) access, services relying on eMBB access, and / or services for Machine-Type Communication (MTC) access, etc. The AMF 162 may provide a control plane function for switching between the RAN 113 and other RANs (not shown) that employ other radio technologies, such as LTE, LTE-A, LTE-A Pro, and / or non-3GPP access technologies such as WiFi.

[0057] The SMFs 183a and 183b may be connected to the AMFs 182a and 182b in the CN 115 via an N11 interface. The SMFs 183a and 183b may also be connected to the UPFs 184a and 184b in the CN 115 via an N4 interface. The SMFs 183a and 183b may select and control the UPFs 184a and 184b and configure the routing of traffic through the UPFs 184a and 184b. The SMFs 183a and 183b may perform other functions, such as managing and assigning UE IP addresses, managing PDU sessions, controlling policy enforcement and QoS, and providing downlink data notification. PDU session types may be IP-based, non-IP-based, Ethernet-based, etc.

[0058] The UPFs 184a, 184b may be connected to one or more of the gNBs 180a, 180b, 180c in the RAN 113 via an N3 interface, which may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 110, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices. The UPFs 184a, 184b may perform other functions, such as routing and forwarding packets, enforcing user plane policies, supporting multihoming PDU sessions, handling user plane QoS, buffering downlink packets, and providing mobility anchoring.

[0059] The CN 115 may facilitate communication with other networks. For example, the CN 115 may include or communicate with an IP gateway (e.g., an IP Multimedia Subsystem (IMS) server) that serves as an interface between the CN 115 and the PSTN 108. In addition, the CN 115 may provide the WTRUs 102a, 102b, 102c with access to other networks 112, which may include other wired and / or wireless networks owned and / or operated by other service providers. In one embodiment, the WTRUs 102a, 102b, 102c may be connected to local data networks (DNs) 185a, 185b through the UPFs 184a, 184b via an N3 interface to the UPFs 184a, 184b and an N6 interface between the UPFs 184a, 184b and the DNs 185a, 185b.

[0060] 1A-1D and the corresponding description thereof, one or more or all of the functions described herein with respect to one or more of the WTRUs 102a-d, base stations 114a-b, eNodeBs 160a-c, MME 162, SGW 164, PGW 166, gNBs 180a-c, AMFs 182a-b, UPFs 184a-b, SMFs 183a-b, DNs 185a-b, and / or any other devices described herein may be performed by one or more emulation devices (not shown). The emulation devices may be one or more devices configured to emulate one or more or all of the functions described herein. For example, the emulation devices may be used to test other devices and / or to simulate network and / or WTRU functionality.

[0061] The emulation device may be designed to perform one or more tests of other devices in a laboratory environment and / or in an operator network environment. For example, one or more emulation devices may perform one or more or all functions while fully or partially implemented and / or deployed as part of a wired and / or wireless communication network to test other devices in the communication network. One or more emulation devices may perform one or more or all functions while temporarily implemented / deployed as part of a wired and / or wireless communication network. The emulation device may be directly coupled to another device for testing purposes and / or may perform tests using over-the-air wireless communication.

[0062] The one or more emulation devices may perform one or more functions, including all functions, without being implemented / deployed as part of a wired and / or wireless communication network. For example, the emulation devices may be utilized in a test lab and / or in a test scenario in an undeployed (e.g., test) wired and / or wireless communication network to perform tests of one or more components. The one or more emulation devices may be test equipment. Direct RF coupling and / or wireless communication via RF circuitry (which may include, for example, one or more antennas) may be used by the emulation devices to transmit and / or receive data.

[0063] Bidirectional optical flow (BDOF) may be performed, for example, to enhance the efficiency of bi-predictive prediction. BDOF can improve the granularity and / or accuracy of motion vectors used during motion compensation. BDOF can improve coding performance. BDOF may increase complexity in a coding device (e.g., an encoder and / or decoder).

[0064] Video coding systems may be used to compress digital video signals to reduce the storage requirements and / or transmission bandwidth of such signals. Several types of video coding systems may exist, such as block-based systems, wavelet-based systems, and object-based systems. For example, block-based hybrid video coding systems may be widely used and deployed. Examples of block-based video coding systems may conform to one or more international video coding standards, such as MPEG1 / 2 / 4 part 2, H.264 / MPEG-4 part 10 AVC, VC-1, etc. Examples of block-based video coding systems may also include High Efficiency Video Coding (HEVC), developed by the Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T / SG16 / Q.6 / VCEG and ISO / IEC / MPEG.

[0065] FIG. 2 shows a diagram of a block-based video encoder that can be built on a block-based hybrid video coding framework. FIG. 2 shows a block diagram of a block-based video coding system, which can be a block-based hybrid video coding system. An input video signal 202 may be processed block by block. Extended block sizes (which may be referred to as coding units, or CUs) may be used to efficiently compress high-resolution (e.g., 1080 pixels or higher) video signals. CUs may be up to 64×64 pixels. CUs may be further partitioned into prediction units (PUs), to which separate prediction methods may be applied. For example, spatial prediction (260) and / or temporal prediction (262) may be performed on an input video block (MB or CU) from one or more input video blocks. Spatial prediction or intra prediction may use pixels from samples of already coded neighboring blocks, which may be referred to as reference samples, within the same video picture / slice to predict a current video block. Spatial prediction can reduce spatial redundancy that may be inherent in video signals. Temporal prediction, which may be referred to as inter-prediction or motion-compensated prediction, may use reconstructed pixels from an already-encoded video picture to predict the current video block. Temporal prediction can reduce temporal redundancy that may be inherent in video signals. The temporal prediction signal for a given video block may be signaled by one or more motion vectors, which may indicate the amount and direction of motion between the current block and its reference block. If multiple reference pictures are supported, a reference picture index for the video block (e.g., each video block) may be transmitted. The reference picture index may be used to identify which reference picture in the reference picture store (264) the temporal prediction signal originates from. After spatial prediction and / or temporal prediction, a mode decision (280) in the encoder may select a prediction mode based, for example, on a rate-distortion optimization method. The selected prediction mode may be the best prediction mode for the neighborhood.The prediction block may be subtracted from the current video block (216), and the prediction residual may be decorrelated using a transform block (204) and a quantization block (206). The quantized residual coefficients may be inverse quantized (210) and inverse transformed (212) to form a reconstructed residual, which can be added back to the prediction block (226) to form a reconstructed video block. Additionally, in-loop filtering, such as a deblocking filter and an adaptive loop filter, may be applied to the reconstructed video block (266), for example, before the reconstructed video block is input to the reference picture store (264) and used to encode a subsequent video block. To form the output video bitstream 220, the coding mode (e.g., inter-mode or intra-mode), prediction mode information, motion information, and quantized residual coefficients may be sent to an entropy coding unit (208) for further compression and packing to form the bitstream.

[0066] 3 shows a block diagram of a video decoder, which may be a block-based video decoder. The video bitstream 302 may be unpacked and entropy decoded in entropy decoding 308. The coding mode and prediction information may be sent to spatial prediction 360 (e.g., intra-coding) or motion-compensated prediction 362 (e.g., inter-coding) to form a prediction block. The residual transform coefficients may be sent to inverse quantization 310 and inverse transform 312 to reconstruct the residual block. The prediction block and the residual block may be added together at 336. The reconstructed block may further undergo in-loop filtering before being stored in a reference picture store 354. The reconstructed video in the reference picture store may then be sent to drive a display device or used to predict subsequent video blocks.

[0067] As shown in Figures 2 and 3, for example, the encoding / decoding workflow may be based on one or more of, for example, spatial prediction (e.g., intra-prediction), temporal prediction (e.g., inter-prediction), transform, quantization, entropy coding, and / or loop filter, etc.

[0068] Bidirectional optical flow (BDOF) may be used for motion vector derivation. For example, bi-prediction may be based on an optical flow model. Bi-prediction in video coding may involve combining two temporal prediction blocks that can be obtained from a reconstructed reference picture. Due to limitations of block-based motion compensation (MC), there may be residual small motion that can be observed between two prediction blocks, which may reduce the efficiency of motion-compensated prediction. BDOF may be applied, for example, to compensate for small motion within samples within a block. BDOF may include applying sample-wise motion refinement. Sample-wise motion refinement may be performed on top of block-based motion-compensated prediction, for example, when bi-prediction is used. Motion vectors (e.g., refined motion vectors) may be derived for samples within a block. Motion vector derivation may be based on an optical flow model (e.g., a classical optical flow model). For example, I (k) (x, y) is the sample value at coordinates (x, y) of the prediction block derived from reference picture list k (k=0, 1), and ∂I (k) (x,y) / ∂x and ∂I (k) Let (x,y) / ∂y contain the vertical and horizontal gradients of the sample, respectively. The motion refinement parameters (v x ,v y ) may be derived using an optical flow model (Equation (1)).

[0069]

number

[0070] By combining the optical flow equation (1) and the interpolation of the prediction block along the motion trajectory (shown in FIG. 4), the BDOF prediction may be obtained as equation (2).

[0071]

number

[0072] Referring to equation (2), τ0 and τ1 are expressed as I (0) and I (1) , and includes the temporal distances of the associated reference pictures Ref0 and Ref1 to the current picture CurPic, e.g., equation (3).

[0073]

number

[0074]

number

[0075] may include

[0076] Figure 4 shows an example of the application of BDOF. In Figure 4, (MV x0 ,MV y0 ) and (MV x1 ,MV y1 ) are the two predicted blocks I (0) and I (1) The motion refinement parameters (v) at sample position (x,y) can be used to generate the block-level motion vectors. x ,v y ) may be calculated by minimizing the difference Δ between the values ​​of the samples after motion refinement compensation (eg, A and B in FIG. 4), as shown as equation (4).

[0077]

number

[0078] The regularity of the derived motion refinement can be maintained. The motion refinement can be consistent within a local surrounding area centered at (x,y). In BDOF design, (v x ,v y The value of ) may be derived by minimizing Δ within a 5×5 window Ω around the current sample at (x,y) as equation (5).

[0079]

number

[0080] BDOF may be applied to bi-predictive blocks. A bi-predictively coded block may be predicted by two or more reference blocks from temporally adjacent pictures. BDOF may be enabled, for example, without transmitting additional information from the encoder to the decoder. For example, BDOF may be applied to bi-directionally predicted blocks with forward and backward prediction signals (e.g., τ0 × τ1 > 0). When the two prediction blocks of the current block are from the same direction (e.g., either forward or backward, τ0 × τ1 < 0), BDOF is applied when the two prediction blocks are associated with non-zero motion, e.g., abs(MV x0 )+abs(MV y0 ) ≠ 0 and abs(MV x1 )+abs(MV y1 )≠0, and the two motion vectors may be proportional to the temporal distance between the current picture and the reference picture, for example, equation (6).

[0081]

number

[0082] BDOF may be disabled if the two prediction blocks of the current block are from the same reference picture (e.g., τ0=τ1). BDOF may be disabled when local illumination compensation (LIC) is used for the current block.

[0083] A gradient derivation process may be performed. For example, as shown in equations (2) and (4), in addition to the block-level MC, the gradient may be derived from the motion compensation block samples (e.g., I (0) and I (1) ) may be used in BDOF for the sample, and the sample may be used to derive local motion refinement and generate a prediction at the location of the sample. In an embodiment, the horizontal and vertical gradients of the samples in the two prediction blocks (e.g.,

[0084]

number

[0085] and

[0086]

number

[0087] ) may be calculated, for example, when a prediction signal is generated based on a filtering process. For example, motion compensated interpolation may be performed using a 2D separable finite response (FIR) filter. Horizontal and vertical gradients may be generated simultaneously. The input to the gradient derivation process may include reference samples used for motion compensation. The input to the gradient derivation process may include an input motion (MV x0 / x1 ,MV y0 / y1 ) may include a fractional component of the gradient at the sample location. To derive the gradient at the sample location, two different filters (e.g., an interpolation filter h L and the gradient filter h G) may be applied. Filters may be applied separately, for example in different orders, for each direction of gradient that may be calculated. One or more of the following may be applied: Horizontal gradients (e.g.,

[0088]

number

[0089] and

[0090]

number

[0091] ) when deriving the interpolation filter h L may be applied vertically to samples within the prediction block to derive sample values ​​at vertical fractional positions in fracY. G may be applied horizontally to the generated vertical fractional samples to calculate a horizontal gradient value based on the value of fracX.

[0092]

number

[0093] and

[0094]

number

[0095] ) to derive the gradient filter h G may be applied vertically on top of the prediction samples to calculate an intermediate vertical gradient corresponding to fracY, followed by an interpolation filter h according to the value of fracX. LThis may be followed by horizontal interpolation of the intermediate vertical gradients using the gradient filter and interpolation filter. The length of the gradient filter and interpolation filter may be 6 taps. An 8-tap filter may be used for motion compensation. Tables 1 and 2 show the accuracy of the block-level motion vectors according to the accuracy of the h G and h L , and indicates the filter coefficients (which may be up to 1 / 16 pixel (pel) for example) that can be used for each.

[0096] [Table 1]

[0097] [Table 2]

[0098] 5A and 5B show an example of gradient derivation in BDOF with 1 / 16 pixel (pel) motion accuracy. As shown in FIGS. 5A and 5B, a gradient derivation process may be applied to BDOF, where sample values ​​at integer sample positions may be indicated by patterned squares and sample values ​​at fractional sample positions may be indicated by blank squares. Because motion vector accuracy can be increased to 1 / 16 pixel (pel), there may be a total of 255 fractional sample positions that can be defined within the range of integer samples in FIGS. 5A and 5B. The subscript coordinates (x, y) may represent the corresponding horizontal and vertical fractional positions of the sample (e.g., coordinate (0, 0) may correspond to a sample at an integer position). Horizontal and vertical gradient values ​​at fractional position (1, 1) may be calculated (e.g., a 1,1 ) Based on the notation in Figures 5A and 5B, for the horizontal gradient derivation, the interpolation filter h L By applying vertically, the fractional sample f 0,1 , e 0,1 , a0,1 , b 0,1 , c 0,1 , and d 0,1 may be derived, for example, as shown in equation (7).

[0099]

number

[0100] Referring to equation (7), B may include the bit depth of the input signal, and OffSet0 may include a rounding offset that may be equal to equation (8).

[0101]

number

[0102] f 0,1 , e 0,1 , a 0,1 , b 0,1 , c 0,1 , and d 0,1 The precision of a may be 14 bits. 1,1 The horizontal gradient of the corresponding gradient filter h G may be calculated by horizontally applying ∑ ...

[0103]

number

[0104] The horizontal gradient may be calculated by shifting the intermediate gradient value to the output precision as in equation (10).

[0105]

number

[0106] Referring to equation (10), sign(·) and abs(·) may include functions that return the sign and absolute value of the input signal, respectively, and OffSet1 may be 2 17-B It may also include a rounding offset which can be calculated as:

[0107] Now, referring to the vertical gradient derivative at (1,1), an intermediate vertical gradient value at fractional position (0,1) may be derived, for example, as shown in equation (11).

[0108]

number

[0109] The intermediate slope value may be adjusted by shifting the 14-bit value as in equation (12).

[0110]

number

[0111] The vertical gradient value at fractional position (1,1) is filtered by the interpolation filter h L As shown by equations (13) and (14), the unrounded gradient value in 20 bits may be calculated, and through a shift operation, the unrounded gradient value may be adjusted to the output bit depth.

[0112]

number

[0113]

number

[0114] The memory bandwidth consumption of BDOF can be established. As shown in equation (5), the local motion refinement (v x,v y To derive Ω(W,T), sample values ​​and gradient values ​​may be calculated for one or more samples (e.g., all samples) within a window Ω surrounding the samples. The window size may comprise (2M+1)×(2M+1), where M=2. Due to the interpolation and gradient filters, the gradient derivation may access one or more (e.g., additional) reference samples that can be found within an extended area of ​​the current block. The length T of the interpolation and gradient filters may be 6, and / or the corresponding extended block size may be equal to T−1=5. For example, given a block of W×H, the memory accesses (total memory accesses) used by BDOF may be (W+T−1+2M)×(H+T−1+2M)=(W+9)×(H+9), which may be more than the memory accesses (W+7)×(H+7) used by other techniques. The memory accesses of BDOF may be less than or equal to the memory accesses of other techniques. A block extension constraint may be imposed. When a block extension constraint is applied, neighboring samples within the current block are subjected to local motion refinement (v x ,v y ) may be used to calculate. Figures 6A-B show diagrams of memory accesses in BDOF, where Figure 6A shows memory accesses without a block extension constraint and Figure 6B shows memory accesses with a block extension constraint. Figures 6A and 6B can compare the size of the memory access area before and after the block extension constraint is applied.

[0115] Motion compensation based on sub-blocks (e.g., sub-CUs) may be performed. The coding block may have a motion vector for the prediction direction. Several sub-block level inter prediction techniques may be used. The sub-block level inter prediction techniques may include advanced temporal motion vector prediction (ATMVP), spatial-temporal motion vector prediction (STMVP), frame rate up-conversion (FRUC) mode, and / or affine mode, etc. One or more of the following may be applied: A video block may be divided into multiple small sub-blocks, which may be used to derive motion information for the sub-blocks (e.g., information for each sub-block separately). The motion information for the sub-blocks may be used to generate a prediction signal for the block, for example, in a motion compensation stage. Sub-block coding modes may be provided.

[0116] ATMVP may be performed as described herein. One or more of the following may be applied: Temporal motion vector prediction may provide a block for deriving motion information. The derived motion information may include motion vectors and reference indices (e.g., from one or more smaller blocks of temporally adjacent pictures of the current picture) for sub-blocks within the block. As shown in Figure 7, ATMVP may derive motion information for sub-blocks of a block; corresponding blocks of the current block, which may be referred to as collocated blocks, may be identified (e.g., in a temporal reference picture), and the current block may be divided into sub-blocks, and / or motion information for the sub-blocks from corresponding smaller blocks in the collocated picture may be derived. The selected temporal reference picture may be referred to as a collocated picture.

[0117] FIG. 7 shows an example diagram of ATMVP. The co-located blocks and co-located pictures may be identified, for example, by motion information of spatially neighboring blocks of the current block. As shown in FIG. 7, available candidates (e.g., the first available candidate) in the merge candidate list may be considered. For example, referring to FIG. 7, block A may be identified as an available (e.g., the first available) merge candidate for the current block based on the existing scanning order of the merge candidate list. The corresponding motion vector (e.g., MV) of block A may be considered. A ) and its reference index may be used to identify the co-located picture and the co-located block. The location of the co-located block within the co-located picture is determined by the block's motion vector (MV A ) to the coordinates of the current block.

[0118] For a sub-block (e.g., each sub-block) in the current block, the motion information of its corresponding small block in the co-located block (e.g., indicated by an arrow in FIG. 7) may be used to derive motion information of the corresponding sub-block in the current block. For example, the motion information of the small block in the co-located block may be converted into a motion vector and reference index of the corresponding sub-block in the current block (e.g., after the motion information of each small block in the co-located block is identified). The motion information of the sub-block in the current block may be derived in a manner similar to other derivation techniques (e.g., temporal motion vector scaling can be applied).

[0119] STMVP may be performed as described herein. Figure 8 shows an example diagram of STMVP. One or more of the following may be applied: In STMVP, motion information for sub-blocks within a coding block may be derived (e.g., recursively derived). Figure 8 shows an example of recursively deriving motion information for sub-blocks within a coding block. With reference to Figure 8, a current block may include four sub-blocks A, B, C, and D. Neighboring small blocks that may be spatially adjacent to the current block may be labeled a, b, c, and d, respectively. Motion derivation for sub-block A may include identifying one or more spatial neighbors (e.g., two spatial neighbors of sub-block A). A neighbor (e.g., a first neighbor) of sub-block A may be neighbor c above. If small block c is not available or is intra-coded, subsequent neighboring small blocks above the current block may be checked in order (e.g., from left to right). Another neighbor (e.g., a second neighbor) of sub-block A may be neighbor b to the left. If small block b is not available or is intra-coded, subsequent neighboring small blocks may be checked, for example, in order to the left of the current block (top to bottom). After fetching the motion information of the spatial neighbors, motion information of the temporal neighbors of sub-block A may be obtained using a procedure that may be similar to TMVP. The motion information of the available spatial neighbors and one or more temporal neighbors (e.g., up to three neighbors) may be averaged and used as the motion information of sub-block A. Based on the raster scan order, the above STMVP process may be repeated to derive motion information of other sub-blocks (e.g., all other sub-blocks) in the current video block.

[0120] Frame rate up-conversion (FRUC) may be performed. FRUC may be supported for inter-coded blocks, which may reduce motion information signaling. When FRUC mode is enabled, motion information of coded blocks, which may include motion vectors and reference indices, may not be signaled. Motion information may be derived (e.g., at a decoder) using, for example, template matching and / or bilateral matching. For example, during the motion derivation process at the decoder, a set of preliminary motion vectors generated from the merge candidate list of the block and the motion vectors of the temporally co-located blocks of the current block may be checked. The candidate that leads to the smallest sum of absolute differences (SAD) may be selected as the starting point. A local search based on template matching or bilateral matching around the starting point may be performed. The MV that results in the smallest SAD may be used as the MV for the block. The motion information may be refined at the sub-block level, which may result in efficient motion compensation.

[0121] 9A and 9B illustrate an embodiment associated with FRUC. For example, FIGS. 9A and 9B illustrate exemplary diagrams for frame rate up-conversion, with FIG. 9A illustrating template matching and FIG. 9B illustrating bilateral matching. As shown in FIG. 9A, template matching may be used to derive motion information for a current block by finding a match (e.g., a best match) between a template in a current picture and a block (which may be the same size as the template) in a reference picture. The template may include a neighboring block above and / or to the left of the current block. In FIG. 9B, bilateral matching may be used to derive motion information for the current block. The derivation of the motion information for the current block may include finding a match (e.g., a best match) between two blocks along the motion trajectory of the current block in different reference pictures (e.g., two different reference pictures). The motion search process for bilateral matching may be based on the motion trajectory. For example, the motion search process for bilateral matching may be based on motion vectors MV0 and MV1. The motion vectors MV0 and MV1 may point to the reference blocks. The motion vectors MV0 and MV1 may be proportional to the temporal distance between the current picture and two reference pictures (e.g., T0 and T1).

[0122] An affine model may be used to provide motion information. Figures 10A and 10B show exemplary diagrams for affine mode, with Figure 10A showing a simplified affine model and Figure 10B showing sub-block level motion derivation for an affine block. A translation motion model may be applied for motion compensated prediction. The motion may include one or more of scaling, rotation, perspective motion, and / or anomalous motion. An exemplary affine transform motion compensated prediction may be applied. As shown in Figure 10A, the affine motion field of a block may be described by the motion vectors of one or more (e.g., two) control points. Based on the motion of the control points, the motion field of the affine block may be described as Equation (15).

[0123]

number

[0124] Referring to equation (15), as shown in FIG. 10A, (v 0x ,v 0y ) may be the motion vector of the upper left corner control point, and (v 1x ,v 1y ) may be the motion vector of the control point of the top-right corner. When a video block is coded using an affine mode, the motion field of the video block may be derived based on a granularity of 4x4 blocks. For example, as shown in FIG. 10B, to derive a motion vector for a 4x4 block (e.g., each 4x4), the motion vector of the center sample of a sub-block (e.g., each sub-block) may be calculated according to equation (15) and rounded to 1 / 16 pixel (pel) accuracy. The derived motion vector may be used in a motion compensation stage to generate a prediction signal for a sub-block within the current block.

[0125] BDOF may be simplified. One or more of the following may be applied: The number of BDOF processes for bi-predicted CUs may be reduced. BDOF may be performed taking parallel processing into consideration. For bi-predicted CUs, BDOF processing may be skipped at either the CU level or the sub-CU level based on the similarity of two prediction signals from one or more (e.g., two) reference lists. For example, if the prediction signals are similar, BDOF adjustment may be skipped. For example, the number of BDOF adjustments invoked may be reduced so that coding performance is maintained. Gradient derivation of BDOF for a list (e.g., each list) may include sample interpolation and gradient calculation if the motion vectors in the list are not integers. The order of horizontal filtering and vertical filtering may be changed for implementations with parallel processing.

[0126] As described herein, integer motion components may be provided. For example, k bits may be used to represent the fractional part of a motion vector component, and the component value of the motion vector may be (2 k ), the motion vector components may include integer motion vector components. Similarly, if the motion vector component values ​​are multiples of (2 k ), a motion vector component may include a non-integer (eg, fractional) portion and an integer portion.

[0127] As described herein, BDOF may be performed with bi-prediction in mind, which can improve the granularity and accuracy of the motion vectors used in the motion compensation stage.

[0128] In BDOF, horizontal and vertical gradients may be generated for reference picture lists (e.g., L0 and L1). For example, BDOF refinement may include invoking one or more filtering operations (e.g., horizontal filtering operations and / or vertical filtering operations) on the horizontal and vertical gradients in the reference picture lists (e.g., each reference picture list). As discussed herein, motion vectors, MVs (MVsx ,MV y ), the horizontal gradient derivation may involve applying a sample interpolation filter in the vertical direction. For example, MV y If the motion vector (e.g., vertical component of the motion vector MV) contains non-integer (e.g., fractional) motion vector components, a sample interpolation filter may be used to derive sample values ​​at fractional positions. Gradient filtering may be performed horizontally using the interpolated sample values ​​at fractional positions vertically. MV y If x contains an integer motion component, then a gradient filter (e.g., a single gradient filter) may be applied in the horizontal direction, e.g., using sample values ​​at integer positions. A similar process may be performed for the derivation of the vertical gradient.

[0129] A bi-predictive CU may be associated with one or more (e.g., two) motion vectors. One or more filtering operations may be performed on the CU. For example, if the horizontal and vertical components of the motion vector associated with the CU include non-integer (e.g., fractional) motion components, multiple (e.g., eight) filtering operations may be performed. When performed (e.g., invoked), the filtering operations may involve memory access requests, multiple multiplications, and multiple additions. The length of the filter used during BDOF (e.g., an 8-tap sample interpolation filter and a 6-tap gradient filter) may affect the coding complexity.

[0130] BDOF refinement may be conditionally skipped. For example, BDOF refinement may be conditionally skipped based on the similarity between two or more predicted signals. One or more other similarity determinations may be performed to determine whether to skip BDOF.

[0131] The BDOF refinement of a CU (e.g., as described in equation (2)) may include motion refinement in the horizontal and vertical directions.x ,v y ) may be derived. For example, a motion refinement parameter (v x ,v y ) may be derived by least-squares techniques using prediction. For example, local gradient information from two or more reference pictures may be used for bi-prediction. Motion refinement parameters may be derived.

[0132] A simplified gradient derivation method may be used for BDOF. As described herein, BDOF may include eight filtering operations when the horizontal and vertical components of the motion vector associated with a CU include non-integer (e.g., fractional) motion components. The number of filtering operations may be reduced, for example, to four filtering operations. The number of memory accesses, multiplications, and / or additions may be reduced.

[0133] The decision whether to perform BDOF refinement may be made, for example, before BDOF refinement is performed. The decision whether to skip BDOF may be based on one or more characteristics associated with the CU (e.g., coding mode and / or block size).

[0134] Directional BDOF refinement may be performed on a CU. For example, the directional BDOF refinement may include performing BDOF refinement in a particular direction (e.g., vertical or horizontal). For example, a gradient-based analysis (e.g., gradient calculation) may be performed on a bi-predictive CU. As described herein, the gradient calculation may be performed at one or more levels, including, for example, the CU level, the sub-CU level, the block level, the sub-block level, etc. Based on the gradient calculation, one or more of the following may be applied: BDOF refinement may be skipped; directional BDOF refinement may be performed in the horizontal direction; directional BDOF refinement may be performed in the vertical direction; or BDOF refinement may be performed in both the horizontal and vertical directions.

[0135] As described herein, BDOF refinement may include performing gradient calculations. The gradient calculation process may include, for example, deriving horizontal and / or vertical gradients for a reference picture of a CU using a motion vector associated with the reference picture. The motion vector associated with the reference picture may include a motion component. The gradient calculation in a particular direction may include applying a sample interpolation filter, for example, if a motion vector component in another direction (e.g., the vertical direction) is a non-integer (e.g., fractional) motion component. The gradient filter may be applied, for example, following the sample interpolation filter. The sample interpolation filter may include a low-pass filter, and the gradient filter may include a high-pass filter, which may be used for gradient derivation.

[0136] The gradient may be calculated using sample value(s) at integer positions. Sample values ​​at integer positions of a reference CU may be identified. Sample values ​​at integer positions may be used to approximate sample values ​​at fractional positions, for example, if the motion vector component in that direction includes a non-integer (e.g., fractional) motion component. The gradient calculation may include applying a gradient filter in a particular direction. A sample interpolation filter may not be applied. The motion vector is calculated using the MV(MV x ,MV y ) and may be associated with the reference picture R. k may be the number of bits represented for the fractional values ​​of the motion vector components. The number of gradient filters defined for the fractional positions may be denoted as n (e.g., 16 shown in Table 1). n is a scalar function of (2 k ) or less. The position of a CU (e.g., the current bi-predictive CU in the current picture) may be P(P x ,P y ) may also be written as

[0137] A horizontal gradient of a CU (e.g., a reference CU) associated with the motion vector MV may be derived. One or more of the following may be applied: An integer position of the reference CU within the reference picture associated with the CU may be identified. The integer position of the reference CU may comprise P'(P'x, P'y), where P'x = Px + (MVx >> k) and P'y = Py + (MV y >>k). The phase (e.g., horizontal fractional position) of the gradient filter may be identified (e.g., Phase=((MV x )+(2 k -1)) / (2 k / n). The gradient filters, which may be defined in Table 1, may be identified by phase. To calculate the horizontal gradient, the gradient filter may be applied to a sample position in a reference CU located at P'(P'x, P'y) in reference picture R (e.g., in the horizontal direction).

[0138] A vertical gradient of a CU (e.g., a reference CU) associated with the motion vector MV may be derived. One or more of the following may be applied: An integer position of a reference CU in a reference picture associated with the CU may be identified. The integer position of the reference CU may comprise P'(P'x, P'y), where P'x = Px + (MVx >> k) and P'y = Py + (MVy >> k). A phase (e.g., vertical fractional position) of a gradient filter may be identified (e.g., Phase = ((MVy) + (2 k -1)) / (2 k / n). The gradient filters, which may be defined in Table 1, may be identified by phase. To calculate the vertical gradient, the gradient filter may be applied to a sample position in a reference CU located at P'(P'x, P'y) in reference picture R (e.g., in the vertical direction).

[0139] The techniques described herein may be applied to derive other sets of horizontal and vertical gradients (e.g., to derive a set of horizontal and vertical gradients from reference picture lists L0 and / or L1). For example, the techniques described herein may be applied to other motion vectors (e.g., a second motion vector) associated with a bi-predictive CU to derive other sets of horizontal and vertical gradients. If a motion vector associated with a CU (e.g., two motion vectors associated with a bi-predictive CU) includes a non-integer (e.g., fractional) motion component, the number of filters applied to samples during BDOF may be reduced (e.g., four gradient filters may be applied to each sample).

[0140] As described herein, for example, the sample interpolation filter may be skipped during gradient derivation. A gradient filter may be applied during gradient derivation, for example, to integer positions associated with a reference CU (e.g., one of the 16 filters defined in Table 1). As described herein, applying a gradient filter to reference samples at integer positions of a reference CU can approximate the fractional positions of samples within the reference CU (when a motion vector includes a non-integer motion component). The filter to be used for a CU (e.g., each CU) may be identified based on the motion vector associated with the CU. The number of gradient filters (e.g., n) applied during gradient derivation may be reduced. The number of gradient filters may be less than the number of possible fractional positions of a motion vector component. For example, a single gradient filter may be used during gradient derivation. A gradient filter, such as the gradient filter defined at position 0 in Table 1, may be defined (e.g., pre-defined). When a single gradient filter is used during gradient derivation, the gradient filter may not be stored, and a phase for the gradient filter may not be calculated.

[0141] BDOF processing may be performed conditionally based on one or more characteristics (e.g., coding mode and / or size) associated with a CU. For example, BDOF may or may not be performed based on one or more characteristics (e.g., coding mode and / or size) associated with a CU. A CU may be associated with one or more inter-coding modes. For example, a particular coding mode may support sub-CU (e.g., or sub-block) prediction, such as ATMVP / STMVP, FRUC bilateral matching, FRUC template matching, affine, etc. A sub-CU (e.g., a sub-block within a CU) with individual motion information may be referred to as a PU. A sub-CU may be used in BDOF, for example, to improve the efficiency of inter-prediction. For example, a sub-CU may provide a motion field (e.g., a refined motion field) for the sub-CU. Inter-coding modes that support sub-CU prediction may have different characteristics. One or more of the following may apply: ATMVP / STMVP can derive the motion field of the current CU from spatial neighboring blocks, temporal neighboring blocks, and / or spatial and temporal neighboring blocks. FRUC bilateral matching and FRUC template matching can derive motion information in a manner similar to motion search. For example, FRUC bilateral matching and FRUC template matching can derive motion information at a decoder.

[0142] BDOF (e.g., BDOF refinement) may be conditionally performed based on a coding mode associated with a CU. For example, BDOF may be skipped based on an inter coding mode associated with a CU (e.g., a sub-CU and / or a PU). An inter coding mode associated with a CU may be identified. The inter coding mode may support sub-CU prediction. If the inter coding mode associated with a CU supports sub-CU prediction, BDOF refinement may be skipped (e.g., disabled for the CU).

[0143] As described herein, BDOF may or may not be performed based on the size associated with a CU (e.g., sub-CU and / or PU). For sub-CU inter mode, if the PU size is larger (e.g., larger than a threshold such as 32×32), the coding region may be within a specific motion area (e.g., a flat motion area). If the PU size is smaller (e.g., smaller than a threshold such as 32×64), the motion within the coding region may be complex. If a CU (e.g., the current bi-predictive CU) is coded using a sub-block inter mode and the PU size is large (e.g., larger than a threshold, which may be predefined), BDOF processing (e.g., BDOF refinement) may be skipped. If the PU size is small (e.g., equal to or smaller than a threshold, which may be predefined), BDOF processing may be applied. The threshold for a sub-CU mode (e.g., each sub-CU mode) may be signaled in a sequence parameter set, a picture parameter set, a slice header, or the like.

[0144] The coding mode and / or PU size may be identified, for example, to determine whether to perform BDOF. Similarity between two or more predicted signals, such as SAD calculation, may not be determined. For example, the techniques described herein related to determining whether to perform BDOF (e.g., based on the coding mode and / or PU size) may be combined with methods based on other signal characteristics. For example, the techniques may include determining whether BDOF processing is required for the current CU. The device may determine whether to perform BDOF (e.g., using one or more of the techniques described herein). For example, BDOF may be conditionally performed based on the PU size and / or coding mode.

[0145] Directional BDOF refinement may be performed. For example, BDOF refinement may be performed in a particular direction (e.g., horizontal or vertical) based on a gradient difference calculation. BDOF refinement may be performed for a sample (e.g., each sample), a block, a CU, and / or a sub-CU (e.g., a sub-block such as 4x4). FIG. 11 shows a diagram for BDOF refinement for a CU. Horizontal and vertical gradients may be calculated for a CU, for example, using the techniques described herein. One or more BDOF refinement parameters (v x ,v y ) may be derived for the sub-CU, for example, using a least squares method. A BDOF refinement prediction may be generated for the sub-CU using the derived BDOF refinement parameters, for example, by applying equation (2). The characteristics of the sub-CU may be different. The horizontal gradient of the reference picture in list 0 (e.g.,

[0146]

number

[0147] ) is the horizontal gradient of the reference picture in List 1 (e.g.,

[0148]

number

[0149] In cases similar to the above, BDOF refinement may not result in an improvement in the horizontal direction. BDOF refinement may or may not be performed in one or more directions.

[0150] The determination of whether to perform BDOF (e.g., directional BDOF) may be based on gradient analysis (e.g., gradient difference) performed in multiple (e.g., two) directions. For example, dGx (e.g., horizontal gradient difference) and dGy (e.g., vertical gradient difference) may be defined for a CU (e.g., or sub-CU) using equations (16) and (17), respectively. dGx and dGy may be used to determine whether gradients in reference pictures associated with the CU (e.g., or sub-CU) are similar and / or to determine a direction (e.g., horizontal or vertical) in which to perform directional BDOF.

[0151]

number

[0152]

number

[0153] dGx and dGy may be compared (e.g., compared with each other) to a threshold, for example, to determine whether to perform directional BDOF. The threshold may be static and / or variable. If dGx is equal to or less than a threshold, such as a static threshold (e.g., a predefined threshold), the horizontal gradients of the CU (e.g., or sub-CU) in the reference picture associated with the CU may be similar. If dGy is equal to or less than a threshold, such as a static threshold (e.g., a predefined threshold), the vertical gradients of the CU (e.g., or sub-CU) in the reference picture associated with the CU may be similar. One or more of the following may be applied: If the gradients in the horizontal and vertical directions are similar, BDOF refinement may be skipped for the CU (e.g., or sub-CU). Bi-prediction may be applied, for example, to generate a prediction for the CU. If the vertical gradients are similar and the horizontal gradients are not similar, the horizontal BDOF refinement parameter v xmay be derived, and the directional BDOF may be performed in the horizontal direction, for example, using equation (18). If the vertical gradients are similar and the horizontal gradients are dissimilar, the vertical BDOF refinement parameter v y The derivation of may be skipped.

[0154]

number

[0155] The vertical gradients may be dissimilar, while the horizontal gradients may be similar. The vertical BDOF refinement parameter v y may be derived and directional BDOF refinement may be performed in the vertical direction, for example, using equation (19). x The derivation of may be skipped.

[0156]

number

[0157] The gradients in the vertical and horizontal directions may be dissimilar. If the gradients in the vertical and horizontal directions are dissimilar, then BDOF refinement may be performed, for example, in the horizontal and vertical directions.

[0158] As described herein, dGx and dGy may be compared (e.g., each may be compared) to a variable threshold (e.g., a dynamic threshold) to determine, for example, whether to perform directional BDOF. For example, dGx may be compared to a first threshold, and dGy may be compared to a second threshold. The first threshold and the second threshold may be variable. For example, the first threshold may be dGy (e.g., horizontal gradient difference), and the second threshold may be dGx (e.g., vertical gradient difference). If dGx is greater than the first threshold, directional BDOF may be performed in the vertical direction. If dGy is greater than the second threshold, directional BDOF may be performed in the horizontal direction.

[0159] FIG. 12 shows a diagram for directional BDOF refinement, which may be for a CU (e.g., or sub-CU). A gradient difference (e.g., dGx and dGy) may be calculated for a CU or sub-CU (e.g., each CU or sub-CU). Based on the gradient difference, one or more of the following may be applied: no BDOF refinement may be performed (e.g., skipped); BDOF refinement may be performed; directional BDOF may be performed in the vertical direction; or directional BDOF may be performed in the horizontal direction. The thresholds may be signaled in a sequence parameter set, a picture parameter set, a slice header, or the like. As described herein, the thresholds may be variable (e.g., with reference to FIG. 12, TH1 may include dGy and / or TH2 may include dGx).

[0160] The gradient difference may be calculated across the CU (e.g., at the beginning of PU processing), for example, using equations (20) and (21). The determination of the direction in which to perform directional BDOF refinement may be performed at the CU level, sub-CU level, and / or PU level. One or more of the following may be applied: BDOF refinement may be skipped at the CU level, sub-CU level, and / or PU level; directional BDOF refinement may be performed at the CU level, sub-CU level, and / or PU level; directional BDOF refinement may be performed in the vertical direction at the CU level, sub-CU level, and / or PU level; BDOF refinement may be performed at the CU level, sub-CU level, and / or PU level; etc. The threshold may be scaled, for example, based on the area of ​​the CU, sub-CU, and / or PU (e.g., because the comparison of dGx or dGy may not be performed for sub-blocks having equal sizes).

[0161]

number

[0162]

number

Claims

1. 1. A video decoding device comprising at least one processor, The at least one processor obtaining a size of a coding block, the coding block including sub-blocks; determining whether to enable bidirectional optical flow (BDOF) for the coding block based on a size of the coding block; obtaining a first prediction of the sub-block based on a first reference block of the sub-block and a second prediction of the sub-block based on a second reference block of the sub-block; determining a predicted similarity value between the first prediction and the second prediction; determining, based on a determination to enable BDOF for the coding block and based on the prediction similarity value, to perform BDOF to predict the sub-block; performing BDOF to obtain a third prediction of the sub-block; decoding the coded block based on a third prediction of the sub-block; 2. A device configured to:

2. The apparatus of claim 1 , wherein the predicted similarity value is a sum of absolute differences (SAD) based on the first prediction and the second prediction.

3. 2. The apparatus of claim 1, wherein the prediction includes a sub-block prediction technique, and wherein BDOF is determined to be disabled for the coding block based on a determination that the sub-block prediction technique is used to decode the coding block.

4. the coding block is a first coding block, The at least one processor determining to perform BDOF on a second coding block; determining a plurality of gradients based on sample positions of the second coded block; determining a motion refinement based on the plurality of gradients; obtaining sample values ​​associated with the second coding block based on the determined motion refinement; The apparatus of claim 1 further configured to:

5. 1. A video decoding method comprising: obtaining a size of a coding block, the coding block including sub-blocks; determining whether to enable bidirectional optical flow (BDOF) for the coding block based on a size of the coding block; obtaining a first prediction of the sub-block based on a first reference block of the sub-block and a second prediction of the sub-block based on a second reference block of the sub-block; determining a predicted similarity value between the first prediction and the second prediction; determining, based on a determination to enable BDOF for the coding block and based on the prediction similarity value, to perform BDOF to predict the sub-block; performing BDOF to obtain a third prediction of the sub-block; decoding the coded block based on a third prediction of the sub-block; A method comprising:

6. 6. The method of claim 5, further comprising comparing the size of the coding block to a value, and wherein a determination to disable BDOF for the coding block is made based on the comparison of the size of the coding block to the value.

7. 6. The method of claim 5, wherein the prediction includes a sub-block prediction technique, and wherein BDOF is determined to be disabled for the coding block based on a determination that the sub-block prediction technique is used to decode the coding block.

8. 1. A video encoding device comprising a processor, The processor: obtaining a size of a coding block, the coding block including sub-blocks; determining, based on a size of the coding block, to enable bidirectional optical flow (BDOF) for the coding block; obtaining a first prediction of the sub-block based on a first reference block of the sub-block and a second prediction of the sub-block based on a second reference block of the sub-block; determining a predicted similarity value between the first prediction and the second prediction; determining, based on a determination to enable BDOF for the coding block and based on the prediction similarity value, to perform BDOF to predict the sub-block; performing BDOF to obtain a third prediction of the sub-block; encoding the coding block based on a third prediction of the sub-block; 2. A device configured to:

9. 9. The apparatus of claim 8, wherein the processor is further configured to compare the size of the coding block to a value, and wherein a determination to disable BDOF for the coding block is made based on the comparison of the size of the coding block to the value.

10. 9. The apparatus of claim 8, wherein the prediction includes a sub-block prediction technique, and wherein BDOF is determined to be disabled for the coding block based on a determination that the sub-block prediction technique is used to encode the coding block.

11. 1. A video encoding method, comprising: obtaining a size of a coding block, the coding block including sub-blocks; determining, based on the size of the coding block, to enable bidirectional optical flow (BDOF) for the coding block; obtaining a first prediction of the sub-block based on a first reference block of the sub-block and a second prediction of the sub-block based on a second reference block of the sub-block; determining a predicted similarity value between the first prediction and the second prediction; determining, based on a determination to enable BDOF for the coding block and based on the prediction similarity value, to perform BDOF to predict the sub-block; performing BDOF to obtain a third prediction of the sub-block; encoding the coding block based on a third prediction of the sub-block; A method comprising:

12. 12. The method of claim 11, further comprising comparing the size of the coding block to a value, and wherein a determination to disable BDOF for the coding block is made based on the comparison of the size of the coding block to the value.

13. 12. The method of claim 11, wherein the prediction includes a sub-block prediction technique, and wherein BDOF is determined to be disabled for the coding block based on a determination that the sub-block prediction technique is used to encode the coding block.

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