Abstract: In one example, a device for coding video data includes a video coder configured to code a value for a syntax element representative of whether any two reference layer samples, collocated with two respective enhancement layer picture samples within a common enhancement layer tile, must be within a common reference layer tile, and code the enhancement layer picture samples based at least in part on the value of the syntax element.

Abstract: An apparatus configured to code (e.g., encode or decode) video information includes a memory unit and a processor in communication with the memory unit. The memory unit is configured to store video information associated with a base layer and an enhancement layer, the enhancement layer comprising an enhancement layer (EL) block and the base layer comprising a base layer (BL) block that is co-located with the enhancement layer block. The processor is configured to determine predicted pixel information of the EL block by applying a prediction function to pixel information of the BL block, and to determine the EL block using the predicted pixel information. The processor may encode or decode the video information.

Abstract: This disclosure presents techniques for sample adaptive offset (SAO) filtering that focus on filtering the changed region of a picture or layer (e.g., the high frequency component of video blocks of a picture or layer). In general, the techniques of this disclosure may be referred to as High-Frequency-Pass SAO (HSAO) filtering. In one example, a method for coding video data comprises obtaining a decoded block of video data, separating the decoded block of video data into a low-frequency component and a high-frequency component, applying an SAO filter to the high-frequency component to generate a SAO filtered high-frequency component, and combining the SAO filtered high-frequency component and the low-frequency component to generate a filtered decoded block of video data.

Abstract: An apparatus configured to code (e.g., encode or decode) video information includes a memory unit and a processor in communication with the memory unit. The memory unit is configured to store video information associated with a base layer and an enhancement layer. The processor is configured to up-sample a base layer reference block by using an up-sampling filter when the base and enhancement layers have different resolutions; perform motion compensation interpolation by filtering the up-sampled base layer reference block; determine base layer residual information based on the filtered up-sampled base layer reference block; determine weighted base layer residual information by applying a weighting factor to the base layer residual information; and determine an enhancement layer block based on the weighted base layer residual information. The processor may encode or decode the video information.

Abstract: In general, techniques are described for performing multiple passes of sample adaptive offset (SAO) filtering when coding video data. A video decoding device comprising one or more processors may perform the techniques. The processors may determine a first SAO pixel classification for a block of video data and determine a first offset value based on the first SAO pixel classification and one or more pixel values of the block. The one or more processors may also determine a second SAO pixel classification for the block and determine a second offset value based on the second SAO pixel classification and the one or more pixel values of block of video data. The processors may then apply the first offset value and the second offset value to the block of video data to generate a block of SAO filtered video data.

Abstract: Described is a technology by which a roadside-to-vehicle communication system may be implemented, including via a stateful scheduling with network coding scheme that enhances network capacity. Moving vehicles request and receive data from a roadside access points. Each of the access points operate a stateful scheduling algorithm that serves multiple vehicles by integrating network coding within a timeslot. In one aspect, the state of each vehicle's previously received and retained data is obtained, and used to enhance network capacity by combining as many packets as possible for multiple recipients in network coding.

Abstract: Methods and systems for video image coding are provided. Sets of filters may be selected and applied to video information at least partially based on phase displacement information between a first and second layer of video information. For example, the phase displacement information may correspond to a difference between a position of a pixel in the first layer and a corresponding position of the pixel in the second layer. The selected filter set can be an up-sampling filter or a down-sampling filter. The phase displacement information may be encoded as a syntax element embedded in the video bit stream.

Abstract: Computation scheduling and allocation for visual communication is described. In one aspect, multiple frames of video data are encoded by allocating for at least a subset of inter-coded frames, on frame-by-frame basis, computational resources to encode the inter-coded frame. To this end, a computational budget to encode a current inter-coded frame is estimated. The estimate is based on the actual computational costs to encode a previous inter-coded frame of video data. Next, sets of operations associated with encoding the current inter-coded frame are analyzed to determine computational resources to implement the operations. If the computational resources exceed the computational budget, complexity of the operations is reduced until the associated computational resources are less than or equal to the computational budget. At this point, the current inter-coded frame is encoded using the operations and the computational budget. This process is repeated for the remaining inter-coded frames of video data.

Abstract: A network can include a number of nodes that link a source node to a sink node. When a first node in a network sends a packet to its downstream node, this information is also received at its upstream node. In response to learning that the first node has sent a packet, the upstream node sends another packet to the first node. In essence, a pull-based transmission approach is used to mitigate congestion and address the funneling effect in data transmission networks such as wireless video sensor networks.

Abstract: Described herein is technology for, among other things, natural network coding in a wireless mesh network. The technology involves wireless mesh network systems, methods and devices based on the natural network coding. By encoding signals in their natural forms using their channel strengths, more efficient transmission of signals is possible in the wireless mesh network.

Abstract: A network can include a number of nodes that link a source node to a sink node. When a first node in a network sends a packet to its downstream node, this information is also received at its upstream node. In response to learning that the first node has sent a packet, the upstream node sends another packet to the first node. In essence, a pull-based transmission approach is used to mitigate congestion and address the funneling effect in data transmission networks such as wireless video sensor networks.

Abstract: Described herein is technology for, among other things, natural network coding in a wireless mesh network. The technology involves wireless mesh network systems, methods and devices based on the natural network coding. By encoding signals in their natural forms using their channel strengths, more efficient transmission of signals is possible in the wireless mesh network.

Abstract: Described is a technology by which a roadside-to-vehicle communication system may be implemented, including via a stateful scheduling with network coding scheme that enhances network capacity. Moving vehicles request and receive data from a roadside access points. Each of the access points operate a stateful scheduling algorithm that serves multiple vehicles by integrating network coding within a timeslot. In one aspect, the state of each vehicle's previously received and retained data is obtained, and used to enhance network capacity by combining as many packets as possible for multiple recipients in network coding.

Abstract: Described is continuous network coding, in which a relay sends probability data comprising a continuous number for use as parity data. The node receives streams of bits sent from sources towards a destination, and computes the probability data based on current noise data and/or fading data. A selected set of the bits (all or some subset thereof) are combined, e.g., XOR-ed or concatenated, and send to the destination. Phase modulation is performed to convey probability information based on the probability data. The destination demodulates the signal to obtain the probability information, and combines the probability information with the data directly received from sources to perform joint decoding. The number of bits in the set of selected bits may be adaptively chosen based on current channel conditions, e.g., increased when the channel conditions from the sources directly to a destination are poor relative to the channel conditions via the relay.

Abstract: Computation scheduling and allocation for visual communication is described. In one aspect, multiple frames of video data are encoded by allocating for at least a subset of inter-coded frames, on frame-by-frame basis, computational resources to encode the inter-coded frame. To this end, a computational budget to encode a current inter-coded frame is estimated. The estimate is based on the actual computational costs to encode a previous inter-coded frame of video data. Next, sets of operations associated with encoding the current inter-coded frame are analyzed to determine computational resources to implement the operations. If the computational resources exceed the computational budget, complexity of the operations is reduced until the associated computational resources are less than or equal to the computational budget. At this point, the current inter-coded frame is encoded using the operations and the computational budget. This process is repeated for the remaining inter-coded frames of video data.