Methods and systems for prediction from multiple cross-components

A video decoding method, comprising:

• decoding an index from a video bitstream;
• determining a set of parameters from a plurality of sets of parameters based on the index, wherein the set of parameters includes a scaling factor;
• and
• determining a predicted sample value of a first chroma component based on the set of the parameters, a reconstructed sample value of a luma component and a reconstructed sample value of a second chroma component, wherein determining the predicted sample value of the first chroma component further comprises:
• determining a first parameter of a combined linear model as a linear combination of a first parameter of a first linear model and a first parameter of a second linear model with the scaling factor;
• determining a second parameter of the combined linear model as a linear combination of a second parameter of the first linear model and a second parameter of the second linear model with the scaling factor;
• and
• determining the predicted sample value of the first chroma component based on the combined linear model;
• wherein the first parameter of the combined linear model is determined based on formula:
• A=(m×α2+p)/n+α1 and the second parameter of the combined linear model is determined based on formula:
• B=(m×β2+p)/n+β1, wherein A is the first parameter of the combined linear model, B is the second parameter of the combined linear model, α1, α2 are the first parameters of the first linear model and the second linear model, β1, β2 are the second parameters of the first linear model and the second linear model, m and 1/n are two scaling factors, and p is a rounding offset.

An apparatus for performing video data processing, the apparatus comprising:

• a memory figured to store instructions;
• and
• one or more processors configured to execute the instructions to cause the apparatus to perform:
• decoding an index from a video bitstream;
• determining a set of parameters from a plurality of sets of parameters based on the index, wherein the set of parameters includes a scaling factor;
• and
• determining a predicted sample value of a first chroma component based on the set of the parameters, a reconstructed sample value of a luma component and a reconstructed sample value of a second chroma component, wherein determining the predicted sample value of the first chroma component further comprises:
• determining a first parameter of a combined linear model as a linear combination of a first parameter of a first linear model and a first parameter of a second linear model with the scaling factor;
• determining a second parameter of the combined linear model as a linear combination of a second parameter of the first linear model and a second parameter of the second linear model with the scaling factor;
• and
• determining the predicted sample value of the first chroma component based on the combined linear model;
• wherein the first parameter of the combined linear model is determined based on formula:
• A=(m×α2+p)/n+α1 and the second parameter of the combined linear model is determined based on formula:
• B=(m×β2+p)/n+β1, wherein A is the first parameter of the combined linear model, B is the second parameter of the combined linear model, α1, α2 are the first parameters of the first linear model and the second linear model, β1, β2 are the second parameters of the first linear model and the second linear model, m and 1/n are two scaling factors, and p is a rounding offset.

A non-transitory computer readable medium storing a bitstream of a video for processing according to a method comprising:

• decoding an index from the bitstream;
• determining a set of parameters from a plurality of sets of parameters based on the index, wherein the set of parameters includes a scaling factor;
• and
• determining a predicted sample value of a first chroma component based on the set of the parameters, a reconstructed sample value of a luma component and a reconstructed sample value of a second chroma component, wherein determining the predicted sample value of the first chroma component further comprises:
• determining a first parameter of a combined linear model as a linear combination of a first parameter of a first linear model and a first parameter of a second linear model with the scaling factor;
• determining a second parameter of the combined linear model as a linear combination of a second parameter of the first linear model and a second parameter of the second linear model with the scaling factor;
• determining the predicted sample value of the first chroma component based on the combined linear model;
• wherein the first parameter of the combined linear model is determined based on formula:
• A=(m×α2+p)/n+α1 and the second parameter of the combined linear model is determined based on formula:
• B=(m×β2+p)/m+β1, wherein A is the first parameter of the combined linear model, B is the second parameter of the combined linear model, α1, α2 are the first parameters of the first linear model and the second linear model, β1, β2 are the second parameters of the first linear model and the second linear model, m and 1/n are two scaling factors, and p is a rounding offset.