Template-based CCLM / MMLM tilt adjustment

Abstract

Systems, methods, and means are disclosed for template-based component-to-component linear model / multi-modal linear model (CCLM / MMLM) adjustment. In one embodiment, a device, such as a video decoding device or a video encoding device, may obtain a predictive model for predicting a coding block. The device may select an adjustment model for adjusting the predictive model from a plurality of adjustment models. The device may adjust the predictive model based on the selected adjustment model. The device may process (e.g., encode and / or decode) the coding block based on the adjusted predictive model.

Description

[Technical field]

[0001] (CROSS REFERENCE TO RELATED APPLICATIONS) This application claims the benefit of European Provisional Patent Application No. 22305499.0, filed April 8, 2022, the contents of which are incorporated herein by reference. [Background technology]

[0002] Video coding systems may be used to compress digital video signals to, for example, reduce the storage and / or transmission bandwidth required for such signals. Video coding systems may include, for example, block-based, wavelet-based, and / or object-based systems. Summary of the Invention

[0003] Systems, methods, and means for prediction model adjustment, such as cross component linear model / multimode linear model (CCLM / MMLM) adjustment, are disclosed. In one embodiment, a video decoder may obtain a prediction model for predicting a coding block. Multiple adjustment models may be available for adjusting the prediction model. The video decoder may select an adjustment model for adjusting the prediction model for the coding block from the multiple adjustment models. The video decoder may adjust the prediction model based on the selected adjustment model. The video decoder may decode the coding block based on the adjusted prediction model.

[0004] The video decoder may derive a slope and an offset of the prediction model based on reconstructed samples neighboring the coding block. Adjusting the prediction model may include adjusting the slope and / or the offset of the prediction model based on the selected adjustment model.

[0005] The prediction model may include an inter-component prediction model. The video decoder may determine parameters of the inter-component prediction model for predicting the coding block based on neighboring chroma and luma samples of the coding block. Different adjustment models may be configured to adjust the parameters of the inter-component prediction model differently.

[0006] Different tuning models may be configured to adjust the predictive model differently. For example, an exemplary tuning model may adjust the slope of the predictive model near a minimum value. An exemplary tuning model may adjust the slope of the predictive model near a median value. An exemplary tuning model may adjust the slope of the predictive model near a maximum value. An exemplary tuning model may adjust the predictive model by adjusting the offset of the predictive model and maintaining the same slope of the predictive model.

[0007] The selected adjustment model may be obtained based on an adjustment model instruction in the video data. For example, the device may determine a pivot point of the selected adjustment model based on the adjustment model instruction. Adjusting the prediction model based on the selected adjustment model may include adjusting a slope of the prediction model via the determined pivot point. For example, the device may determine an offset adjustment for the selected adjustment model based on the adjustment model instruction. The video decoder may adjust an offset of the prediction model based on the determined offset adjustment while maintaining the same slope of the prediction model.

[0008] The prediction model for predicting the coding block may include a plurality of prediction models. The selected adjustment model may include a plurality of adjustment models configured to independently adjust the prediction models. The video decoder may determine a first pivot point for adjusting the first prediction model and a second pivot point for adjusting the second prediction model based on the selected adjustment model. The video decoder may adjust a slope of the first prediction model via the determined first pivot point and adjust a slope of the second prediction model via the determined second pivot point. The coding block may be decoded based on the first and second adjusted prediction models.

[0009] In one example, a video encoder may obtain a prediction model for predicting a coding block. The video encoder may select an adjustment model for adjusting the prediction model from a plurality of adjustment models. The video encoder may adjust the prediction model based on the selected adjustment model. The video encoder may encode the coding block based on the adjusted prediction model.

[0010] The video encoder may obtain a plurality of adjustment models and select a suitable adjustment model for adjusting the prediction model. The video encoder may calculate, for a first adjustment model of the plurality of adjustment models, a difference between a sample value of the coding block and a prediction sample value predicted using a prediction model adjusted based on the first adjustment model. The video encoder may calculate, for a second adjustment model of the plurality of adjustment models, a difference between a sample value of the coding block and a prediction sample value predicted using a prediction model adjusted based on the second adjustment model. The adjustment model may be selected based on at least comparing the difference. For example, an adjustment model associated with a minimum difference may be selected for the coding block.

[0011] The prediction model may include an inter-component prediction model. The video encoder may determine a plurality of parameters of the inter-component prediction model based on neighboring chroma and luma samples of the coding block. A first adjustment model and a second adjustment model of the plurality of adjustment models may differently adjust the plurality of parameters of the inter-component prediction model.

[0012] A first adjustment model of the plurality of adjustment models may adjust a slope of the prediction model near a minimum value. A second adjustment model of the plurality of adjustment models may adjust a slope of the prediction model near a median value, and a third adjustment model of the plurality of adjustment models may adjust a slope of the prediction model near a maximum value. The video encoder may test the adjustment models and select a suitable adjustment model that results in a best prediction of the coding block.

[0013] The video encoder may adjust the prediction model based on the selected adjustment model by adjusting an offset of the prediction model and maintaining the same slope of the prediction model. The video encoder may determine a pivot point of the selected adjustment model, and adjusting the prediction model based on the selected adjustment model may include adjusting a slope of the prediction model via the determined pivot point. The video encoder may include, in the video data, an adjustment model indicator that indicates the selected adjustment model and / or the determined pivot point of the selected adjustment model.

[0014] The video encoder may determine an offset adjustment for adjusting the prediction model. The video encoder may adjust an offset of the prediction model based on the determined offset adjustment of the selected adjustment model while maintaining a same slope of the prediction model. The video encoder may include, in the video data, an adjustment model indicator that indicates the selected adjustment model and / or the determined offset adjustment of the selected adjustment model.

[0015] The prediction model for predicting the coding block may include multiple linear prediction models, and the selected adjustment model may include multiple adjustment models for independently adjusting the prediction models. The video encoder may determine a pivot point for adjusting the first linear prediction model and a different pivot point for adjusting the second linear prediction model. Based on the determination, the video encoder may adjust the slope of the linear prediction model via the different pivot point. The video encoder may indicate the selected pivot point via an adjustment model indicator in the video data.

[0016] The systems, methods, and means described herein may involve a decoder. In embodiments, the systems, methods, and means described herein may involve an encoder. In embodiments, the systems, methods, and means described herein may involve a signal (e.g., from an encoder and / or received by a decoder). A computer-readable medium may include instructions for causing one or more processors to perform the methods described herein. A computer program product may include instructions that, when executed by one or more processors, may cause the one or more processors to perform the methods described herein. [Brief description of the drawings]

[0017] [Figure 1A] FIG. 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 communications system shown in FIG. 1A, according to one embodiment. [Figure 1C] FIG. 1B is a system diagram illustrating an example radio access network (RAN) and an example core network (CN) that may be used within the communication system shown in FIG. 1A, according to one embodiment. [Figure 1D]FIG. 1B is a system diagram illustrating a further exemplary RAN and a further exemplary CN that may be used within the communication system shown in FIG. 1A, according to one embodiment. [Diagram 2] 1 illustrates an exemplary video encoder. [Diagram 3] 1 illustrates an exemplary video decoder. [Figure 4] 1 illustrates an example of a system in which various aspects and embodiments may be implemented. [Diagram 5] 1 illustrates an example of the location of the left and top samples and the current block samples involved in CCLM mode. [Figure 6A] Illustrate an example of the effect of the tilt adjustment parameter. [Figure 6B] Illustrate an example of the effect of the tilt adjustment parameter. [Figure 7] 1 illustrates an example of calculating the adjustment values ​​using reconstructed luma and chroma samples. [Figure 8] An example of deriving adjustment values ​​using template samples is illustrated. [Figure 9A] An example of slope correction near an extreme value is illustrated. [Figure 9B] An example of slope correction near an extreme value is illustrated. [Figure 10] An example of modifying the offset value will be illustrated. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0018] A more detailed understanding may be had from the following description, given by way of example in conjunction with the accompanying drawings, in which:

[0019] 1A is a diagram illustrating an example communications system 100 in which one or more disclosed embodiments may be implemented. Communications system 100 may be a multiple access system that provides content, such as voice, data, video, messaging, broadcasts, etc., to multiple wireless users. Communications system 100 may enable multiple wireless users to access such content through sharing of system resources, including wireless bandwidth. For example, the communications system 100 may use 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-tail unique-word DFT-Spread OFDM (ZT UW DTS-s OFDM), unique word OFDM (UW-OFDM), resource block filtered OFDM, filter bank multicarrier (FBMC), and the like.

[0020] 1A, communications system 100 may include wireless transmit / receive units (WTRUs) 102a, 102b, 102c, 102d, RAN 104 / 113, CN 106 / 115, public switched telephone network (PSTN) 108, Internet 110, and other networks 112, although it will be understood 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, wireless paging, mobile phones, personal digital assistants (PDAs), smartphones, laptops, netbooks, personal computers, wireless sensors, hotspots or Mi-Fi devices, Internet of Things (loT) devices, watches or other wearable head-mounted displays (HMDs), vehicles, drones, medical devices and applications (e.g., for remote surgery), industrial devices and applications (e.g., robots and / or other wireless devices operating in an industrial and / or automated processing chain context), consumer electronics devices, devices operating in commercial and / or industrial wireless networks, and the like. Any of the UEs 102a, 102b, 102c, and 102d may be referred to interchangeably as a WTRU.

[0021] The communication 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 communication networks, such as the CN 106 / 115, the Internet 110, and / or other networks 112. By way of example, the base stations 114a, 114b may be a base station transceiver station (BTS), a Node B, an eNode B, a Home Node B, a Home eNode B, a gNB, an NR Node B, a site controller, an access point (AP), a wireless router, etc. Although the base stations 114a, 114b are each illustrated 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.

[0022] 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), a relay node, etc. The base station 114a and / or the 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 cells (not shown). These frequencies may be licensed spectrum, unlicensed spectrum, or a combination of licensed and unlicensed spectrum. A cell may provide wireless service coverage for 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, i.e., one transceiver for each sector of the cell. In one embodiment, the base station 114a may employ multiple-input multiple output (MIMO) technology and may utilize multiple transceivers for each sector of the cell, for example, using beamforming to transmit and / or receive signals in a desired spatial direction.

[0023] The base stations 114a, 114b may communicate with one or more of the WTRUs 102a, 102b, 102c, 102d via an 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).

[0024] More specifically, as noted above, the communications system 100 may be a multiple access system, but may use one or more channel access schemes, such as CDMA, TDMA, FDMA, OFDMA, SC-FDMA, etc. For example, the base stations 114a and the WTRUs 102a, 102b, 102c in the RAN 104 / 113 may implement a radio technology, such as Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access (UTRA), which may establish the air interface 115 / 116 / 117 using wideband CDMA (WCDMA). WCDMA may include communications 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 Packet Access (HSUPA).

[0025] In one 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).

[0026] In one embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as NR radio access, which may establish the air interface 116 using New Radio (NR).

[0027] In one 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 LTE radio access and NR radio access together, e.g., using dual connectivity (DC) principles. Thus, the air interface utilized by the WTRUs 102a, 102b, 102c may be characterized by multiple types of radio access technologies and / or transmissions transmitted to / from multiple types of base stations (e.g., eNBs and gNBs).

[0028] 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), GSM EDGE (GERAN), or the like.

[0029] 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 an office, a home, a vehicle, a campus, an industrial facility, an air corridor (e.g., for use by drones), a road, etc. 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 one 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 establish a picocell or a femtocell using a cellular-based RAT (e.g., WCDMA, CDMA2000, GSM, LTE, LTE-A, LTE-A Pro, NR, etc.). As shown in FIG. 1A, the base station 114b may have a direct connection to the Internet 110. Thus, the base station 114b may not need to access the Internet 110 via the CN 106 / 115.

[0030] 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, for example, different throughput requirements, latency requirements, error tolerance requirements, reliability requirements, data throughput requirements, mobility requirements, etc. 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 appreciated that the RAN 104 / 113 and / or the CN 106 / 115 may communicate directly or indirectly with other RANs that use 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) using GSM, UMTS, CDMA2000, WiMAX, E-UTRA, or WiFi radio technology.

[0031] The CN 106 / 115 may also act 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) of the TCP / IP Internet protocol suite. The networks 112 may include wired and / or wireless communication networks owned and / or operated by other service providers. For example, the networks 112 may include another CN connected to one or more RANs, which may use the same RAT as the RANs 104 / 113 or a different RAT.

[0032] Some or all of the WTRUs 102a, 102b, 102c, 102d in the communications system 100 may include multi-mode capabilities (e.g., the WTRUs 102a, 102b, 102c, 102d may include multiple transceivers for communicating with different wireless networks over different wireless links). For example, the WTRU 102c shown in FIG. 1A may be configured to communicate with a base station 114a, which may employ a cellular-based wireless technology, and a base station 114b, which may employ an IEEE 802 wireless technology.

[0033] Figure 1B is a system diagram illustrating an example WTRU 102. As shown in Figure 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 sub-combination of the foregoing elements while remaining consistent with an embodiment.

[0034] 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 associated 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. Although FIG. 1B illustrates 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.

[0035] The transmit / receive element 122 may be configured to transmit or receive signals to or 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 one 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 appreciated that the transmit / receive element 122 may be configured to transmit and / or receive any combination of wireless signals.

[0036] 1B as a single element, the WTRU 102 may include any number of transmit / receive elements 122. More specifically, the WTRU 102 may employ 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.

[0037] The transceiver 120 may be configured to modulate signals 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.

[0038] The processor 118 of the WTRU 102 may be coupled to and may receive user-entered 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 also output user data to the speaker / microphone 124, the keypad 126, and / or the display / touchpad 128. In addition, the processor 118 may access 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 on a server or home computer (not shown).

[0039] 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 in the WTRU 102. The power source 134 may be any suitable device for providing power to 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.

[0040] 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 in lieu of, information from the GPS chipset 136, the WTRU 102 may receive location information from a base station (e.g., base stations 114a, 114b) over the air interface 116 and / or 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 by way of any suitable position determination method while remaining consistent with an embodiment.

[0041] 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 electronic 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 modulated (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 peripherals 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.

[0042] 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 to reduce and or substantially eliminate self-interference via either hardware (e.g., a choke) or signal processing via a processor (e.g., via a separate processor (not shown) or via the processor 118). In one embodiment, the WRTU 102 may include a half-duplex radio for transmission and reception of either 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)).

[0043] 1C is a system diagram illustrating the RAN 104 and the CN 106, according to one embodiment. As mentioned 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.

[0044] The RAN 104 may include eNodeBs 160a, 160b, 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, 160c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 116. In an embodiment, the eNodeBs 160a, 160b, 160c may implement MIMO technology. Thus, the eNodeB 160a may, for example, use multiple antennas to transmit wireless signals to and / or receive wireless signals from the WTRU 102a.

[0045] 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 one another via an X2 interface.

[0046] 1C may include a mobility management entity (MME) 162, a serving gateway (SGW) 164, and a packet data network (PDN) gateway (or PGW) 166. Although each of the foregoing elements is illustrated as part of the CN 106, it will be understood that any of these elements may be owned and / or operated by an entity other than the CN operator.

[0047] The MME 162 may be connected to each of the eNodeBs 162a, 162b, 162c in the RAN 104 via an S1 interface and may function as a control node. For example, the MME 162 may be responsible for authenticating users of the WTRUs 102a, 102b, 102c, activating / deactivating bearers, selecting a particular serving gateway during initial attachment 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.

[0048] 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 and 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.

[0049] 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.

[0050] 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 land-line communications 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.

[0051] Although the WTRU is depicted in FIGS. 1A-1D as a wireless terminal, in certain representative embodiments, it is contemplated that such a terminal may use a wired communications interface (e.g., temporarily or permanently) with the communications network.

[0052] In an exemplary embodiment, the other network 112 may be a WLAN.

[0053] A WLAN in infrastructure Basic Service Set (BSS) mode may have an Access Point (AP) of the BSS and one or more stations (STAs) associated with the AP. The AP may have access or interface to a Distribution System (DS) or another type of wired / wireless network that carries traffic into and / or out of the BSS. Traffic originating from outside the BSS to the STA may arrive through the AP and be delivered to the STA. Traffic originating from the STA to a destination outside the BSS may be sent to the AP to be delivered to the respective destination. Traffic between STAs within the BSS may be sent, for example, through the AP, where the source STA may send traffic to the AP, which 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 between (e.g., directly between) the source STA and the destination STA using a 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 (e.g., all of the STAs) within or using the IBSS may communicate directly with each other. The IBSS mode of communication may be referred to herein as an "ad-hoc" communication mode.

[0054] When using an 802.11ac infrastructure mode of operation or a similar mode of operation, an AP may transmit a beacon 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 that is dynamically set via signaling. The primary channel may be the operating channel of the BSS, but may be used by STAs to establish a connection with the AP. In certain representative embodiments, 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., all STAs), 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. One STA (e.g., only one station) may transmit at any given time in a given BSS.

[0055] A High Throughput (HT) STA may use a 40 MHz wide channel for communication, which may be formed, for example, through a combination of a primary 20 MHz channel and adjacent or non-adjacent 20 MHz channels.

[0056] A Very High Throughput (VHT) STA may support 20 MHz, 40 MHz, 80 MHz, and / or 160 MHz wide channels. A 40 MHz and / or 80 MHz channel may be formed by combining multiple contiguous 20 MHz channels. A 160 MHz channel may be formed by combining eight contiguous 20 MHz channels or by combining two non-contiguous 80 MHz channels, which may be referred to as an 80+80 configuration. For the 80+80 configuration, after channel encoding, the data may pass 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 to 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 transmitted to the Medium Access Control (MAC).

[0057] Sub-1 GHz operating modes are 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 TV White Space (TVWS) spectrum, and 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 capabilities, including certain capabilities, for example, support for (e.g., support only for) certain and / or limited bandwidths. MTC devices may include batteries with above-threshold battery life (e.g., to maintain very long battery life).

[0058] WLAN systems that may support 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 maximum common operating bandwidth supported by all STAs in the BSS. The bandwidth of the primary channel may be configured and / or limited by the STAs among all STAs operating in the BSS that support the smallest bandwidth operating mode. In an 802.11ah embodiment, the primary channel may be 1 MHz wide for STAs (e.g., MTC-type devices) that support (e.g., only) the 1 MHz mode, 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) configuration may depend on the status of the primary channel. For example, if the primary channel is active due to a STA (that only supports the 1 MHz mode of operation) transmitting to the AP, the entire available frequency band may be considered active even though most of the frequency band may remain dormant and available.

[0059] In the United States, the available frequency bands that can be used by 802.11ah are 902MHz to 928MHz. In South Korea, the available frequency bands are 917.5MHz to 923.5MHz. In Japan, the available frequency bands are 916.5MHz to 927.5MHz. The total bandwidth available for 802.11ah is 6MHz to 26MHz depending on the country code.

[0060] 1D is a system diagram illustrating the RAN 113 and the CN 115, according to one embodiment. As mentioned above, the RAN 113 may employ NR radio technology and communicate with the WTRUs 102a, 102b, 102c over the air interface 116. The RAN 113 may also communicate with the CN 115.

[0061] The RAN 113 may include gNBs 180a, 180b, 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, 180c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 116. In an embodiment, the gNBs 180a, 180b, 180c may implement MIMO technology. For example, the gNBs 180a, 108b may utilize beamforming to transmit signals to and / or receive signals from the gNBs 180a, 180b, 180c. Thus, the gNB 180a may transmit and / or receive wireless signals to and from the WTRU 102a, for example, using multiple antennas. In one 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 one embodiment, the gNBs 180a, 180b, 180c may implement Coordinated Multi-Point (CoMP) technology. For example, the WTRU 102a may receive coordinated transmissions from the gNBs 180a and 180b (and / or gNB 180c).

[0062] The WTRUs 102a, 102b, 102c may communicate with the gNBs 180a, 180b, 180c using transmissions associated with 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 different lengths of absolute time).

[0063] 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, etc.). 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 and connect to a gNB 180a, 180b, 180c while also communicating with and connecting to another RAN, such as an eNodeB 160a, 160b, 160c. For example, the WTRUs 102a, 102b, 102c may implement DC principles 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.

[0064] 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, 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 via an Xn interface.

[0065] 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. Although each of the foregoing elements is illustrated as part of the CN 115, it will be understood that any of these elements may be owned and / or operated by an entity other than the CN operator.

[0066] 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 function 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, mobility management, etc. Network slicing may be used by the AMF 182a, 182b to customize the CN support of the WTRUs 102a, 102b, 102c based on the type of service utilizing the WTRUs 102a, 102b, 102c. For example, different network slices may be established for different use cases such as services relying on ultra-reliable low latency (URLLC) access, services relying on enhanced massive mobile broadband (eMBB) access, 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.

[0067] The SMFs 183a, 183b may be connected to the AMFs 182a, 182b in the CN 115 via an N11 interface. The SMFs 183a, 183b may also be connected to the UPFs 184a, 184b in the CN 115 via an N4 interface. The SMFs 183a, 183b may select and control the UPFs 184a, 184b and configure the routing of traffic through the UPFs 184a, 184b. The SMFs 183a, 183b may perform other functions such as managing and allocating UE IP addresses, managing PDU sessions, controlling policy enforcement and QoS, providing downlink data notification, etc. The PDU session type may be IP-based, non-IP-based, Ethernet-based, etc.

[0068] 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 184, 184b may perform other functions, such as routing and forwarding packets, enforcing user plane policies, supporting multi-homed PDU sessions, handling user plane QoS, buffering downlink packets, providing mobility anchoring, etc.

[0069] 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.

[0070] 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 functions.

[0071] The emulation device may be designed to perform one or more tests of other devices in a lab environment and / or 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 the tests using terrestrial wireless communication.

[0072] The one or more emulation devices may perform one or more functions, inclusive, while not being implemented / deployed as part of a wired and / or wireless communication network. For example, the emulation devices may be utilized in test scenarios in a test lab and / or in an undeployed (e.g., test) wired and / or wireless communication network to perform testing 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.

[0073] This application describes various aspects, including tools, features, examples, models, techniques, and the like. Many of these aspects are described with specificity and often in a potentially limiting manner to at least illustrate their individual characteristics. However, this is for purposes of clarity of description and does not limit the applicability or scope of the aspects. In fact, all of the different aspects may be combined and interchanged to provide further aspects. Moreover, these aspects may likewise be combined and interchanged with aspects described in prior applications.

[0074] Aspects described and contemplated in this application may be implemented in many different forms. Figures 5-10 described herein may provide examples, but other examples are contemplated. Discussion of Figures 5-10 is not intended to limit the scope of implementations. At least one of the above aspects generally relates to video encoding and decoding, and at least one other aspect generally relates to transmitting a generated or encoded bitstream. These and other aspects may be implemented as a method, an apparatus, a computer-readable storage medium having stored thereon instructions for encoding or decoding video data according to any of the described methods, and / or a computer-readable storage medium having stored thereon a bitstream generated according to any of the described methods.

[0075] In this application, the terms "reconstructed" and "decoded" may be used interchangeably, the terms "pixel" and "sample" may be used interchangeably, and the terms "image", "picture", and "frame" may be used interchangeably.

[0076] Various methods are described herein, each of which includes one or more steps or acts for achieving the described method. Unless a specific order of steps or acts is required for proper operation of the method, the order and / or use of specific steps and / or acts may be modified or combined. Additionally, terms such as "first", "second", etc. may be used in various embodiments to modify elements, components, steps, operations, etc., such as, for example, "first decode" and "second decode". The use of such terms does not imply any ordering to the modified operations, unless specifically required. Thus, in this embodiment, the first decode need not be performed before the second decode, but may occur, for example, before, during, or during a period of overlap with the second decode.

[0077] Various methods and other aspects described herein may be used to modify modules, such as the decoding modules, of the video encoder 200 and decoder 300, as shown in Figures 2 and 3. Moreover, the subject matter disclosed herein may apply to any type, format, or version of video coding, whether described in a standard or recommendation, whether existing or developed in the future, and to extensions of any such standards and recommendations, for example. Unless otherwise indicated or technically impossible, aspects described herein may be used individually or in combination.

[0078] In the embodiments described in this application, various numerical values ​​are used, such as those referenced in the embodiments shown and described in connection with Figures 9 and 10, Equation (5), Table 1, the number of intra modes, downsampling ratios, number of adjustment values, etc. These and other specific values ​​are provided for purposes of illustrating the embodiments, and the described aspects are not limited to these specific values.

[0079] 2 illustrates an exemplary video encoder. Although variations of the exemplary encoder 200 are contemplated, the encoder 200 is described below for clarity purposes without describing all possible variations.

[0080] Before encoding, a video sequence may undergo pre-encoding processing (201), such as applying a color transformation to the input color picture (e.g., from RGB 4:4:4 to YCbCr 4:2:0) or performing a remapping of the input picture components to obtain a compression-resistant signal distribution (e.g., using histogram equalization of one of the color components). Metadata may be associated with the pre-processing and attached to the bitstream.

[0081] In the encoder 200, a picture is coded by the encoder elements, as described below. The picture to be coded is divided (202) and processed, for example, in units of coding units (CUs). Each unit is coded, for example, using either intra-mode or inter-mode. When a unit is coded in intra-mode, it performs intra prediction (260). In inter-mode, motion estimation (275) and motion compensation (270) are performed. The encoder decides (205) whether to use intra-mode or inter-mode to code the unit, and indicates the decision, for example, by a prediction mode flag. A prediction residual is calculated (210), for example, by subtracting the prediction block from the original image block.

[0082] The prediction residual is then transformed (225) and quantized (230). The quantized transform coefficients, as well as motion vectors and other syntax elements such as picture partition information, are entropy coded (245) to output a bitstream. The encoder can skip the transform and apply quantization directly to the untransformed residual signal. The encoder can bypass both the transform and quantization, i.e., the residual is coded directly without applying a transform or quantization process.

[0083] The encoder decodes the coded block to provide a reference for further prediction. To decode the prediction residual, the quantized transform coefficients are dequantized (240) and inverse transformed (250). The decoded prediction residual and the predicted block are combined (255) to reconstruct an image block. An in-loop filter (265) is applied to the reconstructed picture to perform, for example, deblocking / Sample Adaptive Offset (SAO) / Adaptive Loop filter (ALF) filtering to reduce coding artifacts. The filtered image is stored in a reference picture buffer (280).

[0084] 3 illustrates an example of a video decoder. In the exemplary decoder 300, the bitstream is decoded by decoder elements as described below. The video decoder 300 generally performs a decoding path that is the inverse of the encoding path described in FIG. 2. Additionally, the encoder 200 generally performs video decoding as part of the video data encoding.

[0085] In particular, the decoder input includes a video bitstream, which may be generated by the video encoder 200. First, the bitstream is entropy decoded (330) to obtain transform coefficients, prediction modes, motion vectors, and other coded information. Picture partition information indicates how the picture is partitioned. Thus, the decoder may partition the picture according to the decoded picture partition information (335). To decode the prediction residual, the transform coefficients are dequantized (340) and inverse transformed (350). The decoded prediction residual and the predicted block are combined (355) to reconstruct an image block. The predicted block may be obtained from intra prediction (360) or from motion-compensated prediction (i.e., inter prediction) (375) (370). An in-loop filter (365) is applied to the reconstructed image. The filtered image is stored in a reference picture buffer (380). In an embodiment, for a given picture, the contents of the reference picture buffer 380 on the decoder 300 side may be identical to the contents of the reference picture buffer 280 on the encoder 200 side (eg, for the same picture).

[0086] The decoded picture may further undergo post-decoding processing (385), such as an inverse color conversion (e.g., from YCbCr 4:2:0 to RGB 4:4:4) or inverse remapping that performs the inverse of the remapping process performed in the pre-encoding processing (201). The post-decoding processing may use metadata derived in the pre-encoding processing and signaled in the bitstream. In an embodiment, the decoded image (e.g., after application of an in-loop filter (365) and / or after post-decoding processing (385), if post-decoding processing is used) may be sent to a display device for rendering to a user.

[0087] FIG. 4 illustrates an example of a system in which various aspects and embodiments described herein may be implemented. System 400 may be embodied as a device including various components described below and configured to implement one or more of the aspects described herein. Examples of such devices include various electronic devices, such as, but not limited to, personal computers, laptop computers, smartphones, tablet computers, digital multimedia set-top boxes, digital television receivers, personal video recording systems, connected appliances, and servers. The elements of system 400, singly or in combination, may be embodied in a single integrated circuit (IC), multiple ICs, and / or separate components. For example, in at least one embodiment, the processing and encoder / decoder elements of system 400 are distributed across multiple ICs and / or separate components. In various embodiments, system 400 is communicatively coupled to one or more other systems or other electronic devices, for example, via a communication bus or through dedicated input and / or output ports. In various embodiments, system 400 is configured to implement one or more of the aspects described herein.

[0088] The system 400 includes at least one processor 410 configured to execute instructions loaded therein, for example to implement various aspects described herein. The processor 410 can include embedded memory, input / output interfaces, and various other circuits known in the art. The system 400 includes at least one memory 420 (e.g., a volatile memory device and / or a non-volatile memory device). The system 400 includes a storage device 440, which can include non-volatile memory and / or volatile memory, including but not limited to Electrically Erasable Programmable Read-Only Memory (EEPROM), Read-Only Memory (ROM), Programmable Read-Only Memory (PROM), Random Access Memory (RAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Flash, magnetic disk drive, and / or optical disk drive. Storage device(s) 440 may include, by way of non-limiting example, internal storage devices, attached storage devices (including removable and non-removable storage devices), and / or network-accessible storage devices.

[0089] The system 400 includes an encoder / decoder module 430 configured to process data to provide, for example, encoded or decoded video, and the encoder / decoder module 430 may include its own processor and memory. The encoder / decoder module 430 represents a module that may be included within a device to perform encoding and / or decoding functions. As is known, a device may include one or both of an encoding module and a decoding module. It is noted that the encoder / decoder module 430 may be implemented as a separate element of the system 400 or may be incorporated within the processor 410 as a combination of hardware and software known to those skilled in the art.

[0090] Program code to be loaded into the processor 410 or the encoder / decoder 430 to implement various aspects described herein may be stored in the storage device 440 and then loaded into the memory 420 for execution by the processor 410. According to various embodiments, one or more of the processor 410, the memory 420, the storage device 440, and the encoder / decoder module 430 may store one or more of various items during performance of the processes described herein. Such stored items may include, but are not limited to, input video, decoded video or portions of decoded video, bitstreams, matrices, variables, and intermediate or final results from the processing of equations, expressions, operations, and computational logic.

[0091] In an embodiment, memory internal to the processor 410 and / or the encoder / decoder module 430 is used to store instructions and provide working memory for processing required during encoding or decoding. However, in other embodiments, memory external to the processing device (e.g., the processing device can be either the processor 410 or the encoder / decoder module 430) is used for one or more of these functions. The external memory may be the memory 420 and / or the storage device 440, e.g., dynamic volatile memory and / or non-volatile flash memory. In some embodiments, an external non-volatile flash memory is used, for example, to store the television's operating system. In at least one embodiment, a high-speed external dynamic volatile memory, such as a RAM, is used as working memory for video encoding and decoding operations.

[0092] Inputs to the elements of system 400 may be provided through various input devices, as shown in block 445. Such input devices may include, but are not limited to, (i) a radio frequency (RF) section that receives, for example, RF signals transmitted over the air by a broadcast station, (ii) a component (COMP) input terminal (or set of COMP input terminals), (iii) a universal serial bus (USB) input terminal, and / or (iv) a High Definition Multimedia Interface (HDMI) input terminal. Other examples include composite video, not shown in FIG. 4.

[0093] In various embodiments, the input devices of block 445 have associated respective input processing elements as known in the art. For example, the RF section may be associated with elements suitable for (i) selecting a desired frequency (also referred to as selecting a signal or band-limiting a signal to a band of frequencies), (ii) down-converting the selected signal, (iii) band-limiting again to a narrower frequency band to select a signal frequency band, which in certain embodiments may be referred to as a channel (for example), (iv) demodulating the down-converted band-limited signal, (v) performing error correction, and / or (vi) demultiplexing to select a desired data packet stream. The RF section of various embodiments includes one or more elements for performing these functions, such as a frequency selector, a signal selector, a band limiter, a channel selector, a filter, a down-converter, a demodulator, an error corrector, and a demultiplexer. The RF section may include a tuner to perform various of these functions, including, for example, down-converting a received signal to a lower frequency (e.g., an intermediate frequency or a near-baseband frequency) or to baseband. In one set-top box embodiment, the RF section and its associated input processing elements receive RF signals transmitted over a wired (e.g., cable) medium and perform frequency selection by filtering, down-converting, and filtering again to a desired frequency band. Various embodiments rearrange the order of the above-described (and other) elements, remove some of these elements, and / or add other elements to perform similar or different functions. Adding elements can include inserting elements between existing elements, such as, for example, inserting amplifiers and analog-to-digital converters. In various embodiments, the RF section includes an antenna.

[0094] The USB and / or HDMI terminals may include respective interface processors for connecting the system 400 to other electronic devices via USB and / or HDMI connections. It should be appreciated that various aspects of the input processing, e.g., Reed-Solomon error correction, may be implemented, for example, in a separate input processing IC or in the processor 410, as desired. Similarly, aspects of the USB or HDMI interface processing may be implemented, for example, in a separate interface IC or in the processor 410, as desired. The demodulated, error corrected, and demultiplexed streams are provided to various processing elements, including, for example, the processor 410 and an encoder / decoder 430 operating in combination with memory and storage elements, to process the data streams necessary for presentation to an output device.

[0095] The various elements of system 400 may be provided within an integrated housing in which the various elements may be interconnected and transmit data between them using a suitable connection arrangement 425, such as an internal bus known in the art, including an Inter-IC (I2C) bus, hardwired, and printed circuit boards.

[0096] System 400 includes a communication interface 450 that enables communication with other devices over a communication channel 460. Communication interface 450 may include, but is not limited to, a transceiver configured to transmit and receive data over communication channel 460. Communication interface 450 may include, but is not limited to, a modem or a network card, and communication channel 460 may be implemented in a wired and / or wireless medium, for example.

[0097] Data is streamed or otherwise provided to system 400 in various embodiments using a wireless network such as a Wi-Fi network, e.g., IEEE 802.11 (IEEE refers to the Institute of Electrical and Electronics Engineers). The Wi-Fi signal in these embodiments is received via communication channel 460 and communication interface 450 adapted for Wi-Fi communication. Communication channel 460 in these embodiments is typically connected to an access point or router that provides access to external networks, including the Internet, to enable streaming applications and other over-the-top communications. Other embodiments provide streamed data to system 400 using a set-top box that delivers data via an HDMI connection in input block 445. Still other embodiments provide streamed data to system 400 using an RF connection in input block 445. As noted above, various embodiments provide data in a non-streaming manner. Additionally, various embodiments use wireless networks other than Wi-Fi, e.g., cellular networks or Bluetooth networks.

[0098] System 400 can provide output signals to various output devices, including a display 475, speakers 485, and other peripheral devices 495. Display 475 in various embodiments includes one or more of a touch screen display, an organic light emitting diode (OLED) display, a curved display, and / or a foldable display, for example. Display 475 can be for a television, a tablet, a laptop, a mobile phone, or other device. Furthermore, display 475 can be integrated with other components (e.g., as in a smart phone) or can be separate (e.g., an external monitor for a laptop). Other peripheral devices 495 in various embodiments include one or more of a stand-alone digital video disc (or digital versatile disc) (DVD for both terms), a disc player, a stereo system, and / or a lighting system. Various embodiments use one or more peripheral devices 495 that provide functionality based on the output of system 400. For example, a disc player performs the function of playing the output of system 400.

[0099] In various embodiments, control signals are communicated between system 400 and display 475, speaker 485, or other peripheral devices 495 using signaling such as AV.Link, Consumer Electronics Control (CEC), or other communication protocols that allow control between devices with or without user intervention. Output devices may be communicatively coupled to system 400 via dedicated connections through respective interfaces 470, 480, and 490. Alternatively, output devices may be connected to system 400 via communication interface 450 using communication channel 460. Display 475 and speaker 485 may be integrated into a single unit with other components of system 400 in an electronic device such as, for example, a television. In various embodiments, display interface 470 includes a display driver, such as, for example, a timing controller (TCon) chip.

[0100] Display 475 and speakers 485 may alternatively be separate from one or more of the other components, for example, if the RF portion of input 445 is part of a separate set-top box. In various embodiments in which display 475 and speakers 485 are external components, output signals may be provided via dedicated output connections including, for example, an HDMI port, a USB port, or a COMP output.

[0101] These embodiments may be performed by the processor 410, or by computer software implemented by hardware, or by a combination of hardware and software. As a non-limiting example, these embodiments may be implemented by one or more integrated circuits. The memory 420 may be of any type suitable for the technology environment, and may be implemented using any suitable data storage technology, such as, as non-limiting examples, optical memory devices, magnetic memory devices, semiconductor-based memory devices, fixed memories, and removable memories. The processor 410 may be of any type suitable for the technology environment, and may include, as non-limiting examples, one or more of a microprocessor, a general-purpose computer, a special-purpose computer, and a processor based on a multi-core architecture.

[0102] Various implementations involve decoding. As used herein, "decoding" can encompass all or part of the processes performed on a received encoded sequence to provide a final output suitable for, for example, a display. In various embodiments, such processes include processes typically performed by a decoder, such as one or more of entropy decoding, inverse quantization, inverse transform, and differential decoding. In various embodiments, such processes also or alternatively include processes performed by a decoder of various implementations described herein, such as obtaining a prediction model for predicting a coding block, selecting an adjustment model for adjusting the prediction model from a plurality of adjustment models, adjusting the prediction model based on the selected adjustment model, and decoding the coding block based on the adjusted prediction model.

[0103] As a further example, in one embodiment, "decoding" refers to entropy decoding only, in another embodiment, "decoding" refers to differential decoding only, and in another embodiment, "decoding" refers to a combination of entropy decoding and differential decoding. Whether the phrase "decoding process" is intended to refer specifically to a subset of operations or to the broader decoding process as a whole will be clear based on the context of the specific description and will be well understood by one of ordinary skill in the art.

[0104] Various implementations involve encoding. Similar to the above discussion regarding "decoding," "encoding" as used herein can encompass, for example, all or part of the processes performed on an input video sequence to produce an encoded bitstream. In various embodiments, such processes include processes typically performed by an encoder, such as one or more of partitioning, differential encoding, transforming, quantizing, and entropy encoding. In various embodiments, such processes also or alternatively include processes performed by a decoder of various implementations described herein, such as obtaining a prediction model for predicting a coding block, selecting an adjustment model for adjusting the prediction model from a plurality of adjustment models, adjusting the prediction model based on the selected adjustment model, and encoding the coding block based on the adjusted prediction model.

[0105] As a further example, in one embodiment, "encoding" refers to only entropy encoding, while in another embodiment, "encoding" refers to only differential encoding, while in another embodiment, "encoding" refers to a combination of differential and entropy encoding. Whether the phrase "encoding process" is intended to refer specifically to a subset of operations or to the broader encoding process as a whole will be clear based on the context of the specific description and will be well understood by one of ordinary skill in the art.

[0106] It should be noted that syntax elements used herein, such as coding syntax for an indication that a pivot point is to be determined, an adjustment model indicator indicating that an adjustment model is to be used to adjust a predictive model, and / or a first pivot point indicator and a second pivot point indicator indicating that a first pivot point and a second pivot point, respectively, are to be determined for adjusting a predictive model associated with a coding block, are descriptive terms and thus do not preclude the use of other syntax element names or functions.

[0107] Where a figure is presented as a flow diagram, it should be understood that the figure also provides a block diagram of the corresponding apparatus. Similarly, where a figure is presented as a block diagram, it should be understood that the figure also provides a flow diagram of the corresponding method / process.

[0108] The implementations and aspects described herein may be implemented, for example, in a method or process, an apparatus, a software program, a data stream, or a signal. Even if discussed in the context of only a single implementation form (e.g., discussed only as a method), the implementation of the discussed features may also be implemented in other forms (e.g., an apparatus or a program). An apparatus may be implemented, for example, in appropriate hardware, software, and firmware. A method may be implemented, for example, in a processor, which generally refers to a processing device and includes, for example, a computer, a microprocessor, an integrated circuit, or a programmable logic device. Processors also include communication devices, such as, for example, computers, cellular phones, portable / personal digital assistants ("PDAs"), and other devices that facilitate communication of information between end users.

[0109] References to "one example" or "an example" or "one implementation" or "an implementation," as well as other variations thereof, mean that a particular feature, structure, characteristic, etc. described in connection with an embodiment is included in at least one embodiment. Thus, the appearances of the phrases "in one example" or "in an example" or "in one implementation" or "in an implementation" in various places throughout this application, as well as any other variations, are not necessarily all referring to the same embodiment.

[0110] Additionally, the application may refer to "determining" various information. Determining information may include, for example, one or more of estimating information, calculating information, predicting information, or retrieving information from a memory. Obtaining may include receiving, retrieving, constructing, generating, and / or determining.

[0111] Additionally, the application may refer to "accessing" various information. Accessing information may include, for example, one or more of receiving information, retrieving information (e.g., from a memory), storing information, moving information, copying information, calculating information, determining information, predicting information, or estimating information.

[0112] Additionally, the application may refer to "receiving" various information. Receiving, like "accessing," is intended to be a broad term. Receiving information may include, for example, one or more of accessing information or retrieving information (e.g., from a memory). Furthermore, "receiving" generally involves in some manner an operation, such as, for example, storing information, processing information, transmitting information, moving information, copying information, erasing information, calculating information, determining information, predicting information, or estimating information.

[0113] For example, in the case of "A / B," "A and / or B," and "at least one of A and B," it should be understood that the use of any of the following " / ," "and / or," and "at least one of" is intended to encompass the selection of only the first enumerated alternative (A), or the selection of only the second enumerated alternative (B), or the selection of both alternatives (A and B). As a further example, in the case of "A, B, and / or C" and "at least one of A, B, and C," such language is intended to encompass the selection of only the first enumerated alternative (A), or the selection of only the second enumerated alternative (B), or the selection of only the third enumerated alternative (C), or the selection of only the first and second enumerated alternatives (A and B), or the selection of only the first and third enumerated alternatives (A and C), or the selection of only the second and third enumerated alternatives (B and C), or the selection of all three alternatives (A and B and C). This can be expanded as many times as the items listed, as would be apparent to one of ordinary skill in this and related arts.

[0114] Also, as used herein, the term "signaling" specifically means to indicate something to a corresponding decoder. Encoder signals may include, for example, signals indicating whether the encoder has chosen to implicitly or explicitly determine one or more adjustment values. In this way, in one embodiment, the same parameters are used on both the encoder and decoder sides. Thus, for example, the encoder may transmit a particular parameter to the decoder so that the decoder can use the same particular parameter (explicit signaling). Conversely, if the decoder already has the particular parameter as well as other parameters, it may use signaling without transmission just to allow the decoder to know and select the particular parameter (implicit signaling). By avoiding transmission of any actual function, bit savings are realized in various embodiments. It should be understood that signaling may be achieved in various ways. For example, in various embodiments, one or more syntax elements, flags, etc. are used to signal information to a corresponding decoder. Although the above relates to the verb form of the term "signal", the term "signal" may also be used as a noun in this specification.

[0115] As will be apparent to one of ordinary skill in the art, implementations may generate a variety of signals formatted to carry information that may be, for example, stored or transmitted. Information may include, for example, instructions for performing a method or data generated by one of the described implementations. For example, a signal may be formatted to carry a bit stream of the described embodiments. Such a signal may be formatted, for example, as an electromagnetic wave (e.g., using a radio frequency portion of the spectrum) or as a baseband signal. Formatting may include, for example, encoding a data stream and modulating a carrier wave with the encoded data stream. The information that the signal carries may be, for example, analog information or digital information. The signal may be transmitted by a variety of different wired or wireless links, as is well known. The signal may be stored in, accessed from, or received from a processor-readable medium.

[0116] Many examples are described herein. Features of the examples may be provided alone or in any combination across various claim categories and types. Furthermore, examples may include one or more of the features, devices, or aspects described herein, alone or in any combination across various claim categories and types. For example, features described herein may be embodied in a bitstream or signal that includes information generated as described herein. The information may enable a decoder to decode the bitstream, encoder, bitstream, and / or decoder according to any of the described embodiments. For example, features described herein may be implemented by generating and / or transmitting and / or receiving and / or decoding a bitstream or signal. For example, features described herein may be implemented as a method, process, apparatus, medium storing instructions, medium storing data, or signal. For example, features described herein may be implemented by a TV, a set-top box, a mobile phone, a tablet, or other electronic device that performs decoding. A TV, set-top box, mobile phone, tablet, or other electronic device may display (e.g., using a monitor, screen, or other type of display) the resulting image (e.g., an image from the residual reconstruction of the video bitstream). A TV, set-top box, mobile phone, tablet, or other electronic device may receive a signal that includes the encoded image and perform decoding.

[0117] Features described herein may be associated with adjusting a cross-component linear model (CCLM) and a multi-model linear model (MMLM). CCLM and MMLM may be chroma prediction modes with a prediction signal generated from a luma component. CCLM and MMLM may be modified by a scale factor and a slope. The slope value may be modified. For example, the slope may be adjusted based on reconstructed pixels (e.g., reconstructed luma and chroma samples) surrounding the current block.

[0118] Inter-component prediction may be performed. For example, template-based CCLM / MMLM with (e.g., implicit) gradient adjustment may be performed (e.g., in the context of video coding). CCLM and MMLM may be chroma prediction modes. Predictions of chroma samples may be generated from luma samples in the coding block. The prediction model may include a bias factor and a gradient. The gradient value may be adjusted, for example, based on reconstructed pixels surrounding the current chroma block.

[0119] In inter-component prediction, inter-component redundancy can be reduced, for example, by modeling the relationship between luma and chroma components. For example, in CCLM, linear model parameters can be derived from reconstructed luma and chroma samples surrounding the current block. Signaling can be reduced or avoided, for example, and the same model derivation process (e.g., CCLM) can be repeated at the decoder side.

[0120] CCLM can be extended to MMLM, for example, when using multiple linear models. In an embodiment, MMLM can include multiple CCLMs (e.g., two CCLMs). Parameters for multiple prediction models can be derived at the encoder side and the decoder side.

[0121] In an embodiment, the slope may be adjusted by testing different values ​​at the encoder side, and the slope adjustment value may be signaled to the decoder (e.g., signaled by the encoder to the decoder).

[0122] The slope adjustment may be obtained, for example, by deriving a slope adjustment value at the encoder side and the decoder side. In an embodiment, multiple slopes may be determined for multiple adjustment models. The prediction model may be adjusted based on the selected adjustment model. Signaling overhead may be reduced (e.g., eliminated) and / or the bit rate may be modified (e.g., by deriving a slope adjustment value at the encoder side and the decoder side).

[0123] The CCLM prediction mode may be used in video coding. Chroma samples may be predicted based on reconstructed luma samples (e.g., for the same coding block) by, for example, using a linear model. The linear model may be implemented, for example, according to Equation (1): pred C (i,j)=α·rec L '(i,j)+β (1) As shown by way of example in equation (1), pred C (i,j) may represent the predicted chroma sample in the CU. As shown by way of example in Equation (1), rec L '(i,j) may represent the downsampled reconstructed luma sample of the CU.

[0124] The CCLM parameters (e.g., α and β) may be derived based on (e.g., at most four) adjacent chroma samples and the corresponding downsampled luma samples. The current chroma block dimensions may be W×H. In an example, W″ and H′ may be set according to the following logic: For example, when LM mode is applied, W'=W, H'=H, For example, when the LM-A mode is applied, W'=W+H, and / or For example, when LM-L mode is applied, H'=H+W.

[0125] The top adjacent position may be denoted as S[0,-1]...S[W'-1,-1], and the left adjacent position may be denoted as S[-1,0]...S[-1,H'-1]. The four samples may be selected (e.g., according to the example logic) as follows: For example, when LM mode is applied and both upper and left adjacent samples are available, S[W' / 4,-1], S[3 * W' / 4,-1], S[-1,H' / 4], S[-1,3 * H' / 4], For example, when LM-A mode is applied or only the top adjacent samples are available, S[W' / 8,-1]1], S[3 * W' / 8,-1], S[5 * W' / 8,-1], S[7 * W' / 8,-1], and / or For example, when LM-L mode is applied or only the left adjacent sample is available, S[-1,H' / 8], S[-1,3 * H' / 8], S[-1,5 * H' / 8], S[-1,7 * H' / 8].

[0126] In an embodiment, the four adjacent luma samples at the selected location are 0 A and x 1 A Two larger values, denoted as x 0 B and x 1 B The corresponding chroma sample value is y 0 A , y 1 A , y 0 B , and y 1 B In the embodiment, x A , x B , y A , and y B can be derived, for example, according to equations (2a-2d): X a =(x 0 A +x 1 A +1)>>1 (2a) X b =(x 0 B +x 1 B +1)>>1 (2b) Ya =(y 0 A +y 1 A +1)>>1 (2c) Y b =(y 0 B +y 1 B +1)>>1 (2d) The linear model parameters α and β may be determined, for example, according to equations (3) and (4):

[0127]

number

[0128] Figure 5 illustrates an example of the locations of the left and top samples and the current block samples involved in the CCLM mode. Figure 5 shows an example of the locations of the samples used for the derivation of the linear model parameters α and β.

[0129] The division operation to calculate the parameter α (e.g., as shown in Equation (3)) may be implemented, for example, using a look-up table. The difference between the maximum and minimum values ​​(e.g., diff value) and / or the parameter α may be expressed in exponential notation, for example, to reduce the amount of memory used to store the table. In an embodiment, diff may be approximated with a 4-bit mantissa and exponent. The table for 1 / diff may be reduced to 16 elements for 16 values ​​of mantissa, for example, according to Equation (5): DivTable[]={0, 7, 6, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 1, 1, 0} (5) The difference diff (eg, as shown by the example) may be approximated.

[0130] The top and left templates may be used together to calculate linear model coefficients. The top and left templates may be used (e.g., alternatively, independently) in one or more (e.g., other) LM modes (e.g., LM_T and LM_L modes).

[0131] In an embodiment (e.g., in LM_T mode), the top template (e.g., only the top template) may be used to calculate the linear model coefficients. The top template may be extended to (W+H) samples, for example, to obtain more samples. In an embodiment (e.g., in LM_L mode), the left template (e.g., only the left template) may be used to calculate the linear model coefficients. The left template may be extended to (H+W) samples, for example, to obtain more samples. In an embodiment (e.g., in LM_LT mode), the left and top templates may be used together to calculate the linear model coefficients.

[0132] Chroma sample locations may be matched for a video sequence (e.g., for a 4:2:0 video sequence). Multiple (e.g., two) types of downsampling filters may be applied to the luma samples to achieve a downsampling ratio in the horizontal and / or vertical directions (e.g., a 2-to-1 downsampling ratio). The selection of the downsampling filter may be specified, for example, by a sequence parameter set (SPS) level flag. The downsampling filters may correspond to "Type 0" and "Type 2" content, for example, according to Equations (6) and (7), respectively:

[0133]

number

[0134] For example, if / when the upper reference line is at a CTU boundary, a luma line (e.g., a common line buffer in intra prediction) may be used to determine or generate a downsampled luma sample.

[0135] The prediction model parameters are calculated as part of the decoding process and the signaling of the parameters may be bypassed or skipped.

[0136] In an embodiment (e.g., for chroma intra-mode coding), multiple intra-modes (e.g., a total of eight intra-modes) may be permitted (e.g., utilized) for chroma intra-mode coding. The intra-modes may include one or more (e.g., five conventional) intra-modes and one or more (e.g., three) component-wise linear model modes (e.g., CCLM, LM_A, and LM_L).

[0137] Table 1 shows an example of a chroma mode signaling and derivation process. Chroma mode coding may depend on the intra prediction mode of the corresponding luma block. A chroma block may correspond to multiple luma blocks, for example, if / when separate block partitioning structures for luma and chroma components are enabled in I slices. In an embodiment (e.g., for chroma DM mode), the intra prediction mode of the corresponding luma block that covers the center position of the current chroma block may be inherited.

[0138] [Table 1]

[0139] For example, a binarization table (eg, a single binarization table) may be used regardless of the value of sps_cclm_enabled_flag.

[0140] MMLM may be used to predict coding blocks. CCLM may be implemented, for example, in one or more (e.g., three) Multi-Model LM (MMLM) modes. In the (e.g., each) MMLM mode, reconstructed neighboring samples may be classified into multiple (e.g., two) classes, for example, using a threshold. In an embodiment, the threshold may be the average of the luma reconstructed from the neighboring samples. A linear model of the (e.g., each) class may be derived, for example, using a Least-Mean-Square (LMS) method. The LMS method may be used to derive a linear model for the CCLM mode.

[0141] The slope of the prediction model may be adjusted. The CCLM may use a prediction model having one or more (e.g., two) parameters to map luma values ​​to chroma values. The slope parameter "a" and the bias parameter "b" may define the mapping, for example, according to equation (8): chromaVal=a * lumaVal+b (8) An adjustment to the slope parameter 'u' may be signaled to update the model, for example according to equation (9): chromaVal=a' * lumaVal+b' (9) The updated slope parameters may be determined, for example, according to equations (10a-10b): a'=a+u (10a) b'=bu * y r (10b)

[0142] The mapping function may be, for example, based on the selection of the luminance value y r The average of the reference luma samples used in model creation may be, for example, tilted or rotated around a point with y r FIG. 6 illustrates an embodiment of the process.

[0143] 6A and 6B illustrate an exemplary effect of the slope adjustment parameter "u". Fig. 6A shows a model of CCLM without an updated slope parameter. Fig. 6B shows a model of CCLM with an updated slope parameter.

[0144] In an embodiment, the tilt adjustment parameter may be an integer between -4 and 4, inclusive. The tilt adjustment parameter may be signaled in the video data (e.g., bitstream). The units of the tilt adjustment parameter may be, for example, 1 / 8 of a chroma sample value per luma sample value (e.g., for 10-bit content).

[0145] In an embodiment, adjustments may be available for CCLM model(s) that use reference samples above and to the left of the block (e.g., "LM_CHROMA_IDX" and "MMLM_CHROMA_IDX"), but not for "single-sided" mode. For example, the availability of adjustments for CCLM models may be based on coding efficiency versus complexity trade-off considerations.

[0146] For a coding block that uses a multi-mode CCLM model, multiple prediction models may be adjusted. For example, a slope adjustment may be applied to each of the prediction models associated with the multi-mode CCLM model. One or more slope updates may be signaled for a chroma block.

[0147] In an embodiment, an encoder may determine the slope adjustment. For example, the encoder may perform a sum of absolute transformed differences (SATD)-based search for the best value of slope update for Cr. The encoder may perform a similar SATD-based search for Cb. The combined slope adjustment pair (e.g., SATD-based update for Cr, SATD-based update for Cb) may be included in a list of rate distortion (RD) checks for a transform unit (TU), for example, if there are non-zero slope adjustment parameters for Cr or Cb.

[0148] FIG. 7 illustrates an example of deriving an adjustment model based on reconstructed luma and chroma samples. For example, the adjustment value may be calculated using reconstructed luma and chroma samples neighboring the current block. The adjustment value may be calculated at the decoder side and the encoder side. As shown by the example of FIG. 7, the slope adjustment value may be derived at the decoder side (e.g., and the encoder side) using, for example, a template consisting of available reconstructed luma and chroma samples. The luma and chroma samples may include the same samples used to derive the CCLM / MMLM parameters (e.g., the CCLM and MMLM parameters may be based on the obtained reconstructed luma and chroma samples). The adjustment value may be derived using CCLM or MMLM. The adjustment value may be calculated, for example, by testing possible values ​​for the reconstructed samples. The selected adjustment value may be the possible value that minimizes the distance.

[0149] The slope adjustment may be implicit (e.g., explicit signaling of the slope adjustment may be bypassed). The adjustment value (u) may be derived at the decoder side. The value may be estimated at the decoder side, for example, rather than signaling the adjustment value (u) from the encoder to the decoder.

[0150] In an embodiment, the chroma samples available to the decoder may be used to derive the adjustment value (u).

[0151] FIG. 8 illustrates an example of using chroma samples to derive adjustment values.

[0152] The template may include W×N samples above the current block and H×M samples to the left of the current block. The parameters W and H may represent width and height, respectively. Different values ​​of the adjustment value "u" may be tested in the encoder and decoder. CCLM / MMLM may be implemented on the template in the encoder and decoder. For example, an inter-component prediction model may be applied with potential adjustment values ​​to predict chroma samples in the template using their respective co-located reconstructed luma samples. The chroma samples predicted using various adjustment values ​​may be compared with the actual reconstructed chroma samples in the template. The adjustment value that results in the most accurate prediction may be selected as the adjustment value for the model of the current block. In an embodiment, the operation may be performed for adjustment values ​​"u" from -4 to 4. The selected (e.g., best) value of u may be the value that provides the most accurate (e.g., best) prediction on the template. The value of u may be determined without signaling. In an embodiment, N and M may be equal. In an embodiment, N and M may depend on the dimensions of the current block.

[0153] The top template (e.g., only the top template) may be considered, for example, to derive a u value when the top sample (e.g., only the top sample) is considered for CCLM / MMLM(LM_A). The left template (e.g., only the left template) may be considered, for example, to derive a u value when the left sample (e.g., only the left sample) is considered for CCLM / MMLM(LM_A). The top and left templates may be considered, for example, to derive a u value when the top and left samples are considered for CCLM / MMLM(LM_A).

[0154] The adjustment decision indication may indicate implicit or explicit signaling of the adjustment value. The encoder may decide whether the adjustment value should be explicitly signaled in the bitstream or derived / estimated by the decoder and indicate the decision via an implicit or explicit adjustment flag. A flag may be signaled to indicate (e.g., to the decoder) whether the adjustment value (u) is signaled to the decoder or estimated by the decoder. For example, an implicit slope adjustment may be indicated by a flag equal to 0, and an explicit slope adjustment may be indicated by a flag not equal to 0 (e.g., a flag equal to 1).

[0155] The number of adjustment values ​​may vary. In an embodiment, there may be eight adjustment values ​​(e.g., -4-3-2-1 1 2 3 4). Eight adjustment values ​​may provide a reasonable compromise between good prediction and signaling overhead. The restriction on the number of adjustment values ​​may be relaxed for implicit slope adjustment without signaling. In an embodiment, non-integer values ​​between -4 and 4 may be used as adjustment values. In an embodiment, a range (e.g., a wide range) of integer and / or non-integer adjustment values ​​may be used (e.g., -10 to 10). A wide (e.g., high) range of numbers to test may correspond to computational complexity (e.g., additional computational complexity) of the encoder and decoder. In an embodiment, a reasonable trade-off for selecting the range of adjustment values ​​may be implemented.

[0156] Different adjustment models may be available for adjusting one or more prediction models for a coding block. The slope adjustment for a prediction model may be (for example, y r The tilt adjustment may be based on modifying the tilt around luma midpoints (as shown in FIG. 1). The tilt adjustment may be based on pivoting the prediction model around extreme points, such as maximum and / or minimum luma values. FIGS. 9A-9B show examples of tilt adjustment. In some embodiments, the tilt adjustment may be based on modifying the tilt around pivot points indicated in the video data.

[0157] 9A-9B illustrate an example of tilt correction near extreme values. Fig. 9A shows an example of tilt correction near a minimum luma value. Fig. 9B shows an example of tilt correction near a maximum luma value. For example, an example adjustment model may include tilt correction near a luma extreme value.

[0158] Slope modification near luma extrema may provide flexibility to select a suitable slope for a particular coding block. Slope modification near luma extrema may not require additional (e.g., further) signaling.

[0159] For example, the prediction model for the coding block may include a linear prediction model. The linear function may be modified, for example, by pivoting around a minimum and / or a maximum. For example, the minimum of the linear prediction model may be a pivot point for the slope modification. The maximum of the linear prediction model may be a pivot point for the slope modification.

[0160] To adjust the prediction model of the coding block, multiple adjustment models may be obtained. For example, in an exemplary adjustment model, the slope of the prediction model may be adjusted around a pivot point, which may be a minimum value of the prediction model. In an exemplary adjustment model, the slope of the prediction model may be adjusted around a pivot point, which may be a maximum value of the prediction model. In an exemplary adjustment model, the slope of the prediction model may be adjusted around a pivot point, which may be a midpoint of the prediction model.

[0161] In one example of near-minimum correction, assuming Ymin is the minimum value of the collocated luma samples, the a and b values ​​may be corrected, for example, according to equations (11a) and (11b): a=a * u (11a) b=bu * Ymin (11b)

[0162] In one example of near-maximum correction, assuming Ymax is the minimum value of the collocated luma samples, the a and b values ​​may be corrected, for example, according to equations (12a) and (12b): a=a * u (12a) b=bu * Ymax (12a)

[0163] In an exemplary adjustment model, an offset value (e.g., a constant value b) may be modified with or without modifying the slope. In an embodiment, a predictive model may be adjusted based on a selected adjustment model by adjusting the offset of the predictive model and maintaining (e.g., not adjusting) the slope (e.g., of the predictive model). Figure 10 shows an example of changing a constant value (e.g., only a constant value).

[0164] 10 illustrates an example of modifying the linear slope value b. The modification of the slope value b can be implemented, for example, according to equation (13): b=b+u (13)

[0165] Parameters (e.g., slope and offset) of the prediction model may be derived (e.g., by a video decoder) based on reconstructed samples neighboring the coding block. The decoder may adjust the prediction model based on a selected adjustment model. The selected adjustment model may be configured to adjust the slope and / or offset of the prediction model.

[0166] The example adjustment models described herein may be implemented alone or in any combination. For example, different u values ​​may be tested at the encoder side and the decoder side, the slope may be changed around the midpoint and extreme points at the encoder side and the decoder side, and / or the constant value may be changed at the encoder side and the decoder side. For example, the (e.g., best) model may be selected according to the distance measured with or without signaling. Although the examples provided herein relate to predicting chroma samples based on co-located luma samples, those skilled in the art may understand that the examples may be applied to predicting luma samples based on co-located chroma samples.

[0167] In an embodiment, an encoder may select an adjustment model from multiple adjustment models to adjust a prediction model for a coding block. For example, the encoder may perform a sum of absolute transform difference (SATD)-based search for the best adjustment for Cr. A SATD distance (e.g., a distance associated with each adjustment model) may be calculated for the available adjustment models by calculating the SATD between the sample (e.g., chroma and luma) values ​​of the current block and the predicted sample values. The SATD distances calculated for the different adjustment models may be used to select a suitable adjustment model for the current block. The prediction model may be adjusted based on the selected adjustment model.

[0168] A plurality of adjustment models may be obtained (e.g., by a video encoder) to adjust the prediction model. A first difference (e.g., SATD) for a first adjustment model between a sample value of a coding block and a prediction sample value predicted based on a first adjustment model may be calculated (e.g., by a video encoder). A second difference for a second adjustment model between a sample value of a coding block and a prediction sample value predicted based on a second adjustment model may be calculated (e.g., by a video encoder). An adjustment model may be selected based on comparing the first difference and the second difference. The selected adjustment model may be indicated in the video data.

[0169] As shown in the table below, the selected adjustment model may be obtained based on one or more instructions in the video data. For example, in Table 2, the selected adjustment model may be obtained based on an adjustment model instruction (e.g., in the video data). For example, the adjustment model instruction may be or may include an AdjustModel instruction shown in Table 2. Based on the adjustment model instruction, one or more pivot points of the selected adjustment model may be determined. For example, the pivot points may be signaled by Pivotpoint_M1 and Pivotpoint_M2.

[0170] [Table 2]

[0171] As shown in Table 2, the selected adjustment model may be obtained based on an adjustment model indication (e.g., in the video data) indicating a first pivot point (e.g., Pivotpoint_M1) of the selected adjustment model and a second pivot point (e.g., Pivotpoint_M2) of the adjustment model. For example, the prediction model for the block may include multiple prediction models. When MMLM is used for the coding block, multiple linear prediction models are used to predict the coding block. Adjusting the prediction model for the coding block may be based on multiple pivot points, for example, the first pivot point of the selected adjustment model and the second pivot point of the selected adjustment model. Based on the selected adjustment model, it may be determined that the first prediction model for the coding block pivots about the first pivot point of the first prediction model and the second prediction model for the coding block pivots about the second pivot point of the selected adjustment model.

[0172] The first pivot point may be based on the first adjustment model, and the second pivot point may be based on the second adjustment model. The first pivot point may be used to adjust a first prediction model of the plurality of prediction models. The second pivot point may be used to adjust a second prediction model of the plurality of linear prediction models. The video decoder may adjust a slope of the first linear prediction model via the determined first pivot point, and adjust a slope of the second linear prediction model via the determined second pivot point.

[0173] For example, in Table 3, the selected adjustment model may be obtained based on an adjustment model instruction (e.g., in the video data) indicating a pivot point of the selected adjustment model. For example, based on the instruction isMidPoint, it may be determined whether the pivot point of the selected adjustment model is a midpoint of the predictive model. Based on the instruction PivotPoint, it may be determined whether to use the start point or the end point of the predictive model as the pivot point. For example, PivotPoint=1 may indicate the start of the predictive model as the pivot point, and PivotPoint=2 may indicate the end of the predictive model as the pivot point.

[0174] [Table 3]

[0175] For example, in Table 4, the selected adjustment model may be obtained based on an adjustment model instruction (e.g., in the video data) indicating a pivot point. As shown in Table 4, the pivot point may be selected from a plurality of predefined points, such as 2N+1 potential pivot points. The predefined points may include a midpoint and N points on each side of the midpoint (e.g., N predefined potential pivot points above the midpoint and N predefined potential pivot points below the midpoint). The adjustment model instruction may be configured to indicate about which predefined point the predictive model should be adjusted.

[0176] [Table 4-1]

[0177] [Table 4-2]

[0178] Log2(N) bits may be processed (e.g., encoded and / or decoded) as shown in Table 5. For example, four points (e.g., pivot points) may use 2 bits for processing (e.g., to encode and / or decode).

[0179] [Table 5]

[0180] Although the examples provided herein may assume that media content is streamed to a display device, there is no particular limitation on the type of display device that can benefit from the exemplary techniques described herein. For example, the display device may be a television, a projector, a mobile phone, a tablet, etc. Furthermore, the exemplary techniques described herein may be applied to remote conferencing settings as well as streaming use cases. In addition, the decoder and display described herein may be separate devices or may be part of the same device. For example, a set-top box may decode an incoming video stream and (e.g., subsequently) provide the decoded stream to a display device (e.g., via HDMI), and may transmit information about viewing conditions, such as viewing distance, from the display device to the set-top box (e.g., via HDMI).

[0181] Although the features and elements are described above in certain combinations, one skilled in the art will understand that each feature or element may be used alone or in any combination with the other features and elements. In addition, the methods described herein may be implemented in a computer program, software, or firmware embodied in a computer-readable medium for execution by a computer or processor. Examples of computer-readable media include electronic signals (transmitted over wired or wireless connections) and computer-readable storage media. Examples of computer-readable storage media include, but are not limited to, read-only memory (ROM), random-access memory (RAM), registers, cache memory, semiconductor memory devices, magnetic media such as internal hard disks and removable disks, magneto-optical media, and optical media such as CD-ROM disks and digital versatile disks (DVDs). A processor in association with software may be used to implement a radio frequency transceiver for use in a WTRU, UE, terminal, base station, RNC, or any host computer.

Claims

1. 1. A video decoding device, comprising: a processor, the processor comprising: Obtaining a prediction model for predicting a coding block; selecting an adjustment model from a plurality of adjustment models for adjusting the forecast model; Adjusting the forecast model based on the selected adjustment model; The device is configured to decode the coding block based on the adjusted prediction model.

2. The processor, 2. The device of claim 1, further configured to derive a slope and an offset of the prediction model based on reconstructed samples neighboring the coding block, wherein adjusting the prediction model based on the selected adjustment model comprises adjusting at least one of the slope or the offset of the prediction model based on the selected adjustment model.

3. The prediction model includes a component-component prediction model, and the processor:

2. The device of claim 1, further configured to determine a plurality of parameters of the inter-component prediction model based on adjacent chroma and luma samples of the coding block, wherein a first adjustment model and a second adjustment model of the plurality of adjustment models are configured to differently adjust the plurality of parameters of the inter-component prediction model.

4. 2. The device of claim 1, wherein a first adjustment model of the plurality of adjustment models is configured to adjust a slope of the predictive model near a minimum value, a second adjustment model of the plurality of adjustment models is configured to adjust the slope of the predictive model near a median value, and a third adjustment model of the plurality of adjustment models is configured to adjust the slope of the predictive model near a maximum value.

5. The processor, 2. The device of claim 1, further configured to adjust the prediction model based on the selected adjustment model by adjusting an offset of the prediction model and maintaining a same slope of the prediction model.

6. The selected adjustment model is obtained based on an adjustment model indication in the video data, and the processor:

2. The device of claim 1, further configured to determine a pivot point of the selected adjustment model based on the adjustment model indication, and adjusting the predictive model based on the selected adjustment model includes adjusting a slope of the predictive model via the determined pivot point.

7. The selected adjustment model is obtained based on an adjustment model indication in the video data, and the processor: determining an offset adjustment for the selected adjustment model based on the adjustment model indication; The device of claim 1 , further configured to adjust an offset of the predictive model based on the determined offset adjustment of the selected adjustment model.

8. The prediction model for predicting the coding block includes a plurality of linear prediction models, and the processor: determining a first pivot point for adjusting a first linear prediction model of the plurality of linear prediction models based on the selected adjustment model; determining a second pivot point for adjusting a second linear prediction model of the plurality of linear prediction models based on the selected adjustment model; adjusting a slope of the first linear prediction model through the determined first pivot point; The device of claim 1 , further configured to adjust a slope of the second linear prediction model via the determined second pivot point.

9. The prediction model for predicting the coding block includes a plurality of linear prediction models, and the processor: determining a first pivot point for adjusting a first linear prediction model of the plurality of linear prediction models based on a first adjustment model; determining a second pivot point for adjusting a second linear prediction model of the plurality of linear prediction models based on a second adjustment model; adjusting a slope of the first linear prediction model through the determined first pivot point; The device of claim 1 , further configured to adjust a slope of the second linear prediction model via the determined second pivot point.

10. 1. A video encoding device, comprising: a processor, the processor comprising: Obtaining a prediction model for predicting a coding block; selecting an adjustment model from a plurality of adjustment models for adjusting the forecast model; Adjusting the forecast model based on the selected adjustment model; The device is configured to encode the coding block based on the adjusted prediction model.

11. The processor, obtaining the plurality of adjustment models configured to adjust the predictive model; calculating, for a first adjustment model of the plurality of adjustment models, a first difference between a sample value of the coding block and a predicted sample value predicted based on the first adjustment model; 11. The device of claim 10, further configured to calculate, for a second adjustment model among the plurality of adjustment models, a second difference between the sample values ​​of the coding block and a predicted sample value predicted based on the second adjustment model, wherein the adjustment model is selected based on at least the first difference and the second difference.

12. The prediction model includes a component-component prediction model, and the processor:

11. The device of claim 10, further configured to determine a plurality of parameters of the inter-component prediction model based on adjacent chroma and luma samples of the coding block, wherein a first adjustment model and a second adjustment model of the plurality of adjustment models are configured to differently adjust the plurality of parameters of the inter-component prediction model.

13. 11. The device of claim 10, wherein a first adjustment model of the plurality of adjustment models is configured to adjust a slope of the predictive model near a minimum value, a second adjustment model of the plurality of adjustment models is configured to adjust the slope of the predictive model near a median value, and a third adjustment model of the plurality of adjustment models is configured to adjust the slope of the predictive model near a maximum value.

14. The processor, 11. The device of claim 10, further configured to adjust the predictive model based on the selected adjustment model by adjusting an offset of the predictive model and maintaining a same slope of the predictive model.

15. The processor, determining a pivot point for the selected adjustment model, where adjusting the predictive model based on the selected adjustment model adjusts a slope of the predictive model via the determined pivot point; The device of claim 10 , further configured to: include, in the video data, a calibration model indicator indicating the selected calibration model and the determined pivot point of the selected calibration model.

16. The processor, determining an offset adjustment for the selected adjustment model; adjusting an offset of the predictive model based on the determined offset adjustment of the selected adjustment model; 11. The device of claim 10, further configured to include, in the video data, an adjustment model indicator that indicates the selected adjustment model and the determined offset adjustment for the selected adjustment model.

17. The prediction model for predicting the coding block includes a plurality of linear prediction models, and the processor: determining a first pivot point for adjusting a first linear prediction model of the plurality of linear prediction models; determining a second pivot point for adjusting a second linear prediction model of the plurality of linear prediction models; adjusting a slope of the first linear prediction model through the determined first pivot point; adjusting a slope of the second linear prediction model through the determined second pivot point; The device of claim 10 , further configured to include, in the video data, a calibration model indicator indicating the first pivot point and the second pivot point associated with the selected calibration model.

18. The prediction model for predicting the coding block includes a plurality of linear prediction models, and the processor: determining a first adjustment model associated with a first pivot point for adjusting a first linear prediction model of the plurality of linear prediction models; determining a second adjustment model associated with a second pivot point for adjusting a second linear prediction model of the plurality of linear prediction models; adjusting a slope of the first linear prediction model through the determined first pivot point; adjusting a slope of the second linear prediction model through the determined second pivot point; The device of claim 10 , further configured to include, in the video data, a training model indicator that indicates the first training model and the second training model.

19. The device of any one of claims 1 to 18, further comprising a memory operatively connected to the processor.

20. 1. A method for a video decoder, the method comprising: obtaining a prediction model for predicting a coding block; selecting an adjustment model from a plurality of adjustment models for adjusting the forecast model; adjusting the forecast model based on the selected adjustment model; and and decoding the coding block based on the adjusted prediction model.

21. The method further comprising:

21. The method of claim 20, further comprising deriving a slope and an offset of the prediction model based on reconstructed samples neighboring the coding block, and wherein adjusting the prediction model based on the selected adjustment model comprises adjusting at least one of the slope or the offset of the prediction model based on the selected adjustment model.

22. The prediction model includes a component-component prediction model, and the method further comprises:

21. The method of claim 20, further comprising determining a plurality of parameters of the inter-component prediction model based on adjacent chroma and luma samples of the coding block, wherein a first adjustment model and a second adjustment model of the plurality of adjustment models are configured to adjust the plurality of parameters of the inter-component prediction model differently.

23. 21. The method of claim 20, wherein a first adjustment model of the plurality of adjustment models is configured to adjust a slope of the predictive model around a minimum value, a second adjustment model of the plurality of adjustment models is configured to adjust the slope of the predictive model around a median value, and a third adjustment model of the plurality of adjustment models is configured to adjust the slope of the predictive model around a maximum value.

24. The method further comprising:

21. The method of claim 20, further comprising adjusting the forecast model based on the selected adjustment model by adjusting an offset of the forecast model and maintaining a same slope of the forecast model.

25. The selected adjustment model is obtained based on an adjustment model indication in video data, and the method further comprises:

21. The method of claim 20, further comprising determining a pivot point for the selected adjustment model based on the adjustment model indication, and adjusting the predictive model based on the selected adjustment model comprises adjusting a slope of the predictive model via the determined pivot point.

26. The selected adjustment model is obtained based on an adjustment model indication in video data, and the method further comprises: determining an offset adjustment for the selected adjustment model based on the adjustment model indication; 21. The method of claim 20, further comprising: adjusting an offset of the predictive model based on the determined offset adjustment of the selected adjustment model.

27. wherein the prediction model for predicting the coding block comprises a plurality of linear prediction models, and the method further comprises: determining a first pivot point for adjusting a first linear prediction model of the plurality of linear prediction models based on the selected adjustment model; determining a second pivot point for adjusting a second linear prediction model of the plurality of linear prediction models based on the selected adjustment model; adjusting a slope of the first linear prediction model through the determined first pivot point; 21. The method of claim 20, further comprising: adjusting a slope of the second linear prediction model through the determined second pivot point.

28. wherein the prediction model for predicting the coding block comprises a plurality of linear prediction models, and the method further comprises: determining a first pivot point for adjusting a first linear prediction model of the plurality of linear prediction models based on a first adjustment model; determining a second pivot point for adjusting a second linear prediction model of the plurality of linear prediction models based on a second adjustment model; adjusting a slope of the first linear prediction model through the determined first pivot point; 21. The method of claim 20, further comprising: adjusting a slope of the second linear prediction model through the determined second pivot point.

29. 1. A method for a video encoder, the method comprising: obtaining a prediction model for predicting a coding block; selecting an adjustment model from a plurality of adjustment models for adjusting the forecast model; adjusting the forecast model based on the selected adjustment model; and and encoding the coding block based on the adjusted prediction model.

30. The method further comprising: obtaining the plurality of adjustment models configured to adjust the predictive model; calculating, for a first adjustment model of the plurality of adjustment models, a first difference between a sample value of the coding block and a predicted sample value predicted based on the first adjustment model; 30. The method of claim 29, further comprising: for a second adjustment model of the plurality of adjustment models, calculating a second difference between the sample value of the coding block and a predicted sample value predicted based on the second adjustment model, wherein the adjustment model is selected based on at least the first difference and the second difference.

31. The prediction model includes a component-component prediction model, and the method further comprises:

30. The method of claim 29, further comprising determining a plurality of parameters of the inter-component prediction model based on adjacent chroma and luma samples of the coding block, wherein a first adjustment model and a second adjustment model of the plurality of adjustment models are configured to adjust the plurality of parameters of the inter-component prediction model differently.

32. 30. The method of claim 29, wherein a first adjustment model of the plurality of adjustment models is configured to adjust a slope of the predictive model around a minimum value, a second adjustment model of the plurality of adjustment models is configured to adjust the slope of the predictive model around a median value, and a third adjustment model of the plurality of adjustment models is configured to adjust the slope of the predictive model around a maximum value.

33. The method further comprising:

30. The method of claim 29, further comprising adjusting the predictive model based on the selected adjustment model by adjusting an offset of the predictive model and maintaining a same slope of the predictive model.

34. The method further comprising: determining a pivot point for the selected adjustment model, where adjusting the predictive model based on the selected adjustment model includes adjusting a slope of the predictive model through the determined pivot point; 30. The method of claim 29, further comprising including, in the video data, a calibration model indicator indicating the selected calibration model and the determined pivot point of the selected calibration model.

35. The method further comprising: determining an offset adjustment for the selected adjustment model; adjusting an offset of the predictive model based on the determined offset adjustment of the selected adjustment model; and 30. The method of claim 29, further comprising: including, in the video data, an adjustment model indicator that indicates the selected adjustment model and the determined offset adjustment for the selected adjustment model.

36. wherein the prediction model for predicting the coding block comprises a plurality of linear prediction models, and the method further comprises: determining a first pivot point for adjusting a first linear prediction model of the plurality of linear prediction models; determining a second pivot point for adjusting a second linear prediction model of the plurality of linear prediction models; adjusting a slope of the first linear prediction model through the determined first pivot point; adjusting a slope of the second linear prediction model through the determined second pivot point; 30. The method of claim 29, further comprising: including in the video data a calibration model indicator indicating the first pivot point and the second pivot point associated with the selected calibration model.

37. wherein the prediction model for predicting the coding block comprises a plurality of linear prediction models, and the method further comprises: determining a first adjustment model associated with a first pivot point for adjusting a first linear prediction model of the plurality of linear prediction models; determining a first adjustment model associated with a second pivot point for adjusting a second linear prediction model of the plurality of linear prediction models; adjusting a slope of the first linear prediction model via the determined first pivot point; adjusting a slope of the second linear prediction model via the determined second pivot point; 30. The method of claim 29, further comprising: including in the video data a training model indicator that indicates the first training model and the second training model.

38. A computer program product comprising program code instructions stored on a non-transitory computer readable medium and for implementing the steps of the method according to at least one of claims 20 to 37 when executed by a processor.

39. A computer program comprising program code instructions for implementing the steps of the method according to at least one of claims 20 to 37, when the computer program is executed by a processor.

40. Video data comprising information representative of said coding blocks encoded according to one of the methods of any one of claims 29 to 37.

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