Nonlinear inverse transforms for video compression

Abstract

Decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering includes generating decoded block data by decoding a current block of a current frame. Decoding the current block includes obtaining quantized transform coefficients for the current block from an encoded bitstream, obtaining transform data for the current block from the encoded bitstream, wherein the transform data indicates a transform type and a transform size, obtaining dequantized transform block data by dequantizing the quantized transform coefficients, and obtaining decoded residual block data by inverse transforming the dequantized transform block data in accordance with the transform data. Inverse transforming the dequantized transform block data includes obtaining intermediate decoded block data by combining prediction block data for the current block and the decoded residual block data and obtaining the decoded block data by filtering the intermediate decoded block data using a transform size adaptive directional nonlinear filter.

Description

NONLINEAR INVERSE TRANSFORMS FOR VIDEO COMPRESSION CROSS-REFERENCE TO RELATED APPLICATION(S)

[0001] This application claims priority to and the benefit of U.S. Provisional Application Patent Serial No. 63 / 531,397, filed August 08, 2023, the entire disclosure of which is hereby incorporated by reference. BACKGROUND

[0002] Digital images and video can be used, for example, on the internet, for remote business meetings via video conferencing, high-definition video entertainment, video advertisements, or sharing of user-generated content. Due to the large amount of data involved in transferring and processing image and video data, high-performance compression may be advantageous for transmission and storage. Accordingly, it would be advantageous to provide high-resolution image and video transmitted over communications channels having limited bandwidth. SUMMARY

[0003] This application relates to encoding and decoding of image data, video stream data, or both for transmission, storage, or both. Disclosed herein are aspects of systems, methods, and apparatuses for encoding and decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering.

[0004] Variations in these and other aspects will be described in additional detail hereafter.

[0005] An aspect is a method for encoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering. Encoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering may include generating encoded block data by encoding a current block from a current frame from an input video. Encoding the current block may include obtaining residual block data indicating a difference between the current block and prediction block data for the current block and identifying an optimal transform from available transforms for transforming the residual block data by evaluating two or more of the available transforms, wherein identifying the optimal transform includesidentifying an optimal transform type and an optimal transform size. Evaluating a respective available transform may include obtaining candidate transform block data by transforming the residual block data using the respective available transform, obtaining candidate quantized block data by quantizing the candidate transform block data, obtaining candidate dequantized transform block data by dequantizing the candidate quantized block data, and obtaining candidate decoded residual block data by inverse transforming the candidate dequantized transform block data. Inverse transforming the candidate dequantized transform block data may include obtaining intermediate decoded block data by combining the prediction block data and the candidate decoded residual block data and obtaining candidate decoded block data by filtering the intermediate decoded block data using an optimal transform size adaptive directional nonlinear filter. Encoding the current block may include including the candidate quantized block data in an encoded bitstream and outputting the encoded bitstream.

[0006] An aspect is a method for decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering. Decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering may include generating decoded block data by decoding a current block of a current frame and outputting the decoded block data. Decoding the current block may include obtaining quantized transform coefficients for the current block from an encoded bitstream, obtaining transform data for the current block from the encoded bitstream, wherein the transform data indicates a transform type and a transform size, obtaining dequantized transform block data by dequantizing the quantized transform coefficients, and obtaining decoded residual block data by inverse transforming the dequantized transform block data in accordance with the transform data. Inverse transforming the dequantized transform block data may include obtaining intermediate decoded block data by combining prediction block data for the current block and the decoded residual block data and obtaining the decoded block data by filtering the intermediate decoded block data using a transform size adaptive directional nonlinear filter.

[0007] An aspect is a non-transitory computer-readable storage medium having stored thereon an encoded bitstream comprising quantized transform coefficients for a current block from a current frame of a video and transform data for the current block. The transform data indicates a transform type and a transform size of a transform for inverse transforming dequantized transform block data, the dequantized transform block data corresponding to dequantizing the quantized transform coefficients, to obtain decoded residual block data. Thetransform data indicates a transform size adaptive directional nonlinear filter corresponding to the transform for obtaining decoded block data corresponding to filtering a combination of the decoded residual block data and prediction block data for the current block using the transform size adaptive directional nonlinear filter.

[0008] An aspect is an apparatus for encoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering. The apparatus includes a non-transitory computer readable medium, and a processor configured to execute instructions stored on the non-transitory computer readable medium to generate encoded block data. To generate the encoded block data the processor is configured to execute the instructions to encode a current block from a current frame from an input video. To encode the current block, the processor is configured to execute the instructions to obtain residual block data that indicates a difference between the current block and prediction block data for the current block and identify an optimal transform from available transforms for transforming the residual block data, wherein to identify the optimal transform, the processor is configured to execute the instructions to evaluate two or more of the available transforms, wherein the optimal transform includes an optimal transform type and an optimal transform size. To evaluate a respective available transform, the processor is configured to execute the instructions to obtain candidate transform block data, wherein, to obtain the candidate transform block data, the processor is configured to execute the instructions to use the respective available transform to transform the residual block data, obtain candidate quantized block data, wherein, to obtain the candidate quantized block data, the processor is configured to execute the instructions to quantize the candidate transform block data, obtain candidate dequantized transform block data, wherein, to obtain the candidate dequantized transform block data, the processor is configured to execute the instructions to dequantize the candidate quantized block data, and obtain candidate decoded residual block data, wherein, to obtain the candidate decoded residual block data, the processor is configured to execute the instructions to inverse transform the candidate dequantized transform block data. To inverse transform the candidate dequantized transform block data the processor is configured to execute the instructions to obtain intermediate decoded block data, wherein, to obtain the intermediate decoded block data, the processor is configured to execute the instructions to combine the prediction block data and the candidate decoded residual block data and obtain candidate decoded block data, wherein, to obtain the candidate decoded block data, the processor is configured to execute the instructions to use an optimal transform size adaptive directional nonlinear filter to filter the intermediate decoded block data. The processor isconfigured to include the candidate quantized block data in an encoded bitstream and output the encoded bitstream.

[0009] An aspect is an apparatus for decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering. The apparatus includes a non-transitory computer readable medium, and a processor configured to execute instructions stored on the non-transitory computer readable medium to generate decoded block data. To generate the decoded block data the processor configured to execute the instructions stored on the non-transitory computer readable medium to decode a current block of a current frame and output the decoded block data. To decode the current block the processor configured to execute the instructions stored on the non-transitory computer readable medium to obtain quantized transform coefficients for the current block from an encoded bitstream, obtain transform data for the current block from the encoded bitstream, wherein the transform data indicates a transform type and a transform size, obtain dequantized transform block data, wherein, to obtain the dequantized transform block data the processor configured to execute the instructions stored on the non-transitory computer readable medium to dequantize the quantized transform coefficients, and obtain decoded residual block data, wherein, to obtain the decoded residual block data the processor configured to execute the instructions stored on the non-transitory computer readable medium to inverse transform the dequantized transform block data in accordance with the transform data. To inverse transform the dequantized transform block data the processor configured to execute the instructions stored on the non-transitory computer readable medium to obtain intermediate decoded block data. To obtain the intermediate decoded block data the processor configured to execute the instructions stored on the non-transitory computer readable medium to combine prediction block data for the current block and the decoded residual block data. To inverse transform the dequantized transform block data the processor configured to execute the instructions stored on the non-transitory computer readable medium to obtain the decoded block data. To obtain the decoded block data the processor is configured to execute the instructions stored on the non-transitory computer readable medium to filter the intermediate decoded block data using a transform size adaptive directional nonlinear filter. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The description herein makes reference to the accompanying drawings wherein like reference numerals refer to like parts throughout the several views unless otherwise noted or otherwise clear from context.

[0011] FIG. 1 is a diagram of a computing device in accordance with implementations of this disclosure.

[0012] FIG. 2 is a diagram of a computing and communications system in accordance with implementations of this disclosure.

[0013] FIG. 3 is a diagram of a video stream for use in encoding and decoding in accordance with implementations of this disclosure.

[0014] FIG. 4 is a block diagram of an encoder in accordance with implementations of this disclosure.

[0015] FIG. 5 is a block diagram of a decoder in accordance with implementations of this disclosure.

[0016] FIG. 6 is a block diagram of a representation of a portion of a frame in accordance with implementations of this disclosure.

[0017] FIG. 7 is a block diagram of an encoder implementing transform selection in accordance with implementations of this disclosure.

[0018] FIG. 8 is a flowchart diagram of an example of encoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering in accordance with implementations of this disclosure.

[0019] FIG. 9 is a flowchart diagram of an example of decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering in accordance with implementations of this disclosure.

[0020] FIG. 10 is a block diagram of an encoder implementing transform selection with nonlinear inverse transforms in accordance with implementations of this disclosure.

[0021] FIG. 11 is a block diagram of a decoder implementing transform selection with nonlinear inverse transforms in accordance with implementations of this disclosure. DETAILED DESCRIPTION

[0022] Image and video compression schemes may include breaking an image, or frame, into smaller portions, such as blocks, and generating an output bitstream using techniques to minimize the bandwidth utilization of the information included for each block in the output. In some implementations, the information included for each block in the output may be limited by reducing spatial redundancy, reducing temporal redundancy, or a combination thereof. For example, temporal or spatial redundancies may be reduced by predicting a frame, or a portion thereof, based on information available to both the encoder and decoder, and including information representing a difference, or residual, between the predicted frame andthe original frame in the encoded bitstream. The residual information may be further compressed by transforming the residual information into transform coefficients (e.g., energy compaction), quantizing the transform coefficients, and entropy coding the quantized transform coefficients. For example, transforming the residual information can include using block-based transforms, such as a Karhunen-Loève Transform (KLT), a Discrete Cosine Transform (DCT), a Singular Value Decomposition Transform (SVD), a Wavelet Transform, or an Asymmetric Discrete Sine Transform (ADST). Other coding information, such as motion information, may be included in the encoded bitstream, which may include transmitting differential information based on predictions of the encoding information, which may be entropy coded to further reduce the corresponding bandwidth utilization. An encoded bitstream can be decoded to reconstruct the blocks and the source images from the limited information. In some implementations, the accuracy, efficiency, or both, of coding a block may be limited.

[0023] Block-based hybrid video coding techniques, or codecs, to improve coding efficiency, perform rate-distortion optimization to identify optimized, or optimal, encoding parameters, relative to available encoding parameters and resource limitations, which may include identifying a rate-distortion optimization optimized transform. A reconstructed frame, or a portion thereof, may include quantization artifacts. A decoder may perform post- processing on reconstructed frame data to remove, or minimize, artifacts, or other distortion, such as quantization artifacts. In some block-based hybrid video coding techniques, or codecs, rate-distortion optimization omits or excludes filtering, such as post-processing filtering to remove, or reduce, quantization artifacts. Rate-distortion optimization that omits or excludes filtering, such as post-processing filtering to remove, or reduce, quantization artifacts may inaccurately identify the optimal transform (type, size, or both). For example, rate-distortion optimization that omits or excludes filtering, such as post-processing filtering to remove, or reduce, quantization artifacts may determine that a relatively large transform corresponds to relatively large amounts of quantization artifacts in image portions including edges and may encode the portion of the image using relatively small transforms to reduce the quantization artifacts despite a corresponding reduction in compression efficiency relative to using the relatively large transform and post-processing filtering to reduce or eliminate the quantization artifacts.

[0024] The encoding and decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering described herein improves on video coding techniques, or codecs, by performing rate-distortionoptimization using inverse transforms that include using a transform size adaptive directional nonlinear filter, which may reduce encoding cost, improve accuracy, or both, by identifying relatively large transforms, relative to rate-distortion optimization that omits or excludes filtering.

[0025] FIG. 1 is a diagram of a computing device 100 in accordance with implementations of this disclosure. The computing device 100 shown includes a memory 110, a processor 120, a user interface (UI) 130, an electronic communication unit 140, a sensor 150, a power source 160, and a bus 170. As used herein, the term “computing device” includes any unit, or a combination of units, capable of performing any method, or any portion or portions thereof, disclosed herein.

[0026] The computing device 100 may be a stationary computing device, such as a personal computer (PC), a server, a workstation, a minicomputer, or a mainframe computer; or a mobile computing device, such as a mobile telephone, a personal digital assistant (PDA), a laptop, or a tablet PC. Although shown as a single unit, any one element or elements of the computing device 100 can be integrated into any number of separate physical units. For example, the user interface 130 and processor 120 can be integrated in a first physical unit and the memory 110 can be integrated in a second physical unit.

[0027] The memory 110 can include any non-transitory computer-usable or computer- readable medium, such as any tangible device that can, for example, contain, store, communicate, or transport data 112, instructions 114, an operating system 116, or any information associated therewith, for use by or in connection with other components of the computing device 100. The non-transitory computer-usable or computer-readable medium can be, for example, a solid-state drive, a memory card, removable media, a read-only memory (ROM), a random-access memory (RAM), any type of disk including a hard disk, a floppy disk, an optical disk, a magnetic or optical card, an application-specific integrated circuits (ASICs), or any type of non-transitory media suitable for storing electronic information, or any combination thereof.

[0028] Although shown a single unit, the memory 110 may include multiple physical units, such as one or more primary memory units, such as random-access memory units, one or more secondary data storage units, such as disks, or a combination thereof. For example, the data 112, or a portion thereof, the instructions 114, or a portion thereof, or both, may be stored in a secondary storage unit and may be loaded or otherwise transferred to a primary storage unit in conjunction with processing the respective data 112, executing the respective instructions 114, or both. In some implementations, the memory 110, or a portion thereof,may be removable memory.

[0029] The data 112 can include information, such as input audio data, encoded audio data, decoded audio data, or the like. The instructions 114 can include directions, such as code, for performing any method, or any portion or portions thereof, disclosed herein. The instructions 114 can be realized in hardware, software, or any combination thereof. For example, the instructions 114 may be implemented as information stored in the memory 110, such as a computer program, which may be executed by the processor 120 to perform any of the respective methods, algorithms, aspects, or combinations thereof, as described herein.

[0030] Although shown as included in the memory 110, in some implementations, the instructions 114, or a portion thereof, may be implemented as a special purpose processor, or circuitry, that can include specialized hardware for carrying out any of the methods, algorithms, aspects, or combinations thereof, as described herein. Portions of the instructions 114 can be distributed across multiple processors on the same machine or different machines or across a network such as a local area network, a wide area network, the Internet, or a combination thereof.

[0031] The processor 120 can include any device or system capable of manipulating or processing a digital signal or other electronic information now-existing or hereafter developed, including optical processors, quantum processors, molecular processors, or a combination thereof. For example, the processor 120 can include a special purpose processor, a central processing unit (CPU), a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessor in association with a DSP core, a controller, a microcontroller, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a programmable logic array, programmable logic controller, microcode, firmware, any type of integrated circuit (IC), a state machine, or any combination thereof. As used herein, the term “processor” includes a single processor or multiple processors.

[0032] The user interface 130 can include any unit capable of interfacing with a user, such as a virtual or physical keypad, a touchpad, a display, a touch display, a speaker, a microphone, a video camera, a sensor, or any combination thereof. For example, the user interface 130 may be an audio-visual display device, and the computing device 100 may present audio, such as decoded audio, using the user interface 130 audio-visual display device, such as in conjunction with displaying video, such as decoded video. Although shown as a single unit, the user interface 130 may include one or more physical units. For example, the user interface 130 may include an audio interface for performing audio communication with a user, and a touch display for performing visual and touch-based communication withthe user.

[0033] The electronic communication unit 140 can transmit, receive, or transmit and receive signals via a wired or wireless electronic communication medium 180, such as a radio frequency (RF) communication medium, an ultraviolet (UV) communication medium, a visible light communication medium, a fiber optic communication medium, a wireline communication medium, or a combination thereof. For example, as shown, the electronic communication unit 140 is operatively connected to an electronic communication interface 142, such as an antenna, configured to communicate via wireless signals.

[0034] Although the electronic communication interface 142 is shown as a wireless antenna in FIG. 1, the electronic communication interface 142 can be a wireless antenna, as shown, a wired communication port, such as an Ethernet port, an infrared port, a serial port, or any other wired or wireless unit capable of interfacing with a wired or wireless electronic communication medium 180. Although FIG. 1 shows a single electronic communication unit 140 and a single electronic communication interface 142, any number of electronic communication units and any number of electronic communication interfaces can be used.

[0035] The sensor 150 may include, for example, an audio-sensing device, a visible light- sensing device, a motion sensing device, or a combination thereof. For example, 100the sensor 150 may include a sound-sensing device, such as a microphone, or any other sound- sensing device now existing or hereafter developed that can sense sounds in the proximity of the computing device 100, such as speech or other utterances, made by a user operating the computing device 100. In another example, the sensor 150 may include a camera, or any other image-sensing device now existing or hereafter developed that can sense an image such as the image of a user operating the computing device. Although a single sensor 150 is shown, the computing device 100 may include a number of sensors 150. For example, the computing device 100 may include a first camera oriented with a field of view directed toward a user of the computing device 100 and a second camera oriented with a field of view directed away from the user of the computing device 100.

[0036] The power source 160 can be any suitable device for powering the computing device 100. For example, the power source 160 can include a wired external power source interface; one or more dry cell batteries, such as nickel-cadmium (NiCd), nickel-zinc (NiZn), nickel metal hydride (NiMH), lithium-ion (Li-ion); solar cells; fuel cells; or any other device capable of powering the computing device 100. Although a single power source 160 is shown in FIG. 1, the computing device 100 may include multiple power sources 160, such as a battery and a wired external power source interface.

[0037] Although shown as separate units, the electronic communication unit 140, the electronic communication interface 142, the user interface 130, the power source 160, or portions thereof, may be configured as a combined unit. For example, the electronic communication unit 140, the electronic communication interface 142, the user interface 130, and the power source 160 may be implemented as a communications port capable of interfacing with an external display device, providing communications, power, or both.

[0038] One or more of the memory 110, the processor 120, the user interface 130, the electronic communication unit 140, the sensor 150, or the power source 160, may be operatively coupled via a bus 170. Although a single bus 170 is shown in FIG. 1, a computing device 100 may include multiple buses. For example, the memory 110, the processor 120, the user interface 130, the electronic communication unit 140, the sensor 150, and the bus 170 may receive power from the power source 160 via the bus 170. In another example, the memory 110, the processor 120, the user interface 130, the electronic communication unit 140, the sensor 150, the power source 160, or a combination thereof, may communicate data, such as by sending and receiving electronic signals, via the bus 170.

[0039] Although not shown separately in FIG. 1, one or more of the processor 120, the user interface 130, the electronic communication unit 140, the sensor 150, or the power source 160 may include internal memory, such as an internal buffer or register. For example, the processor 120 may include internal memory (not shown) and may read data 112 from the memory 110 into the internal memory (not shown) for processing.

[0040] Although shown as separate elements, the memory 110, the processor 120, the user interface 130, the electronic communication unit 140, the sensor 150, the power source 160, and the bus 170, or any combination thereof can be integrated in one or more electronic units, circuits, or chips.

[0041] FIG. 2 is a diagram of a computing and communications system 200 in accordance with implementations of this disclosure. The computing and communications system 200 shown includes computing and communication devices 100A, 100B, 100C, access points 210A, 210B, and a network 220. For example, the computing and communication system 200 can be a multiple access system that provides communication, such as voice, audio, data, video, messaging, broadcast, or a combination thereof, to one or more wired or wireless communicating devices, such as the computing and communication devices 100A, 100B, 100C. Although, for simplicity, FIG. 2 shows three computing and communication devices 100A, 100B, 100C, two access points 210A, 210B, and one network 220, any number of computing and communication devices, access points, and networks can be used.

[0042] A computing and communication device 100A, 100B, 100C can be, for example, a computing device, such as the computing device 100 shown in FIG. 1. For example, the computing and communication devices 100A, 100B may be user devices, such as a mobile computing device, a laptop, a thin client, or a smartphone, and the computing and communication device 100C may be a server, such as a mainframe or a cluster. Although the computing and communication device 100A and the computing and communication device 100B are described as user devices, and the computing and communication device 100C is described as a server, any computing and communication device may perform some or all of the functions of a server, some, or all, of the functions of a user device, or some or all of the functions of a server and a user device. For example, the server computing and communication device 100C may receive, encode, process, store, transmit, or a combination thereof audio data and one or both of the computing and communication device 100A and the computing and communication device 100B may receive, decode, process, store, present, or a combination thereof the audio data.

[0043] Each computing and communication device 100A, 100B, 100C, which may include a user equipment (UE), a mobile station, a fixed or mobile subscriber unit, a cellular telephone, a personal computer, a tablet computer, a server, consumer electronics, or any similar device, can be configured to perform wired or wireless communication, such as via the network 220. For example, the computing and communication devices 100A, 100B, 100C can be configured to transmit or receive wired or wireless communication signals. Although each computing and communication device 100A, 100B, 100C is shown as a single unit, a computing and communication device can include any number of interconnected elements.

[0044] Each access point 210A, 210B can be any type of device configured to communicate with a computing and communication device 100A, 100B, 100C, a network 220, or both via wired or wireless communication links 180A, 180B, 180C. For example, an access point 210A, 210B can include a base station, a base transceiver station (BTS), a Node- B, an enhanced Node-B (eNode-B), a Home Node-B (HNode-B), a wireless router, a wired router, a hub, a relay, a switch, or any similar wired or wireless device. Although each access point 210A, 210B is shown as a single unit, an access point can include any number of interconnected elements.

[0045] The network 220 can be any type of network configured to provide services, such as voice, data, applications, voice over internet protocol (VoIP), or any other communications protocol or combination of communications protocols, over a wired or wireless communication link. For example, the network 220 can be a local area network (LAN), widearea network (WAN), virtual private network (VPN), a mobile or cellular telephone network, the Internet, or any other means of electronic communication. The network can use a communication protocol, such as the transmission control protocol (TCP), the user datagram protocol (UDP), the internet protocol (IP), the real-time transport protocol (RTP) the HyperText Transport Protocol (HTTP), or a combination thereof.

[0046] The computing and communication devices 100A, 100B, 100C can communicate with each other via the network 220 using one or more a wired or wireless communication links, or via a combination of wired and wireless communication links. For example, as shown the computing and communication devices 100A, 100B can communicate via wireless communication links 180A, 180B, and computing and communication device 100C can communicate via a wired communication link 180C. Any of the computing and communication devices 100A, 100B, 100C may communicate using any wired or wireless communication link, or links. For example, a first computing and communication device 100A can communicate via a first access point 210A using a first type of communication link, a second computing and communication device 100B can communicate via a second access point 210B using a second type of communication link, and a third computing and communication device 100C can communicate via a third access point (not shown) using a third type of communication link. Similarly, the access points 210A, 210B can communicate with the network 220 via one or more types of wired or wireless communication links 230A, 230B. Although FIG. 2 shows the computing and communication devices 100A, 100B, 100C in communication via the network 220, the computing and communication devices 100A, 100B, 100C can communicate with each other via any number of communication links, such as a direct wired or wireless communication link.

[0047] In some implementations, communications between one or more of the computing and communication device 100A, 100B, 100C may omit communicating via the network 220 and may include transferring data via another medium (not shown), such as a data storage device. For example, the server computing and communication device 100C may store audio data, such as encoded audio data, in a data storage device, such as a portable data storage unit, and one or both of the computing and communication device 100A or the computing and communication device 100B may access, read, or retrieve the stored audio data from the data storage unit, such as by physically disconnecting the data storage device from the server computing and communication device 100C and physically connecting the data storage device to the computing and communication device 100A or the computing and communication device 100B.

[0048] Other implementations of the computing and communications system 200 are possible. For example, in an implementation, the network 220 can be an ad-hoc network and can omit one or more of the access points 210A, 210B. The computing and communications system 200 may include devices, units, or elements not shown in FIG. 2. For example, the computing and communications system 200 may include many more communicating devices, networks, and access points.

[0049] FIG. 3 is a diagram of a video stream 300 for use in encoding and decoding in accordance with implementations of this disclosure. A video stream 300, such as a video stream captured by a video camera or a video stream generated by a computing device, may include a video sequence 310. The video sequence 310 may include a sequence of adjacent frames 320. Although three adjacent frames 320 are shown, the video sequence 310 can include any number of adjacent frames 320.

[0050] Each frame 330 from the adjacent frames 320 may represent a single image from the video stream. Although not shown in FIG. 3, a frame 330 may include one or more segments, tiles, or planes, which may be coded, or otherwise processed, independently, such as in parallel. A frame 330 may include one or more tiles 340. Each of the tiles 340 may be a rectangular region of the frame that can be coded independently. Each of the tiles 340 may include respective blocks 350. Although not shown in FIG. 3, a block can include pixels. For example, a block can include a 16×16 group of pixels, an 8×8 group of pixels, an 8×16 group of pixels, or any other group of pixels. Unless otherwise indicated herein, the term ‘block’ can include a superblock, a macroblock, a segment, a slice, or any other portion of a frame. A frame, a block, a pixel, or a combination thereof can include display information, such as luminance information, chrominance information, or any other information that can be used to store, modify, communicate, or display the video stream or a portion thereof.

[0051] FIG. 4 is a block diagram of an encoder 400 in accordance with implementations of this disclosure. Encoder 400 can be implemented in a device, such as the computing device 100 shown in FIG. 1 or the computing and communication devices 100A, 100B, 100C shown in FIG. 2, as, for example, a computer software program stored in a data storage unit, such as the memory 110 shown in FIG. 1. The computer software program can include machine instructions that may be executed by a processor, such as the processor 120 shown in FIG. 1, and may cause the device to encode video data as described herein. The encoder 400 can be implemented as specialized hardware included, for example, in computing device 100.

[0052] The encoder 400 can encode an input video stream 402, such as the video stream 300 shown in FIG. 3, to generate an encoded (compressed) bitstream 404. In someimplementations, the encoder 400 may include a forward path for generating the compressed bitstream 404. The forward path may include an intra / inter prediction unit 410, a transform unit 420, a quantization unit 430, an entropy encoding unit 440, or any combination thereof. In some implementations, the encoder 400 may include a reconstruction path (indicated by the broken connection lines) to reconstruct a frame for encoding of further blocks. The reconstruction path may include a dequantization unit 450, an inverse transform unit 460, a reconstruction unit 470, a filtering unit 480, or any combination thereof. Other structural variations of the encoder 400 can be used to encode the video stream 402.

[0053] For encoding the video stream 402, each frame within the video stream 402 can be processed in units of blocks. Thus, a current block may be identified from the blocks in a frame, and the current block may be encoded.

[0054] At the intra / inter prediction unit 410, the current block can be encoded using either intra-frame prediction, which may be within a single frame, or inter-frame prediction, which may be from frame to frame. Intra-prediction may include generating a prediction block from samples in the current frame that have been previously encoded and reconstructed. Inter- prediction may include generating a prediction block from samples in one or more previously constructed reference frames. Generating a prediction block for a current block in a current frame may include performing motion estimation to generate a motion vector indicating an appropriate reference portion of the reference frame.

[0055] The intra / inter prediction unit 410 may subtract the prediction block from the current block (raw block) to produce a residual block. The transform unit 420 may perform a block-based transform, which may include transforming the residual block into transform coefficients in, for example, the frequency domain. Examples of block-based transforms include the Karhunen-Loève Transform (KLT), the Discrete Cosine Transform (DCT), the Singular Value Decomposition Transform (SVD), and the Asymmetric Discrete Sine Transform (ADST). In an example, the DCT may include transforming a block into the frequency domain. The DCT may include using transform coefficient values based on spatial frequency, with the lowest frequency (i.e., DC) coefficient at the top-left of the matrix and the highest frequency coefficient at the bottom-right of the matrix.

[0056] The quantization unit 430 may convert the transform coefficients into discrete quantum values, which may be referred to as quantized transform coefficients or quantization levels. The quantized transform coefficients can be entropy encoded by the entropy encoding unit 440 to produce entropy-encoded coefficients. Entropy encoding can include using a probability distribution metric. The entropy-encoded coefficients and information used todecode the block, which may include the type of prediction used, motion vectors, and quantizer values, can be output to the compressed bitstream 404. The compressed bitstream 404 can be formatted using various techniques, such as run-length encoding (RLE) and zero- run coding.

[0057] The reconstruction path can be used to maintain reference frame synchronization between the encoder 400 and a corresponding decoder, such as the decoder 500 shown in FIG. 5. The reconstruction path may be similar to the decoding process discussed below and may include decoding the encoded frame, or a portion thereof, which may include decoding an encoded block, which may include dequantizing the quantized transform coefficients at the dequantization unit 450 and inverse transforming the dequantized transform coefficients at the inverse transform unit 460 to produce a derivative residual block. The reconstruction unit 470 may add the prediction block generated by the intra / inter prediction unit 410 to the derivative residual block to create a decoded block. The filtering unit 480 can be applied to the decoded block to generate a reconstructed block, which may reduce distortion, such as blocking artifacts. Although one filtering unit 480 is shown in FIG. 4, filtering the decoded block may include loop filtering, deblocking filtering, or other types of filtering or combinations of types of filtering. The reconstructed block may be stored or otherwise made accessible as a reconstructed block, which may be a portion of a reference frame, for encoding another portion of the current frame, another frame, or both, as indicated by the broken line at 482. Coding information, such as deblocking threshold index values, for the frame may be encoded, included in the compressed bitstream 404, or both, as indicated by the broken line at 484.

[0058] Other variations of the encoder 400 can be used to encode the compressed bitstream 404. For example, a non-transform-based encoder 400 can quantize the residual block directly without the transform unit 420. In some implementations, the quantization unit 430 and the dequantization unit 450 may be combined into a single unit.

[0059] FIG. 5 is a block diagram of a decoder 500 in accordance with implementations of this disclosure. The decoder 500 can be implemented in a device, such as the computing device 100 shown in FIG. 1 or the computing and communication devices 100A, 100B, 100C shown in FIG. 2, as, for example, a computer software program stored in a data storage unit, such as the memory 110 shown in FIG. 1. The computer software program can include machine instructions that may be executed by a processor, such as the processor 120 shown in FIG. 1, and may cause the device to decode video data as described herein. The decoder 500 can be implemented as specialized hardware included, for example, in computing device100.

[0060] The decoder 500 may receive a compressed bitstream 502, such as the compressed bitstream 404 shown in FIG. 4, and may decode the compressed bitstream 502 to generate an output video stream 504. The decoder 500 may include an entropy decoding unit 510, a dequantization unit 520, an inverse transform unit 530, an intra / inter prediction unit 540, a reconstruction unit 550, a filtering unit 560, or any combination thereof. Other structural variations of the decoder 500 can be used to decode the compressed bitstream 502.

[0061] The entropy decoding unit 510 may decode data elements within the compressed bitstream 502 using, for example, Context Adaptive Binary Arithmetic Decoding, to produce a set of quantized transform coefficients. The dequantization unit 520 can dequantize the quantized transform coefficients, and the inverse transform unit 530 can inverse transform the dequantized transform coefficients to produce a derivative residual block, which may correspond to the derivative residual block generated by the inverse transform unit 460 shown in FIG. 4. Using header information decoded from the compressed bitstream 502, the intra / inter prediction unit 540 may generate a prediction block corresponding to the prediction block created in the encoder 400. At the reconstruction unit 550, the prediction block can be added to the derivative residual block to create a decoded block. The filtering unit 560 can be applied to the decoded block to reduce artifacts, such as blocking artifacts, which may include loop filtering, deblocking filtering, or other types of filtering or combinations of types of filtering, and which may include generating a reconstructed block, which may be output as the output video stream 504.

[0062] Other variations of the decoder 500 can be used to decode the compressed bitstream 502. For example, the decoder 500 can produce the output video stream 504 without the deblocking filtering unit 560.

[0063] FIG. 6 is a block diagram of a representation of a portion 600 of a frame, such as the frame 330 shown in FIG. 3, in accordance with implementations of this disclosure. As shown, the portion 600 of the frame includes four 64×64 blocks 610, in two rows and two columns in a matrix or Cartesian plane. In some implementations, a 64×64 block may be a maximum coding unit, N=64. Each 64×64 block may include four 32×32 blocks 620. Each 32×32 block may include four 16×16 blocks 630. Each 16×16 block may include four 8×8 blocks 640. Each 8×8 block 640 may include four 4×4 blocks 650. Each 4×4 block 650 may include 16 pixels, which may be represented in four rows and four columns in each respective block in the Cartesian plane or matrix. The pixels may include information representing an image captured in the frame, such as luminance information, color information, and locationinformation. In some implementations, a block, such as a 16×16 pixel block as shown, may include a luminance block 660, which may include luminance pixels 662; and two chrominance blocks 670, 680, such as a U or Cb chrominance block 670, and a V or Cr chrominance block 680. The chrominance blocks 670, 680 may include chrominance pixels 690. For example, the luminance block 660 may include 16×16 luminance pixels 662 and each chrominance block 670, 680 may include 8×8 chrominance pixels 690 as shown. Although one arrangement of blocks is shown, any arrangement may be used. Although FIG. 6 shows N×N blocks, in some implementations, N×M blocks may be used. For example, 32×64 blocks, 64×32 blocks, 16×32 blocks, 32×16 blocks, or any other size blocks may be used. In some implementations, N×2N blocks, 2N×N blocks, or a combination thereof may be used.

[0064] In some implementations, video coding may include ordered block-level coding. Ordered block-level coding may include coding blocks of a frame in an order, such as raster- scan order, wherein blocks may be identified and processed starting with a block in the upper left corner of the frame, or portion of the frame, and proceeding along rows from left to right and from the top row to the bottom row, identifying each block in turn for processing. For example, the 64×64 block in the top row and left column of a frame may be the first block coded and the 64×64 block immediately to the right of the first block may be the second block coded. The second row from the top may be the second row coded, such that the 64×64 block in the left column of the second row may be coded after the 64×64 block in the rightmost column of the first row.

[0065] In some implementations, coding a block may include using quad-tree coding, which may include coding smaller block units within a block in raster-scan order. For example, the 64×64 block shown in the bottom left corner of the portion of the frame shown in FIG. 6, may be coded using quad-tree coding wherein the top left 32×32 block may be coded, then the top right 32×32 block may be coded, then the bottom left 32×32 block may be coded, and then the bottom right 32×32 block may be coded. Each 32×32 block may be coded using quad-tree coding wherein the top left 16×16 block may be coded, then the top right 16×16 block may be coded, then the bottom left 16×16 block may be coded, and then the bottom right 16×16 block may be coded. Each 16×16 block may be coded using quad-tree coding wherein the top left 8×8 block may be coded, then the top right 8×8 block may be coded, then the bottom left 8×8 block may be coded, and then the bottom right 8×8 block may be coded. Each 8×8 block may be coded using quad-tree coding wherein the top left 4×4 block may be coded, then the top right 4×4 block may be coded, then the bottom left 4×4block may be coded, and then the bottom right 4×4 block may be coded. In some implementations, 8×8 blocks may be omitted for a 16×16 block, and the 16×16 block may be coded using quad-tree coding wherein the top left 4×4 block may be coded, then the other 4×4 blocks in the 16×16 block may be coded in raster-scan order.

[0066] In some implementations, video coding may include compressing the information included in an original, or input, frame by, for example, omitting some of the information in the original frame from a corresponding encoded frame. For example, coding may include reducing spectral redundancy, reducing spatial redundancy, reducing temporal redundancy, or a combination thereof.

[0067] In some implementations, reducing spectral redundancy may include using a color model based on a luminance component (Y) and two chrominance components (U and V or Cb and Cr), which may be referred to as the YUV or YCbCr color model, or color space. Using the YUV color model may include using a relatively large amount of information to represent the luminance component of a portion of a frame and using a relatively small amount of information to represent each corresponding chrominance component for the portion of the frame. For example, a portion of a frame may be represented by a high- resolution luminance component, which may include a 16×16 block of pixels, and by two lower resolution chrominance components, each of which represents the portion of the frame as an 8×8 block of pixels. A pixel may indicate a value, for example, a value in the range from 0 to 255, and may be stored or transmitted using, for example, eight bits. Although this disclosure is described in reference to the YUV color model, any color model may be used.

[0068] In some implementations, reducing spatial redundancy may include transforming a block into the frequency domain using, for example, a discrete cosine transform (DCT). For example, a unit of an encoder, such as the transform unit 420 shown in FIG. 4, may perform a DCT using transform coefficient values based on spatial frequency.

[0069] In some implementations, reducing temporal redundancy may include using similarities between frames to encode a frame using a relatively small amount of data based on one or more reference frames, which may be previously encoded, decoded, and reconstructed frames of the video stream. For example, a block or pixel of a current frame may be similar to a spatially corresponding block or pixel of a reference frame. In some implementations, a block or pixel of a current frame may be similar to block or pixel of a reference frame at a different spatial location and reducing temporal redundancy may include generating motion information indicating the spatial difference, or translation, between the location of the block or pixel in the current frame and corresponding location of the block orpixel in the reference frame.

[0070] In some implementations, reducing temporal redundancy may include identifying a portion of a reference frame that corresponds to a current block or pixel of a current frame. For example, a reference frame, or a portion of a reference frame, which may be stored in memory, may be searched to identify a portion for generating a prediction to use for encoding a current block or pixel of the current frame with maximal efficiency. For example, the search may identify a portion of the reference frame for which the difference in pixel values between the current block and a prediction block generated based on the portion of the reference frame is minimized and may be referred to as motion searching. In some implementations, the portion of the reference frame searched may be limited. For example, the portion of the reference frame searched, which may be referred to as the search area, may include a limited number of rows of the reference frame. In an example, identifying the portion of the reference frame for generating a prediction may include calculating a cost function, such as a sum of absolute differences (SAD), between the pixels of portions of the search area and the pixels of the current block.

[0071] In some implementations, the spatial difference between the location of the portion of the reference frame for generating a prediction in the reference frame and the current block in the current frame may be represented as a motion vector. The difference in pixel values between the prediction block and the current block may be referred to as differential data, residual data, a prediction error, or as a residual block. In some implementations, generating motion vectors may be referred to as motion estimation, and a pixel of a current block may be indicated based on location using Cartesian coordinates as fx, y.Similarly, a pixel of the search area of the reference frame may be indicated based on location using Cartesian coordinates as rx, y.A motion vector (MV) for the current block may be determined based on, for example, a SAD between the pixels of the current frame and the corresponding pixels of the reference frame.

[0072] Although described herein with reference to matrix or Cartesian representation of a frame for clarity, a frame may be stored, transmitted, processed, or any combination thereof, in any data structure such that pixel values may be efficiently represented for a frame or image. For example, a frame may be stored, transmitted, processed, or any combination thereof, in a two-dimensional data structure such as a matrix as shown, or in a one- dimensional data structure, such as a vector array. In an implementation, a representation of the frame, such as a two-dimensional representation as shown, may correspond to a physicallocation in a rendering of the frame as an image. For example, a location in the top left corner of a block in the top left corner of the frame may correspond with a physical location in the top left corner of a rendering of the frame as an image.

[0073] In some implementations, block-based coding efficiency may be improved by partitioning input blocks into one or more prediction partitions, which may be rectangular, including square, partitions for prediction coding. In some implementations, video coding using prediction partitioning may include selecting a prediction partitioning scheme from among multiple candidate prediction partitioning schemes. For example, in some implementations, candidate prediction partitioning schemes for a 64×64 coding unit may include rectangular size prediction partitions ranging in sizes from 4×4 to 64×64, such as 4×4, 4×8, 8×4, 8×8, 8×16, 16×8, 16×16, 16×32, 32×16, 32×32, 32×64, 64×32, or 64×64. In some implementations, video coding using prediction partitioning may include a full prediction partition search, which may include selecting a prediction partitioning scheme by encoding the coding unit using each available candidate prediction partitioning scheme and selecting the best scheme, such as the scheme that produces the least rate-distortion error.

[0074] In some implementations, encoding a video frame may include identifying a prediction partitioning scheme for encoding a current block, such as block 610. In some implementations, identifying a prediction partitioning scheme may include determining whether to encode the block as a single prediction partition of maximum coding unit size, which may be 64×64 as shown, or to partition the block into multiple prediction partitions, which may correspond with the sub-blocks, such as the 32×32 blocks 620 the 16×16 blocks 630, or the 8×8 blocks 640, as shown, and may include determining whether to partition into one or more smaller prediction partitions. For example, a 64×64 block may be partitioned into four 32×32 prediction partitions. Three of the four 32×32 prediction partitions may be encoded as 32×32 prediction partitions and the fourth 32×32 prediction partition may be further partitioned into four 16×16 prediction partitions. Three of the four 16×16 prediction partitions may be encoded as 16×16 prediction partitions and the fourth 16×16 prediction partition may be further partitioned into four 8×8 prediction partitions, each of which may be encoded as an 8×8 prediction partition. In some implementations, identifying the prediction partitioning scheme may include using a prediction partitioning decision tree.

[0075] In some implementations, video coding for a current block may include identifying an optimal prediction coding mode from multiple candidate prediction coding modes, which may provide flexibility in handling video signals with various statistical properties and may improve the compression efficiency. For example, a video coder may evaluate each candidateprediction coding mode to identify the optimal prediction coding mode, which may be, for example, the prediction coding mode that minimizes an error metric, such as a rate-distortion cost, for the current block. In some implementations, the complexity of searching the candidate prediction coding modes may be reduced by limiting the set of available candidate prediction coding modes based on similarities between the current block and a corresponding prediction block. In some implementations, the complexity of searching each candidate prediction coding mode may be reduced by performing a directed refinement mode search. For example, metrics may be generated for a limited set of candidate block sizes, such as 16×16, 8×8, and 4×4, the error metric associated with each block size may be in descending order, and additional candidate block sizes, such as 4×8 and 8×4 block sizes, may be evaluated.

[0076] In some implementations, block-based coding efficiency may be improved by partitioning a current residual block into one or more transform partitions, which may be rectangular, including square, partitions for transform coding. In some implementations, video coding, such as video coding using transform partitioning, may include selecting a uniform transform partitioning scheme. For example, a current residual block, such as block 610, may be a 64×64 block and may be transformed without partitioning using a 64×64 transform.

[0077] Although not expressly shown in FIG. 6, a residual block may be transform partitioned using a uniform transform partitioning scheme. For example, a 64×64 residual block may be transform partitioned using a uniform transform partitioning scheme including four 32×32 transform blocks, using a uniform transform partitioning scheme including sixteen 16×16 transform blocks, using a uniform transform partitioning scheme including sixty-four 8×8 transform blocks, or using a uniform transform partitioning scheme including 2564×4 transform blocks.

[0078] In some implementations, video coding, such as video coding using transform partitioning, may include identifying multiple transform block sizes for a residual block using multiform transform partition coding. In some implementations, multiform transform partition coding may include recursively determining whether to transform a current block using a current block size transform or by partitioning the current block and multiform transform partition coding each partition. For example, the bottom left block 610 shown in FIG. 6 may be a 64×64 residual block, and multiform transform partition coding may include determining whether to code the current 64×64 residual block using a 64×64 transform or to code the 64×64 residual block by partitioning the 64×64 residual block into partitions, suchas four 32×32 blocks 620, and multiform transform partition coding each partition. In some implementations, determining whether to transform partition the current block may be based on comparing a cost for encoding the current block using a current block size transform to a sum of costs for encoding each partition using partition size transforms.

[0079] FIG. 7 is a block diagram of an encoder implementing transform selection 700 in accordance with implementations of this disclosure. The encoder implementing transform selection 700 can be implemented in a device, such as the computing device 100 shown in FIG. 1 or the computing and communication devices 100A, 100B, 100C shown in FIG. 2, as, for example, a computer software program stored in a data storage unit, such as the memory 110 shown in FIG. 1. The computer software program can include machine instructions that may be executed by a processor, such as the processor 120 shown in FIG. 1, and may cause the device to encode video data as described herein. The encoder implementing transform selection 700 can be implemented as specialized hardware included, for example, in computing device 100. The encoder implementing transform selection 700 is similar to the encoder 400 shown in FIG. 4, except as is described herein or as is otherwise clear from context.

[0080] The encoder implementing transform selection 700 encodes an input video stream 702, such as the video stream 300 shown in FIG. 3, to generate an encoded (compressed) bitstream 704. In some implementations, the encoder implementing transform selection 700 includes a forward path for generating the compressed bitstream 704. The forward path includes an intra / inter prediction unit 710, a transform unit 720, a quantization unit 730, an entropy encoding unit 740, or any combination thereof. In some implementations, the encoder implementing transform selection 700 includes a reconstruction path (indicated by the broken connection lines) to reconstruct a frame for encoding of further blocks. The reconstruction path includes a dequantization unit 750, an inverse transform unit 760, a filtering unit 770, or any combination thereof. Other structural variations of the encoder implementing transform selection 700 can be used to encode the video stream 702.

[0081] For encoding the video stream 702, each frame within the video stream 702 can be processed in units of blocks. Thus, a current block may be identified from the blocks in a frame, and the current block may be encoded.

[0082] The intra / inter prediction unit 710 is similar to the intra / inter prediction unit 410 shown in FIG. 4, except as is described herein or as is otherwise clear from context. Intra- prediction includes generating a prediction block from samples in the current frame that have been previously encoded and reconstructed. Inter-prediction includes generating a predictionblock (prediction block data) from samples in one or more previously constructed reference frames. The intra / inter prediction unit 710 subtracts the prediction block from the current block (raw block) to produce a residual block (residual block data).

[0083] The transform unit 720 is similar to the transform unit 420 shown in FIG. 4, except as is described herein or as is otherwise clear from context. The transform unit 720 performs a block-based transform, which includes transforming the residual block into transform coefficients in, for example, the frequency domain.

[0084] The transform unit 720 selects, determines, identifies, or obtains an optimal transform from available transforms for transforming the residual block data. Identifying the optimal transform includes identifying an optimal transform type from available transform types and an optimal transform size from available transform sizes. Examples of available transform types include the Karhunen-Loève Transform (KLT), the Discrete Cosine Transform (DCT), the Singular Value Decomposition Transform (SVD), and the Asymmetric Discrete Sine Transform (ADST). The transform type may be indicated by a transform type identifier. Examples of available transform sizes include 4×4, 4×8, 8×4, 4×16, 16×4, 8×8, 8×16, 16×8, 8×32, 32×8, 16×16, 16×32, 32×16, 16×64, 64×16, 32×32, 32×64, 64×32, or 64×64. An available transform may be a combination or tuple of an available transform type and an available transform size.

[0085] The transform unit 720 selects, determines, identifies, or obtains the optimal transform, including an optimal transform type, an optimal transform size, or both by evaluating the available transforms, such as two or more of the available transforms, wherein evaluating a respective available transform includes evaluating an available transform type and an available transform size (n×m).

[0086] Evaluating the respective available transform includes obtaining candidate transform block data by transforming the residual block data using the respective available transform.

[0087] Evaluating the respective available transform includes obtaining candidate quantized block data by quantizing the candidate transform block data by the quantization unit 730. The quantization unit 730 is similar to the quantization unit 430 shown in FIG. 4, except as is described herein or as is otherwise clear from context.

[0088] Evaluating the respective available transform includes obtaining candidate dequantized transform block data (c) by dequantizing the candidate quantized block data by the dequantization unit 750. The dequantization unit 750 is similar to the dequantization unit 450 shown in FIG. 4, except as is described herein or as is otherwise clear from context.

[0089] Evaluating the respective available transform includes obtaining candidate decoded residual block data (r) by inverse transforming the candidate dequantized transform block data by the inverse transform unit 760 using an inverse transform (T) corresponding to the respective available transform (r=Tc). The inverse transform unit 760 is similar to the inverse transform unit 460 shown in FIG. 4, except as is described herein or as is otherwise clear from context.

[0090] Evaluating the respective available transform includes obtaining candidate decoded block data (q) by combining the prediction block data (p) and the candidate decoded residual block data (r) by the inverse transform unit 760 (q = p + r).

[0091] Evaluating the respective available transform includes obtaining one or more rate- distortion optimization metrics, such as a distortion metric, an encoding cost metric (rate), or both, for encoding the current block using the respective available transform, based on the candidate decoded block data (q = p + r) obtained using the respective available transform. For example, obtaining the distortion metric may include determining a difference, such as a sum of absolute differences (SAD), between the candidate decoded block data (q) and the current block data.

[0092] Evaluating the available transforms includes the transform unit 720 comparing the rate-distortion optimization metric, or metrics, obtained for a first available transform with a comparable rate-distortion optimization metric, or metrics, obtained for a second available transform, as indicated by the broken directional line at 762. Selecting, determining, identifying, or obtaining the optimal transform omits, skips, excludes, or otherwise avoids filtering the decoded block data (q = p + r), such as by the filtering unit 770.

[0093] The transform unit 720 selects, determines, identifies, or obtains, as the optimal transform, the available transform corresponding to the minimal rate-distortion optimization metric, or metrics.

[0094] The quantized transform coefficients obtained using the optimal transform are entropy encoded by the entropy encoding unit 740 to produce entropy-encoded coefficients. The entropy encoding unit 740 is similar to the entropy encoding unit 440 shown in FIG. 4, except as is described herein or as is otherwise clear from context. The entropy-encoded coefficients and information used to decode the block, which may include the type of prediction used, motion vectors, and quantizer values, can be output to the compressed bitstream 704. The compressed bitstream 704 is similar to the compressed bitstream 404 shown in FIG. 4, except as is described herein or as is otherwise clear from context.

[0095] The filtering unit 770 is applied to the decoded block data (q = p + r) obtainedusing the optimal transform to generate a reconstructed block, which may reduce distortion, such as blocking artifacts. The filtering unit 770 is similar to the filtering unit 480 shown in FIG. 4, except as is described herein or as is otherwise clear from context. Although one filtering unit 770 is shown in FIG. 7, filtering the decoded block includes loop filtering, deblocking filtering, or other types of filtering or combinations of types of filtering. The reconstructed block may be stored or otherwise made accessible as a reconstructed block, which may be a portion of a reference frame, for encoding another portion of the current frame, another frame, or both, as indicated by the broken line at 772. Coding information, such as deblocking threshold index values, for the frame may be encoded, included in the compressed bitstream 704, or both, as indicated by the broken line at 774.

[0096] Other variations of the encoder implementing transform selection 700 can be used to encode the compressed bitstream 704.

[0097] FIG. 8 is a flowchart diagram of an example of encoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 800 in accordance with implementations of this disclosure. Encoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 800 may be implemented by an encoder, such as the encoder 400 shown in FIG. 4.

[0098] Encoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 800 includes encoding an input video steam, such as the input video stream 402 shown in FIG. 4, or one or more portions thereof, to generate an encoded (compressed) output bitstream, such as the encoded (compressed) bitstream 404 shown in FIG. 4.

[0099] In block-based hybrid video coding, to reduce, or minimize, the resource utilization, such as bandwidth utilization, for signaling, storing, or both, compressed, or encoded, video data, redundant data, such as spatially redundant data, temporally redundant data, or both, is omitted or excluded from the compressed, or encoded, data. The amount, such as the number, count, or cardinality, of bits, of encoded data for a portion of a video, such as a sequence of frames, a frame, or a block, is the bitrate, or rate (R), for encoding the respective portion. Differences between a reconstructed portion of the encoded, or compressed, video and the input, or source, video portion may be used as a metric, or measure, of distortion (D) caused by the coding process, which corresponds to quality loss with respect to the reconstructed video. Optimal video coding minimizes distortion (D), in accordance with rate (R) limitations or targets. A combination of rate (R) and distortion (D)may be used as a metric, or measure, (cost) of encoding optimization.

[0100] To maximize encoding optimization, such as to minimize distortion (D) in accordance with rate (R) limitations or targets, the encoder performs rate-distortion optimization (RDO) for a portion, such as a block, of a video or frame, wherein the encoder identifies, or determines, encoding parameters from among candidate encoding parameters that maximize encoding optimization. For example, rate-distortion optimization may include determining prediction block, or subblock, sizes, transform block, or subblock, sizes, or both. In another example, rate-distortion optimization may include a mode decision that includes determining, identifying, or selecting, a prediction mode, such as an intra prediction mode or an inter prediction mode, for encoding a portion, such as a block, of a video or frame. Rate- distortion optimization includes determining a respective cost, such as based on a combination of rate (R), or rate value, and distortion (D), or approximations thereof, for respective sets of one or more coding parameters and identifying, or selecting, the set of coding parameters corresponding to the minimal cost, among the sets of coding parameters, as the parameters for codding the current portion, such as the current block, of the video or frame.

[0101] For example, in a block-based mode decision, the encoder identifies, as the encoding mode for a current block, a candidate mode that has a minimal rate-distortion cost, or rate-distortion optimization cost value, (^) among the rate-distortion costs for the candidate modes. For a respective candidate mode, the encoder obtains, such as by calculating or otherwise accessing, a value of a rate metric (^^) corresponding to encoding the currentblock using the candidate mode. The encoder obtains a value of a distortion metric (^^)representing, or measuring, differences between a source image (^^), or a portion thereofcorresponding to the current block, and a candidate reconstructed image (^^^), or a portionthereof corresponding to the current block. In some implementations, the distortion may be determined as the squared (ℓ^) error (^^= ||^^− ^^^||^) between the source image (^^)and the reconstructed image (^^^). Other distortion metrics may be used. In someimplementations, a rate-distortion cost, or rate-distortion cost value, (^) may be obtained for a candidate reconstructed block (^) using a rate-distortion optimization cost function that obtains, such as calculates, a sum of the value of the distortion metric (^(^)) and a result ofmultiplying the value of the rate metric (^) by a Lagrangian multiplier (^), which may beexpressed as the following:^ = ^(^) + ^^. [Equation 1]

[0102] In encoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 800 rate-distortion optimization includes identifying one or more transforms, and corresponding inverse transforms, for encoding the current block.

[0103] Encoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 800 includes obtaining an input block (at 810), obtaining encoded block data (at 820), and outputting an encoded bitstream (at 830). Although not shown expressly in FIG. 8, encoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 800 includes other aspects of video coding.

[0104] Obtaining the input, current, or source, block (at 810), such as one of the blocks 350 shown in FIG. 3 or a block as shown in FIG. 6, includes obtaining an input, current, or source frame, such a frame, such as the frame 330 shown in FIG. 3, from one or more frames, such as the frames 320 shown in FIG. 3, such as from a sequence of frames, such as the video sequence 310 shown in FIG. 3, such as from a video, such as the video stream 300 shown in FIG. 3 or the input video stream 402 shown in FIG. 4.

[0105] In some implementations, input video data is obtained (at 810). The input video data includes a sequence of frames (input frames). For example, the encoder, or a component thereof, such as an intra / inter prediction unit of the encoder, such as the intra / inter prediction unit 410 shown in FIG. 4, may obtain the input video stream.

[0106] The current frame for encoding is obtained (at 810), such as from the sequence of frames from the input video data. The current frame may be obtained (at 810) subsequent to encoding one or more other frames, such as a frame sequentially preceding the current frame in the input video stream, and generating, or otherwise obtaining, a corresponding reconstructed frame (or frames), or one or more portions thereof, for use as a reference frame (or frames) for encoding the current frame.

[0107] The current block for encoding is obtained (at 810) from the current frame. The current block may be obtained (at 810) subsequent to encoding one or more other blocks, such as a block sequentially preceding the current block in the current frame, in accordance with a block coding order for coding the current frame, and generating, or otherwise obtaining, a corresponding reconstructed block, or one or more portions thereof.

[0108] Obtaining the encoded block data (at 820) includes rate-distortion optimization (at840) for encoding the current block (obtained at 810). Obtaining the encoded block data (at 820) may include other aspects of encoding not expressly shown in FIG. 8.

[0109] Rate-distortion optimization (at 840) includes identifying, or selecting, encoding parameters, or a set thereof, for encoding the current block from among multiple available parameters, or sets thereof. A broken directional line is shown (at 845) to indicate that rate- distortion optimization (at 840) includes evaluating two or more encoding parameters, or sets thereof, for encoding the current block from among multiple available parameters, or sets thereof.

[0110] Rate-distortion optimization (at 840) includes, for a respective set of current candidate encoding parameters from among multiple available parameters, or sets thereof, such as a current candidate transform, obtaining a current candidate encoded block by encoding the current block (current input block) using the current candidate set of encoding parameters, obtaining a current candidate reconstructed block by decoding and reconstructing the current candidate encoded block, and obtaining a rate-distortion cost, or score, for encoding the current block using the current candidate set of encoding parameters. The rate- distortion cost, value, or score, for encoding the current block using a respective candidate set of encoding parameters is obtained using a rate-distortion optimization cost function. The candidate encoding parameters corresponding to the minimal cost, or score, are identified as the coding parameters for the current block.

[0111] Rate-distortion optimization (at 840) includes obtaining prediction block data (a prediction, or predicted, block) for encoding the current block (not expressly shown in FIG. 8).

[0112] Rate-distortion optimization (at 840) includes obtaining residual block data indicating a difference between the current block and prediction block data for the current block (not expressly shown in FIG. 8).

[0113] Rate-distortion optimization (at 840) includes identifying a current, or candidate, transform (at 850) for transforming the residual block data.

[0114] Identifying the current, or candidate, transform (at 850) includes identifying a transform type from among one or more available transform types. The available transform types may include a Discrete Cosine Transform (DCT), a Discrete Sine Transform (DST), and an Asymmetric Discrete Sine Transform (ADST). Other transform types may be used.

[0115] Identifying the current, or candidate, transform (at 850) includes identifying a transform size from among one or more available transform sizes. The available transform sizes may include rectangular size transforms ranging in sizes from 4×4 to 64×64, such as4×4, 4×8, 8×4, 8×8, 8×16, 16×8, 16×16, 16×32, 32×16, 32×32, 32×64, 64×32, or 64×64.

[0116] Rate-distortion optimization (at 840) includes identifying a corresponding inverse transform that includes transform size adaptive directional nonlinear filtering (at 860).

[0117] In some implementations, rate-distortion optimization (at 840) includes determining that the coding mode for the current block is an intra prediction mode and, in response, determining that corresponding inverse transforms that include transform size adaptive directional nonlinear filtering are available. In some implementations, rate-distortion optimization includes determining that the coding mode for the current block is an inter prediction mode and, in response, determining corresponding inverse transforms that include transform size adaptive directional nonlinear filtering are unavailable. In some implementations, corresponding inverse transforms that include transform size adaptive directional nonlinear filtering are available irrespective of prediction mode.

[0118] In some implementations, rate-distortion optimization includes determining that corresponding inverse transforms that include transform size adaptive directional nonlinear filtering are unavailable in response to a determination that the number, count, or cardinality, of zero value transform coefficients in a current, or candidate transform block data for the current block is below, such as less than, a defined threshold, such as four (4) or zero (0). In some implementations, corresponding inverse transforms that include transform size adaptive directional nonlinear filtering are available for transform blocks irrespective of the number, count, or cardinality, of zero value transform coefficients.

[0119] In some implementations, rate-distortion optimization includes determining that corresponding inverse transforms that include transform size adaptive directional nonlinear filtering are unavailable in response to a determination that the transform size is below, such as less than, a defined threshold. For example, rate-distortion optimization may include determining that corresponding inverse transforms that include transform size adaptive directional nonlinear filtering are unavailable in response to a determination that a maximum, or largest, dimension of the current transform size is less than a defined threshold, such as sixteen (16). In another example, rate-distortion optimization may include determining that corresponding inverse transforms that include transform size adaptive directional nonlinear filtering are unavailable in response to a determination that a minimum, or smallest, dimension of the current transform size is less than a defined threshold, such as eight (8). In another example, rate-distortion optimization may include determining that corresponding inverse transforms that include transform size adaptive directional nonlinear filtering are unavailable in response to a determination that the maximum, or largest, dimension of thecurrent transform size is less than a defined maximum transform dimension threshold, such as sixteen (16), or a determination that the minimum, or smallest, dimension of the current transform size is less than a defined minimum transform dimension threshold, such as eight (8).

[0120] Rate-distortion optimization (at 840) includes identifying an optimal transform, or a rate-distortion optimization optimal transform, from available transforms for transforming the residual block data by evaluating two or more of the available transforms. Identifying the optimal transform includes identifying an optimal transform type, or a rate-distortion optimization optimal transform type, and an optimal transform size, or a rate-distortion optimization optimal transform size.

[0121] As indicated by the broken directional line (at 845) rate-distortion optimization (at 840) includes evaluating two or more available transforms and identifying the transform corresponding to the rate-distortion optimization metric, or cost, as the optimal transform for coding the current block.

[0122] Evaluating the current, candidate, or respective available, transform (at 840) includes obtaining candidate transform block data by transforming the residual block data using the candidate transform (not expressly shown in FIG. 8).

[0123] Evaluating the current, candidate, or respective available, transform (at 840) includes obtaining candidate quantized block data by quantizing the candidate transform block data (not expressly shown in FIG. 8).

[0124] Evaluating the current, candidate, or respective available, transform (at 840) includes obtaining candidate dequantized transform block data (c), wherein c(n × 1), by dequantizing the candidate quantized block data (not expressly shown in FIG. 8).

[0125] Evaluating the current, candidate, or respective available, transform (at 840) includes obtaining candidate decoded residual block data by inverse transforming the candidate dequantized transform block data using the corresponding inverse transform that includes transform size adaptive directional nonlinear filtering (not expressly shown in FIG. 8).

[0126] Inverse transforming the candidate dequantized transform block data using the corresponding inverse transform that includes transform size adaptive directional nonlinear filtering includes obtaining the candidate decoded residual block data (r) (intermediate decoded block), such as by multiplying the candidate dequantized transform block data (c) by a transform matrix (T), wherein T(n×n), of the corresponding inverse transform, which may be expressed as the following:^ = ^^.

[0127] Inverse transforming the candidate dequantized transform block data includes obtaining candidate decoded block data (q) by combining the prediction block data (p) and the candidate decoded residual block data (r) (not expressly shown in FIG. 8), which maybe expressed as the following: ^ = ^ + ^.

[0128] Inverse transforming the candidate dequantized transform block data includes obtaining candidate reconstructed block data (d) by filtering the candidate decoded block data (q) using an optimal transform size adaptive directional nonlinear filter (N(.)) (not expressly shown in FIG. 8), which may be expressed as the following: ^ = ^(^).

[0129] The optimal transform size adaptive directional nonlinear filter (N(.)) is a filter that is optimal, transform size, adaptive, directional, and nonlinear. For example, the optimal transform size adaptive directional nonlinear filter (N(.)) is optimal in that the optimal transform size adaptive directional nonlinear filter (N(.)) is identified, selected, or determined, via rate-distortion optimization. In another example, the optimal transform size adaptive directional nonlinear filter (N(.)) is transform size in that the size of the optimal transform size adaptive directional nonlinear filter (N(.)) is the size of the transform block. In another example, the optimal transform size adaptive directional nonlinear filter (N(.)) is an adaptive filter, such as a pixel-adaptive filter, wherein the filter is derived on a per-pixel basis in conjunction with an artificial intelligence, or machine learning, model, such as an artificial neural network. To obtain, determine, or identify, the optimal transform size adaptive directional nonlinear filter (N(.)), the artificial neural network may derive a vector of combining scalars on a per-pixel basis, which may be combined with a filter-bank of filters to derive a filter on a per-pixel basis. Using the optimal transform size adaptive directional nonlinear filter (N(.)) may including applying the per-pixel filter to image, or pixel, values in the neighborhood, such as within a defined distance, of the respective pixel to obtain a filtered value for the respective pixel. In some implementations, the optimal transform size adaptive directional nonlinear filter (N(.)), or one or more aspects, such as an identifier, thereof, may be indicated in the encoded bitstream. In some implementations, the optimal transform size adaptive directional nonlinear filter (N(.)) may be a non-separable filter.

[0130] The size of the optimal transform size adaptive directional nonlinear filter (N(.)) is the size of the optimal transform, or of the corresponding inverse transform. For example, the inverse transform may be a 16×16 transform, and the optimal transform size adaptivedirectional nonlinear filter (N(.)) is a 16×16 filter. In some implementations, the optimal transform size adaptive directional nonlinear filter (N(.)) is a denoising filter, such as a weighted averaging denoising filter with overcomplete dictionaries, or a weighted overcomplete denoising filter. In some implementations, the optimal transform size adaptive directional nonlinear filter (N(.)) is a contextually-designed filter.

[0131] Obtaining the encoded block data (at 820) includes including the candidate quantized block data obtained using the optimal transform in the encoded bitstream.

[0132] Although not expressly shown in FIG. 8, in some implementations, the reconstructed block data (d) may be further processed, subsequent to obtaining the encoded block data (at 820), such as in the reconstruction, or decoding, path of the encoder, such as using reconstruction filtering, such as loop filtering, or other post-processing filtering. The reconstruction filtering is similar to the filtering shown (at 480) in FIG. 4, the filtering shown (at 560) in FIG. 5, or the filtering shown (at 770) in FIG. 7, except as is described herein or as is otherwise clear from context. Reconstruction filtering is separate and distinct from the transform size adaptive directional nonlinear filtering. Identifying the transform corresponding to the rate-distortion optimization metric, or cost, as the optimal transform for coding the current block is performed prior to and independent of the reconstruction filtering.

[0133] Although not expressly shown in FIG. 8, in some implementations, the candidate decoded block data (q) may be further processed, subsequent to obtaining the encoded block data (at 820), such as in the reconstruction, or decoding, path of the encoder, such as using reconstruction filtering, such as loop filtering, or other post-processing filtering. The reconstruction filtering is similar to the filtering shown (at 480) in FIG. 4, the filtering shown (at 560) in FIG. 5, or the filtering shown (at 770) in FIG. 7, except as is described herein or as is otherwise clear from context. The reconstruction filtering is separate and distinct from the transform size adaptive directional nonlinear filtering. Identifying the transform corresponding to the rate-distortion optimization metric, or cost, as the optimal transform for coding the current block is performed prior to and independent of the reconstruction filtering.

[0001] The output, compressed, or encoded, bitstream, is output, such as stored or transmitted, such as to a decoder, (at 830).

[0002] In some implementations, the encoder includes data, such as a bit, flag, or other symbol, indicating that nonlinear transform filtering, such as the use of the transform size adaptive directional nonlinear filter, is enabled.

[0003] In some implementations, the encoder includes data, such as a bit, flag, or other symbol, indicating nonlinear transform filtering, such as the use of the transform sizeadaptive directional nonlinear filter, is disabled.

[0134] FIG. 9 is a flowchart diagram of an example of decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 900 in accordance with implementations of this disclosure. Decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 900 may be implemented in a decoder, such as the decoder 500 shown in FIG. 5. Decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 900 includes block-based hybrid video coding as described herein.

[0135] Decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 900 includes generating reconstructed video data by decoding an encoded bitstream, such as the compressed bitstream 502 shown in FIG. 5, or one or more portions thereof, to generate a reconstructed video, or a portion thereof, such as the output video stream 504 shown in FIG. 5.

[0136] Decoding the encoded bitstream, or one or more portions thereof, for decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 900, includes obtaining the encoded bitstream (at 910), obtaining transform data (at 920), inverse transformation (at 930), and outputting reconstructed video data (at 940). One or more aspects of decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 900 may be omitted from the description herein for simplicity and brevity.

[0137] The encoded bitstream is obtained (at 910). For example, the decoder, or a component thereof, such as an intra / inter prediction unit of the decoder, such as the entropy decoding unit 510 shown in FIG. 5, may obtain the encoded bitstream. Obtaining the encoded bitstream (at 910) includes identifying a current frame from a current sequence of frames to decode from the encoded bitstream to generate a current reconstructed frame. Obtaining the encoded bitstream (at 910) includes identifying a current block from the current frame. Obtaining the encoded bitstream (at 910) includes obtaining encoded block data for the current block from the encoded bitstream.

[0138] Transform data for an inverse transform, such as one or more transform parameters, such as transform type data indicating a transform type, transform size data indicating a transform size, or a combination thereof, is obtained (at 920), such as extracted, decoded, or otherwise accessed, from the encoded bitstream.

[0139] The encoded block data is dequantized to obtain dequantized transform coefficients(c), such as a dequantized transform block or dequantized transform block data. Obtaining the dequantized transform block data may include entropy decoding the encoded block data to obtain quantized transform coefficients, such as a quantized transform block or quantized transform block data, and dequantizing the quantized transform block data.

[0140] Although not expressly shown in FIG. 9, decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 900 includes obtaining prediction block data (p) for the current block.

[0141] Decoded residual block data (r) is obtained by inverse transforming the dequantized transform block data (at 930) in accordance with the transform data (obtained at 920), such as by applying an inverse transform (T) as identified by the transform data (obtained at 920) to the dequantized transform block data (r=Tc).

[0142] Inverse transforming the dequantized transform block data (at 930) includes obtaining intermediate decoded block data (q) by combining the decoded residual block data with the prediction block data for the current block (q = p + r).

[0143] Inverse transforming the dequantized transform block data (at 930) includes obtaining a transform size adaptive directional nonlinear filter, such as the optimal transform size adaptive directional nonlinear filter (N(.)) identified (at 840) in FIG. 8. The decoder obtains the transform size adaptive directional nonlinear filter in accordance with the transform data (obtained at 920). In some implementations, the transform data (obtained at 920) may include data, such as a bit, flag, or other symbol, indicating whether nonlinear transform filtering, such as the use of the transform size adaptive directional nonlinear filter, is enabled. In response to determining that the data indicating whether nonlinear transform filtering, such as the use of the transform size adaptive directional nonlinear filter, is enabled indicates that nonlinear transform filtering, such as the use of the transform size adaptive directional nonlinear filter, is disabled, inverse transforming the dequantized transform block data (at 930) omits, skips, avoids, or excludes filtering using the transform size adaptive directional nonlinear filter.

[0144] Inverse transforming the dequantized transform block data (at 930) includes obtaining the decoded block data (d) by filtering the intermediate decoded block data (q) using the transform size adaptive directional nonlinear filter (N(.)), which may be expressed as (d = N(q)).

[0145] Although not expressly shown in FIG. 9, reconstructed block data is obtained by reconstruction filtering the decoded block data (d), which may include loop filtering, deblocking filtering, or other types of filtering or combinations of types of filtering. Thereconstruction filtering is similar to the filtering shown (at 480) in FIG. 4, the filtering shown (at 560) in FIG. 5, or the filtering shown (at 770) in FIG. 7, except as is described herein or as is otherwise clear from context. The reconstruction filtering is separate and distinct from the transform size adaptive directional nonlinear filtering.

[0146] The decoder obtains reconstructed frame data for the current frame. To obtain the reconstructed frame data, the decoder includes the reconstructed block data in the reconstructed frame data for the current frame.

[0147] The decoder outputs the reconstructed frame data (at 940).

[0148] FIG. 10 is a block diagram of an encoder implementing transform selection with nonlinear inverse transforms 1000 in accordance with implementations of this disclosure. The encoder implementing transform selection with nonlinear inverse transforms 1000 can be implemented in a device, such as the computing device 100 shown in FIG. 1 or the computing and communication devices 100A, 100B, 100C shown in FIG. 2, as, for example, a computer software program stored in a data storage unit, such as the memory 110 shown in FIG. 1. The computer software program can include machine instructions that may be executed by a processor, such as the processor 120 shown in FIG. 1, and may cause the device to encode video data as described herein. The encoder implementing transform selection with nonlinear inverse transforms 1000 can be implemented as specialized hardware included, for example, in computing device 100. The encoder implementing transform selection with nonlinear inverse transforms 1000 is similar to the encoder 400 shown in FIG. 4, except as is described herein or as is otherwise clear from context. The encoder implementing transform selection with nonlinear inverse transforms 1000 is similar to the encoder implementing transform selection 700 shown in FIG. 7, except as is described herein or as is otherwise clear from context.

[0149] The encoder implementing transform selection with nonlinear inverse transforms 1000 implements encoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 800 as shown in FIG. 8.

[0150] The encoder implementing transform selection with nonlinear inverse transforms 1000 encodes an input video stream 1002, such as the video stream 300 shown in FIG. 3, to generate an encoded (compressed) bitstream 1004. In some implementations, the encoder implementing transform selection with nonlinear inverse transforms 1000 includes a forward path for generating the compressed bitstream 1004. The forward path includes an intra / inter prediction unit 1010, a transform unit 1020, a quantization unit 1030, an entropy encodingunit 1040, or any combination thereof. In some implementations, the encoder implementing transform selection with nonlinear inverse transforms 1000 includes a reconstruction path (indicated by the broken connection lines) to reconstruct a frame for encoding of further blocks. The reconstruction path includes a dequantization unit 1050, a nonlinear inverse transform unit 1060, a filtering unit 1070, or any combination thereof. Other structural variations of the encoder implementing transform selection with nonlinear inverse transforms 1000 can be used to encode the video stream 1002.

[0151] For encoding the video stream 1002, each frame within the video stream 1002 can be processed in units of blocks. Thus, a current block may be identified from the blocks in a frame, and the current block may be encoded. Identifying the current block may be similar to obtaining an input block as shown (at 810) in FIG. 8.

[0152] The intra / inter prediction unit 1010 is similar to the intra / inter prediction unit 710 shown in FIG. 7, except as is described herein or as is otherwise clear from context. Intra- prediction includes generating a prediction block from samples in the current frame that have been previously encoded and reconstructed. Inter-prediction includes generating a prediction block (prediction block data) from samples in one or more previously constructed reference frames. The intra / inter prediction unit 1010 subtracts the prediction block from the current block (raw block) to produce a residual block (residual block data).

[0153] The transform unit 1020 is similar to the transform unit 720 shown in FIG. 7, except as is described herein or as is otherwise clear from context. The transform unit 1020 performs a block-based transform, which includes transforming the residual block into transform coefficients in, for example, the frequency domain.

[0154] The transform unit 1020 selects, determines, identifies, or obtains an optimal transform from available transforms for transforming the residual block data. Identifying the optimal transform includes identifying an optimal transform type from available transform types and an optimal transform size from available transform sizes. Examples of available transform types include the Karhunen-Loève Transform (KLT), the Discrete Cosine Transform (DCT), the Singular Value Decomposition Transform (SVD), and the Asymmetric Discrete Sine Transform (ADST). The transform type may be indicated by a transform type identifier. Examples of available transform sizes include 4×4, 4×8, 8×4, 4×16, 16×4, 8×8, 8×16, 16×8, 8×32, 32×8, 16×16, 16×32, 32×16, 16×64, 64×16, 32×32, 32×64, 64×32, or 64×64. An available transform may be a combination or tuple of an available transform type and an available transform size.

[0155] The transform unit 1020 selects, determines, identifies, or obtains the optimaltransform, including an optimal transform type, an optimal transform size, or both by evaluating the available transforms, such as two or more of the available transforms, wherein evaluating a respective available transform includes evaluating an available transform type and an available transform size (n×m). Obtaining the optimal transform may be similar to the rate-distortion optimization shown (at 840) in FIG. 8.

[0156] Evaluating the respective available transform includes obtaining candidate transform block data by transforming the residual block data using the respective available transform.

[0157] Evaluating the respective available transform includes obtaining candidate quantized block data by quantizing the candidate transform block data by the quantization unit 1030. The quantization unit 1030 is similar to the quantization unit 730 shown in FIG. 7, except as is described herein or as is otherwise clear from context.

[0158] Evaluating the respective available transform includes obtaining candidate dequantized transform block data (c) by dequantizing the candidate quantized block data by the dequantization unit 1050. The dequantization unit 1050 is similar to the dequantization unit 750 shown in FIG. 7, except as is described herein or as is otherwise clear from context.

[0159] Evaluating the respective available transform includes obtaining candidate decoded residual block data (r) by inverse transforming the candidate dequantized transform block data by the nonlinear inverse transform unit 1060 using an inverse transform (T) corresponding to the respective available transform (r=Tc). The nonlinear inverse transform unit 1060 is similar to the inverse transform unit 760 shown in FIG. 7, except as is described herein or as is otherwise clear from context. The inverse transforming may be similar to the inverse transforming shown (at 860) in FIG. 8.

[0160] Evaluating the respective available transform includes obtaining intermediate decoded block data (q) by combining the prediction block data (p) and the candidate decoded residual block data (r) by the nonlinear inverse transform unit 1060 (q = p + r).

[0161] Evaluating the respective available transform includes obtaining candidate decoded block data (d) by filtering the intermediate decoded block data (q) using a candidate transform size adaptive directional nonlinear filter (N(.)), wherein the candidate transform size adaptive directional nonlinear filter is an adaptive directional nonlinear filter having a size equivalent to, or matching, the transform size of the respective available transform, which may be expressed as (d = N(q)).

[0162] Evaluating the respective available transform includes obtaining one or more rate- distortion optimization metrics, such as a distortion metric, an encoding cost metric (rate), orboth, for encoding the current block using the respective available transform, based on the candidate decoded block data (d = N(q)) obtained using the respective available transform and the corresponding candidate transform size adaptive directional nonlinear filter. For example, obtaining the distortion metric may include determining a difference, such as a sum of absolute differences (SAD), between the candidate decoded block data (d) and the current block data.

[0163] Evaluating the available transforms, such as evaluating two or more of the available transforms, includes the transform unit 1020 obtaining rate-distortion optimization costs for the available transforms on a per-available transform basis. Evaluating the available transforms, such as evaluating two or more of the available transforms, includes the transform unit 1020 comparing the rate-distortion optimization metric, or metrics, obtained for a first available transform, such as the respective available transform, with a comparable rate-distortion optimization metric, or metrics, obtained for a second available transform, as indicated by the broken directional line at 1062.

[0164] The transform unit 1020 selects, determines, identifies, or obtains, as the optimal transform, the available transform corresponding to the minimal rate-distortion optimization metric, or metrics. For example, the transform unit 1020 selects, determines, identifies, or obtains the respective available transform as the optimal transform for coding the current block in response to determining that, or a determination that, the respective available transform corresponds to a minimal rate-distortion optimization cost among the rate- distortion optimization costs.

[0165] The quantized transform coefficients obtained using the optimal transform are entropy encoded by the entropy encoding unit 1040 to produce entropy-encoded coefficients. The entropy encoding unit 1040 is similar to the entropy encoding unit 440 shown in FIG. 4, except as is described herein or as is otherwise clear from context. The entropy-encoded coefficients and information used to decode the block, which may include the type of prediction used, motion vectors, and quantizer values, can be output to the compressed bitstream 1004. The compressed bitstream 1004 is similar to the compressed bitstream 404 shown in FIG. 4, except as is described herein or as is otherwise clear from context.

[0166] The filtering unit 1070 reconstruction filters the decoded block data (d = N(q)) obtained using the optimal transform and the corresponding candidate transform size adaptive directional nonlinear filter to generate a reconstructed block, which may reduce distortion, such as blocking artifacts. The filtering unit 1070 is similar to the filtering unit 770 shown in FIG. 7, except as is described herein or as is otherwise clear from context. Although onefiltering unit 1070 is shown in FIG. 10, filtering the decoded block includes loop filtering, deblocking filtering, or other types of filtering or combinations of types of filtering. The reconstructed block may be stored or otherwise made accessible as a reconstructed block, which may be a portion of a reference frame, for encoding another portion of the current frame, another frame, or both, as indicated by the broken line at 1072. Coding information, such as deblocking threshold index values, for the frame may be encoded, included in the compressed bitstream 1004, or both, as indicated by the broken line at 1074. The reconstruction filtering applied by the filtering unit 1070 is separate and distinct from the transform size adaptive directional nonlinear filtering. Identifying the transform corresponding to the minimal rate-distortion optimization metric, or cost, as the optimal transform for coding the current block is performed prior to and independent of the reconstruction filtering. In some implementations, the filtering unit 1070 omits, skips, avoids, or excludes reconstruction filtering the decoded block data (d = N(q)) and the filtering unit 1070 reconstruction filters the intermediate decoded block data (q) to generate the reconstructed block, which may reduce distortion, such as blocking artifacts.

[0167] Other variations of the encoder implementing transform selection with nonlinear inverse transforms 1000 can be used to encode the compressed bitstream 1004.

[0168] FIG. 11 is a block diagram of a decoder implementing transform selection with nonlinear inverse transforms 1100 in accordance with implementations of this disclosure. The decoder implementing transform selection with nonlinear inverse transforms 1100 can be implemented in a device, such as the computing device 100 shown in FIG. 1 or the computing and communication devices 100A, 100B, 100C shown in FIG. 2, as, for example, a computer software program stored in a data storage unit, such as the memory 110 shown in FIG. 1. The computer software program can include machine instructions that may be executed by a processor, such as the processor 120 shown in FIG. 1, and may cause the device to decode video data as described herein. The decoder implementing transform selection with nonlinear inverse transforms 1100 can be implemented as specialized hardware included, for example, in computing device 100. The decoder implementing transform selection with nonlinear inverse transforms 1100 may be similar to the decoder 500 shown in FIG. 5, except as is described herein or as is otherwise clear from context.

[0169] The decoder implementing transform selection with nonlinear inverse transforms 1100 implements decoding using rate-distortion optimization including inverse transformation including transform size adaptive directional nonlinear filtering 900 as shown in FIG. 9.

[0170] The decoder implementing transform selection with nonlinear inverse transforms 1100 receives a compressed bitstream 1102, such as the compressed bitstream 404 shown in FIG. 4. The decoder implementing transform selection with nonlinear inverse transforms 1100 decodes the compressed bitstream 1102 to generate an output video stream 1104, which includes decoding encoded block data from the compressed bitstream 1102 to generate decoded block data for a current block of a current frame.

[0171] The decoder implementing transform selection with nonlinear inverse transforms 1100 includes an entropy decoding unit 1110, a dequantization unit 1120, an intra / inter prediction unit 1130, a nonlinear inverse transform unit 1140, a filtering unit 1150, or any combination thereof. Other structural variations of the decoder implementing transform selection with nonlinear inverse transforms 1100 may be used to decode the compressed bitstream 1102.

[0172] The entropy decoding unit 1110 decodes data elements, such as encoded block data for the current block, within the compressed bitstream 1102 using, for example, Context Adaptive Binary Arithmetic Decoding, to obtain quantized transform coefficients (quantized transform block data).

[0173] The decoder implementing transform selection with nonlinear inverse transforms 1100, or a component thereof, such as the entropy decoding unit 1110, obtains transform data for the current block from the encoded bitstream 1102. The transform data indicates a transform (or transform tuple) indicating a transform type and a transform size.

[0174] The dequantization unit 1120 dequantizes the quantized transform coefficients to obtain dequantized transform coefficients (dequantized transform block data). The dequantization unit 1120 is similar to the dequantization unit 520 shown in FIG. 5 or the dequantization unit 1050 shown in FIG. 10, except as is described herein or as is otherwise clear from context.

[0175] Using header information decoded from the compressed bitstream 1102, the intra / inter prediction unit 1130 generates a prediction block (prediction block data) corresponding to the prediction block created in the encoder implementing transform selection with nonlinear inverse transforms 1000 shown in FIG. 10. The intra / inter prediction unit 1130 is similar to the intra / inter prediction unit 1040 shown in FIG. 10, except as is described herein or as is otherwise clear from context.

[0176] The nonlinear inverse transform unit 1140 inverse transforms the dequantized transform coefficients in accordance with the transform data, such as using the inverse transform (the transform type and the transform size) indicated by the transform data, toproduce, or obtain, a derivative residual block (decoded residual block data), which may correspond to the decoded residual block data generated by the nonlinear inverse transform unit 1060 shown in FIG. 10.

[0177] The nonlinear inverse transform unit 1140 obtains intermediate decoded block data by combining, such as adding, the prediction block data for the current block and the decoded residual block data.

[0178] The nonlinear inverse transform unit 1140 obtains a transform size adaptive directional nonlinear filter having a size corresponding to, matching, or equal to the transform size, such as corresponding to the candidate transform size adaptive directional nonlinear filter (N(.)) corresponding to the optimal transform identified for the current block by the transform unit 1020 shown in FIG. 10.

[0179] The nonlinear inverse transform unit 1140 obtains the decoded block data (d) by filtering the intermediate decoded block data using the transform size adaptive directional nonlinear filter.

[0180] The reconstruction filtering unit 1150 applies one or more reconstruction filters to the decoded block data (d) to reduce artifacts, such as blocking artifacts, which may include loop filtering, deblocking filtering, or other types of reconstruction filtering or combinations of types of reconstruction filtering, and which may include generating a reconstructed block (reconstructed block data), which may be output as, or included in, the output video stream 1104. For example, the decoder implementing transform selection with nonlinear inverse transforms 1100 may include the reconstructed block data in reconstructed frame data for the current frame and may include the reconstructed frame data in the output video stream 1104. The reconstruction filtering performed by the reconstruction filtering unit 1150 is separate and distinct from the transform size adaptive directional nonlinear filtering implemented by the nonlinear inverse transform unit 1140.

[0181] Other variations of the decoder implementing transform selection with nonlinear inverse transforms 1100 can be used to decode the compressed bitstream 1102.

[0182] As used herein, the terms “optimal”, “optimized”, “optimization”, or other forms thereof, are relative to a respective context and are not indicative of absolute theoretic optimization unless expressly specified herein.

[0183] As used herein, the term “set” indicates a distinguishable collection or grouping of zero or more distinct elements or members that may be represented as a one-dimensional array or vector, except as expressly described herein or otherwise clear from context.

[0184] The words “example” or “exemplary” are used herein to mean serving as anexample, instance, or illustration. Any aspect or design described herein as “example” or “exemplary” not necessarily to be construed as preferred or advantageous over other aspects or designs. Rather, use of the words “example” or “exemplary” is intended to present concepts in a concrete fashion. As used in this application, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or”. That is, unless specified otherwise, or clear from context, “X includes A or B” is intended to mean any of the natural inclusive permutations. That is, if X includes A; X includes B; or X includes both A and B, then “X includes A or B” is satisfied under any of the foregoing instances. In addition, the articles “a” and “an” as used in this application and the appended claims should generally be construed to mean “one or more” unless specified otherwise or clear from context to be directed to a singular form. Moreover, use of the term “an embodiment” or “one embodiment” or “an implementation” or “one implementation” throughout is not intended to mean the same embodiment or implementation unless described as such. As used herein, the terms “determine” and “identify”, or any variations thereof, includes selecting, ascertaining, computing, looking up, receiving, determining, establishing, obtaining, or otherwise identifying or determining in any manner whatsoever using one or more of the devices shown in FIG. 1.

[0185] Further, for simplicity of explanation, although the figures and descriptions herein may include sequences or series of steps or stages, elements of the methods disclosed herein can occur in various orders and / or concurrently. Additionally, elements of the methods disclosed herein may occur with other elements not explicitly presented and described herein. Furthermore, one or more elements of the methods described herein may be omitted from implementations of methods in accordance with the disclosed subject matter.

[0186] The implementations of the transmitting computing and communication device 100A and / or the receiving computing and communication device 100B (and the algorithms, methods, instructions, etc. stored thereon and / or executed thereby) can be realized in hardware, software, or any combination thereof. The hardware can include, for example, computers, intellectual property (IP) cores, application-specific integrated circuits (ASICs), programmable logic arrays, optical processors, programmable logic controllers, microcode, microcontrollers, servers, microprocessors, digital signal processors or any other suitable circuit. In the claims, the term “processor” should be understood as encompassing any of the foregoing hardware, either singly or in combination. The terms “signal” and “data” are used interchangeably. Further, portions of the transmitting computing and communication device 100A and the receiving computing and communication device 100B do not necessarily haveto be implemented in the same manner.

[0187] Further, in one implementation, for example, the transmitting computing and communication device 100A or the receiving computing and communication device 100B can be implemented using a computer program that, when executed, carries out any of the respective methods, algorithms and / or instructions described herein. In addition, or alternatively, for example, a special purpose computer / processor can be utilized which can contain specialized hardware for carrying out any of the methods, algorithms, or instructions described herein.

[0188] The transmitting computing and communication device 100A and receiving computing and communication device 100B can, for example, be implemented on computers in a real-time video system. Alternatively, the transmitting computing and communication device 100A can be implemented on a server and the receiving computing and communication device 100B can be implemented on a device separate from the server, such as a hand-held communications device. In this instance, the transmitting computing and communication device 100A can encode content using an encoder 400 into an encoded video signal and transmit the encoded video signal to the communications device. In turn, the communications device can then decode the encoded video signal using a decoder 500. Alternatively, the communications device can decode content stored locally on the communications device, for example, content that was not transmitted by the transmitting computing and communication device 100A. Other suitable transmitting computing and communication device 100A and receiving computing and communication device 100B implementation schemes are available. For example, the receiving computing and communication device 100B can be a generally stationary personal computer rather than a portable communications device and / or a device including an encoder 400 may also include a decoder 500.

[0189] Further, all or a portion of implementations can take the form of a computer program product accessible from, for example, a tangible computer-usable or computer- readable medium. A computer-usable or computer-readable medium can be any device that can, for example, tangibly contain, store, communicate, or transport the program for use by or in connection with any processor. The medium can be, for example, an electronic, magnetic, optical, electromagnetic, or a semiconductor device. Other suitable mediums are also available.

[0190] It will be appreciated that aspects can be implemented in any convenient form. For example, aspects may be implemented by appropriate computer programs which may becarried on appropriate carrier media which may be tangible carrier media (e.g., disks) or intangible carrier media (e.g. communications signals). Aspects may also be implemented using suitable apparatus which may take the form of programmable computers running computer programs arranged to implement the methods and / or techniques disclosed herein. Aspects can be combined such that features described in the context of one aspect may be implemented in another aspect.

[0191] The above-described implementations have been described in order to allow easy understanding of the application are not limiting. On the contrary, the application covers various modifications and equivalent arrangements included within the scope of the appended claims, which scope is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structure as is permitted under the law.

Claims

CLAIMS What is claimed is:

1. A method comprising: generating encoded block data by encoding a current block from a current frame from an input video, wherein encoding the current block includes: obtaining residual block data indicating a difference between the current block and prediction block data for the current block; and identifying an optimal transform from available transforms for transforming the residual block data by evaluating two or more of the available transforms, wherein identifying the optimal transform includes identifying an optimal transform type and an optimal transform size, wherein evaluating a respective available transform includes: obtaining candidate transform block data by transforming the residual block data using the respective available transform; obtaining candidate quantized block data by quantizing the candidate transform block data; obtaining candidate dequantized transform block data by dequantizing the candidate quantized block data; and obtaining candidate decoded residual block data by inverse transforming the candidate dequantized transform block data, wherein inverse transforming the candidate dequantized transform block data includes: obtaining intermediate decoded block data by combining the prediction block data and the candidate decoded residual block data; and obtaining candidate decoded block data by filtering the intermediate decoded block data using an optimal transform size adaptive directional nonlinear filter; including the candidate quantized block data in an encoded bitstream; and outputting the encoded bitstream.

2. The method of claim 1, wherein evaluating the two or more of the available transforms includes:obtaining rate-distortion optimization costs for the available transforms on a per- available transform basis; and identifying the respective available transform as the optimal transform for coding the current block in response to a determination that the respective available transform corresponds to a minimal rate-distortion optimization cost among the rate-distortion optimization costs.

3. The method of claim 1, wherein identifying the optimal transform includes: identifying an optimal transform type; and identifying an optimal transform size.

4. The method of claim 1, wherein inverse transforming the candidate dequantized transform block data includes: obtaining the optimal transform size adaptive directional nonlinear filter.

5. The method of claim 1, further comprising: obtaining reconstructed block data by reconstruction filtering the candidate decoded block data; including the reconstructed block data in reconstructed frame data for the current frame; and storing the reconstructed frame data for subsequently encoding another frame from the input video.

6. The method of claim 1, further comprising: obtaining reconstructed block data by reconstruction filtering the intermediate decoded block data; including the reconstructed block data in reconstructed frame data for the current frame; and storing the reconstructed frame data for subsequently encoding another frame from the input video.

7. The method of claim 1, wherein including the candidate quantized block data in an encoded bitstream includes:including, in the encoded bitstream, data indicating that using a transform size adaptive directional nonlinear filter is enabled.

8. A method comprising: generating decoded block data by decoding a current block of a current frame, wherein decoding the current block includes: obtaining quantized transform coefficients for the current block from an encoded bitstream; obtaining transform data for the current block from the encoded bitstream, wherein the transform data indicates a transform type and a transform size; obtaining dequantized transform block data by dequantizing the quantized transform coefficients; and obtaining decoded residual block data by inverse transforming the dequantized transform block data in accordance with the transform data, wherein inverse transforming the dequantized transform block data includes: obtaining intermediate decoded block data by combining prediction block data for the current block and the decoded residual block data; and obtaining the decoded block data by filtering the intermediate decoded block data using a transform size adaptive directional nonlinear filter; and outputting the decoded block data.

9. The method of claim 8, wherein outputting the decoded block data includes: obtaining reconstructed block data by reconstruction filtering the decoded block data; including the reconstructed block data in reconstructed frame data for the current frame; and outputting the reconstructed frame data.

10. The method of claim 8, wherein obtaining the transform data includes: obtaining transform type data indicating the transform type; and obtaining transform size data indicating the transform size.

11. The method of claim 8, wherein inverse transforming the dequantized transform block data includes:obtaining the transform size adaptive directional nonlinear filter in accordance with the transform data.

12. The method of claim 8, wherein inverse transforming the dequantized transform block data includes accessing, from the encoded bitstream, data indicating that using the transform size adaptive directional nonlinear filter is enabled.

13. The method of claim 8, wherein: in response to accessing, from the encoded bitstream, data indicating that using the transform size adaptive directional nonlinear filter is disabled: inverse transforming the dequantized transform block data omits filtering the intermediate decoded block data using a transform size adaptive directional nonlinear filter; and outputting the decoded block data includes: obtaining reconstructed block data by reconstruction filtering the intermediate decoded block data; including the reconstructed block data in reconstructed frame data for the current frame; and outputting the reconstructed frame data.

14. An apparatus comprising: a non-transitory computer readable medium; and a processor configured to execute instructions stored on the non-transitory computer readable medium to: generate encoded block data, wherein, to generate the encoded block data, the processor is configured to execute the instructions to encode a current block from a current frame from an input video, wherein, to encode the current block, the processor is configured to execute the instructions to: obtain residual block data that indicates a difference between the current block and prediction block data for the current block; and identify an optimal transform from available transforms for transforming the residual block data, wherein to identify the optimal transform, the processor is configured to execute the instructions to evaluatetwo or more of the available transforms, wherein the optimal transform includes an optimal transform type and an optimal transform size, wherein, to evaluate a respective available transform, the processor is configured to execute the instructions to: obtain candidate transform block data, wherein, to obtain the candidate transform block data, the processor is configured to execute the instructions to use the respective available transform to transform the residual block data; obtain candidate quantized block data, wherein, to obtain the candidate quantized block data, the processor is configured to execute the instructions to quantize the candidate transform block data; obtain candidate dequantized transform block data, wherein, to obtain the candidate dequantized transform block data, the processor is configured to execute the instructions to dequantize the candidate quantized block data; and obtain candidate decoded residual block data, wherein, to obtain the candidate decoded residual block data, the processor is configured to execute the instructions to inverse transform the candidate dequantized transform block data, wherein to inverse transform the candidate dequantized transform block data, the processor is configured to execute the instructions to: obtain intermediate decoded block data, wherein, to obtain the intermediate decoded block data, the processor is configured to execute the instructions to combine the prediction block data and the candidate decoded residual block data; and obtain candidate decoded block data, wherein, to obtain the candidate decoded block data, the processor is configured to execute the instructions to use an optimal transform size adaptive directional nonlinear filter to filter the intermediate decoded block data; include the candidate quantized block data in an encoded bitstream; and output the encoded bitstream.

15. The apparatus of claim 14, wherein, to evaluate the two or more of the available transforms, the processor is configured to execute the instructions to: obtain rate-distortion optimization costs for the available transforms on a per- available transform basis; and identify the respective available transform as the optimal transform for coding the current block in response to a determination that the respective available transform corresponds to a minimal rate-distortion optimization cost among the rate-distortion optimization costs.

16. The apparatus of claim 14, wherein, to identify the optimal transform, the processor is configured to execute the instructions to: identify an optimal transform type; and identify an optimal transform size.

17. The apparatus of claim 14, wherein, to inverse transform the candidate dequantized transform block data, the processor is configured to execute the instructions to: obtain the optimal transform size adaptive directional nonlinear filter.

18. The apparatus of claim 14, wherein the processor is configured to execute the instructions to obtain reconstructed block data, wherein the processor is configured to execute the instructions to: reconstruction filter the candidate decoded block data to obtain the reconstructed block data; include the reconstructed block data in reconstructed frame data for the current frame; and store the reconstructed frame data for subsequently encoding another frame from the input video.

19. The apparatus of claim 14, wherein the processor is configured to execute the instructions to obtain reconstructed block data, wherein the processor is configured to execute the instructions to: reconstruction filter the intermediate decoded block data to obtain the reconstructed block data;include the reconstructed block data in reconstructed frame data for the current frame; and store the reconstructed frame data for subsequently encoding another frame from the input video.

20. The apparatus of claim 14, wherein the processor is configured to execute the instructions to: include, in the encoded bitstream, data indicating that using a transform size adaptive directional nonlinear filter is enabled.

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