A method for video encoding is provided. The method comprises retrieving a first video frame comprising a plurality of pixel blocks; determining a rate distortion optimization (RDO) cost for a first prediction mode for a pixel block; determining a variance-bits ratio (VBR) of the pixel block; upon determining the VBR is greater than a predefined threshold, scaling the RDO cost for the first prediction mode based on a predefined scale factor; and selecting one of the first prediction mode and a second prediction mode for video encoding of the first video frame based on comparing the scaled RDO cost for the first prediction mode and a second RDO cost for the second prediction mode for the pixel block.

Methods and systems are provided for increasing bandwidth efficiency in satellite communications. In some embodiments, a satellite communications method is provided that comprises receiving, at a satellite and from a plurality of user ground terminals, a plurality of source signals, wherein each of the source signals are modulated according to at least one source modulation method, and further receiving, at a satellite and from a plurality of user ground terminals, a plurality of information signals corresponding to the plurality of source signals. The method further includes combining, at the satellite, the plurality of source signals into a combined source signal with an overlapping bandwidth, wherein each of the source signals are further modulated according to at least one predetermined modulation method before they are combined, and transmitting, by a downlink transmission from the satellite to a gateway ground station, the combined source signal.

Methods and systems are provided for increasing bandwidth efficiency in satellite communications. In some embodiments, a satellite communications method is provided that comprises receiving, at a satellite and from a plurality of user ground terminals, a plurality of source signals, wherein each of the source signals are modulated according to at least one source modulation method, and further receiving, at a satellite and from a plurality of user ground terminals, a plurality of information signals corresponding to the plurality of source signals. The method further includes combining, at the satellite, the plurality of source signals into a combined source signal with an overlapping bandwidth, wherein each of the source signals are further modulated according to at least one predetermined modulation method before they are combined, and transmitting, by a downlink transmission from the satellite to a gateway ground station, the combined source signal.

An image prediction method and a related product, where the image prediction method includes performing intra-frame prediction on a current block using a reference block to obtain an initial predicted pixel value of a pixel in the current block, and performing weighted filtering on the initial predicted pixel value of the pixel in the current block to obtain a predicted pixel value of the pixel in the current block. Weighting coefficients used for the weighted filtering include a horizontal weighting coefficient and a vertical weighting coefficient, and a first attenuation rate factor acting on the horizontal weighting coefficient is different from a second attenuation rate factor acting on the vertical weighting coefficient.

A digital signal process unit includes a first cancel signal generation unit and a second cancel signal generation unit. The first cancel signal generation unit generates, as a first cancel signal component, a cancel signal component corresponding to an image signal included in an analog signal output from a mixer. The second cancel signal generation unit generates, as a second cancel signal component, a cancel signal component corresponding to a leakage signal generated between an input and output of the mixer. The digital signal process unit includes subtractors for subtracting the first cancel signal component and the second cancel signal component from a signal component corresponding to a frequency band divided from an input signal to obtain a digital signal.

An image decoding method according to the present disclosure comprises deriving a first candidate intra prediction mode based on a first neighboring block of a current block; deriving a second candidate intra prediction mode based on a second neighboring block of the current block; constructing MPM (Most Probable Mode) list of the current block based on the first candidate intra prediction mode and the second candidate intra prediction mode; deriving an intra prediction mode for the current block based on the MPM list; and generating a prediction sample for the current block based on the intra prediction mode, wherein the first neighboring block is a left neighboring block located at the lowermost side among neighboring blocks adjacent to a left boundary of the current block, and wherein the second neighboring block is an upper neighboring block located at the rightmost side among neighboring blocks adjacent to an upper boundary of the current block.

A video coder receives data from a bitstream for a block of pixels to be encoded or decoded as a current block of a current picture of a video. Upon determining that an applied block setting of the current block satisfies a threshold condition, the video coder generates a first prediction based on a first motion information for a first prediction unit of the current block. The video coder generates a second prediction based on a second motion information for a second prediction unit of the current block. The video coder generates a third prediction based on the first and second motion information for an overlap prediction region that is defined based on a partitioning between the first prediction unit and the second prediction unit. The video coder encodes or decodes the current block by using the first, second, and third predictions.

Examples of biomimetic codecs and biomimetic coding techniques are described herein. Morphologically-adaptive coding networks can be developed in accordance with energy dissipation driven “heat” generated by application of training data. The morphologically-adaptive coding networks may be representative of common features expected in an input signal or data stream. Decoding may proceed using the morphologically-adaptive coding network. Morphologically-adaptive coding networks may be used as a cortex that can be shared for boosting multimedia data compression rates and/or increasing the encode-decode fidelity of information content while the features remain queryable in encoded form. Examples of the biomimetic codecs and biomimetic coding techniques provide a broad-based technology platform that can be used in context-IDed multimedia storage, pattern recognition, and high-performance computing/big data management, the hallmarks of web- and cloud-based systems.

Examples of biomimetic codecs and biomimetic coding techniques are described herein. Morphologically-adaptive coding networks can be developed in accordance with energy dissipation driven “heat” generated by application of training data. The morphologically-adaptive coding networks may be representative of common features expected in an input signal or data stream. Decoding may proceed using the morphologically-adaptive coding network. Morphologically-adaptive coding networks may be used as a cortex that can be shared for boosting multimedia data compression rates and/or increasing the encode-decode fidelity of information content while the features remain queryable in encoded form. Examples of the biomimetic codecs and biomimetic coding techniques provide a broad-based technology platform that can be used in context-IDed multimedia storage, pattern recognition, and high-performance computing/big data management, the hallmarks of web- and cloud-based systems.

A system includes code including obtaining code to obtain a first syntax element that indicates a first quantization index value; at least one second syntax element that indicates an offset value, a second quantization index value for another coefficient by combining the first quantization index value and the offset value to obtain a combined value, and modifying the combined value to be a predetermined minimum value as the second quantization index value, fourth obtaining code to obtain a quantization step size that corresponds to the second quantization index value; and determining code to determine a mode in which the coded image is to be decoded based on determining whether the first quantization index value is equal to a quantization index value associated with lossless coding, and based on determining whether the offset value is less than or equal to the quantization index value associated with the lossless coding.