A method and apparatus for variable rate compression with a conditional autoencoder is herein provided. According to one embodiment, a method for compression includes receiving a first image and a first scheme as inputs for an autoencoder network; determining a first Lagrange multiplier based on the first scheme; and using the first image and the first Lagrange multiplier as inputs, computing a second image from the autoencoder network. The autoencoder network is trained using a plurality of Lagrange multipliers and a second image as training inputs.

A method and apparatus for variable rate compression with a conditional autoencoder is herein provided. According to one embodiment, a method for compression includes receiving a first image and a first scheme as inputs for an autoencoder network; determining a first Lagrange multiplier based on the first scheme; and using the first image and the first Lagrange multiplier as inputs, computing a second image from the autoencoder network. The autoencoder network is trained using a plurality of Lagrange multipliers and a second image as training inputs.

A method for colour component prediction, applied to an encoder and includes: determining a neighbouring reference sample set of a current block, wherein the neighbouring reference sample set comprises at least one reference sample; determining a preset parameter value corresponding to the current block, including: determining a bitdepth value corresponding to a to-be-predicted colour component of the current block; and performing a shift on 1 by the bitdepth value minus 1 to obtain the preset parameter value. The method further includes: determining an input sample matrix by means of a first preset calculation model based on the neighbouring reference sample set and the preset parameter value; and performing colour component prediction on the current block according to the input sample matrix to obtain a prediction block of the current block.

A method for colour component prediction, applied to an encoder and includes: determining a neighbouring reference sample set of a current block, wherein the neighbouring reference sample set comprises at least one reference sample; determining a preset parameter value corresponding to the current block, including: determining a bitdepth value corresponding to a to-be-predicted colour component of the current block; and performing a shift on 1 by the bitdepth value minus 1 to obtain the preset parameter value. The method further includes: determining an input sample matrix by means of a first preset calculation model based on the neighbouring reference sample set and the preset parameter value; and performing colour component prediction on the current block according to the input sample matrix to obtain a prediction block of the current block.

A method for video bitstream processing includes generating a prediction block for a first video block of a video related to a first component, where the prediction block is selectively generated according to a criterion by applying a two-step cross-component prediction mode (TSCPM), and performing a conversion between the first video block and a bitstream representation of the video using the prediction block, wherein a first field in the bitstream representation corresponds to the TSCPM.

A feature data encoding method, an encoder, a feature data decoding method, and a decoder are provided. The feature data encoding method includes following steps. A transform unit is divided into a plurality of sub-blocks and N sub-transform units. A reference origin and a LSC are determined in an i-th sub-transform unit of the sub-transform units, and an original coordinate of the last significant coefficient of the i-th sub-transform unit is modified to a specific coordinate. The i-th sub-transform unit is scanned from a specific sub-block of the i-th sub-transform unit, and significant feature coefficients in the i-th sub-transform unit are individually encoded as coded data.

A feature data encoding method, an encoder, a feature data decoding method, and a decoder are provided. The feature data encoding method includes following steps. A transform unit is divided into a plurality of sub-blocks and N sub-transform units. A reference origin and a LSC are determined in an i-th sub-transform unit of the sub-transform units, and an original coordinate of the last significant coefficient of the i-th sub-transform unit is modified to a specific coordinate. The i-th sub-transform unit is scanned from a specific sub-block of the i-th sub-transform unit, and significant feature coefficients in the i-th sub-transform unit are individually encoded as coded data.

This disclosure describes systems, methods, and devices related to complexity aware encoding. A device may generate a list of encodes based on pairs of resolution and quantization parameters (QP) pairs associated with one or more video segments received from a source. The device may generate an estimated bit rate associated with the one or more video segments based on an analysis of the one or more video segments. The device may determine distortion values associated with the one or more video segments. The device may apply a weighting mechanism to the distortion values using the estimated bit rate. The device may select a subset of encodes based on the weighting mechanism. The device may perform the subset of encodes on the one or more video segments for transmission.

The embodiments of the present disclosure provide a code rate control method and apparatus, an image acquisition device, and a readable storage medium. The method comprises: acquiring the gain and exposure time of an image to be encoded from an image processing module of an image acquisition device; obtaining corresponding reference distortion degree according to the gain and exposure time of said image; calculating the difference between the distortion degree in a characteristic region of said image and the reference distortion degree; calculating a distortion tolerance degree of macro blocks constituting said image according to the difference between the distortion degree in the characteristic region of said image and the reference distortion degree; performing macro block predictions on the respective macro blocks in said image, to obtain an optimum macro block prediction mode; and encoding said image, which corresponds to the optimum macro block prediction mode, in order to control the code rate of said image. By means of the cooperation of image processing and encoding, said method can achieve code rate control while guaranteeing that the encoded image has a good subjective presentation.

The embodiments of the present disclosure provide a code rate control method and apparatus, an image acquisition device, and a readable storage medium. The method comprises: acquiring the gain and exposure time of an image to be encoded from an image processing module of an image acquisition device; obtaining corresponding reference distortion degree according to the gain and exposure time of said image; calculating the difference between the distortion degree in a characteristic region of said image and the reference distortion degree; calculating a distortion tolerance degree of macro blocks constituting said image according to the difference between the distortion degree in the characteristic region of said image and the reference distortion degree; performing macro block predictions on the respective macro blocks in said image, to obtain an optimum macro block prediction mode; and encoding said image, which corresponds to the optimum macro block prediction mode, in order to control the code rate of said image. By means of the cooperation of image processing and encoding, said method can achieve code rate control while guaranteeing that the encoded image has a good subjective presentation.