The general idea behind the chroma from luma (CfL) prediction feature is to exploit the correlation between luma and chroma to express the Intra prediction of chroma sample values as an affine function of the corresponding reconstructed luma sample values, where the reconstructed luma samples are sub-sampled to match the chroma sub-sampling. The chroma prediction is given by
where and
are predicted chroma
and reconstructed luma samples, respectively. The parameters
and
can be
determined (at least theoretically) using least squares regression. The feature provides gains in screen sharing
applications.
In practice, the CfL prediction is performed as illustrated in Figure 1 below.
The steps illustrated in the diagram above can be summarized as follows:
-
Consider the reconstructed luma sample values.
-
Reconstructed luma samples are sub-sampled to match the chroma sub-sampling.
-
Calculate the
(i.e. average) of the
reconstructed luma sample values. -
Subtract the
from the reconstructed luma
sample values to generate the AC reconstructed luma sample values,
, which has a zero average. -
Compute
and 
using the
AC reconstructed luma sample values. -
Compute the intra DC mode chroma prediction,
. The final chroma from
luma prediction is then given by:
Inputs: Intra chroma code, luma inverse quantized residuals
Outputs: Best and chroma residuals
Control macros/flags:
| Flag | Level | Description |
|---|---|---|
| -dcfl | Configuration | 0: OFF (do not disable), 1: ON (disable), -1: DEFAULT |
| -chroma_mode | Configuration | Level: [0-3], -1: DEFAULT |
| chroma_level | Picture | Describes the Chroma level of the encoder. Indicates which Chroma modes are allowed. |
Details of the implementation
Figure 2. The main function calls leading to CfL prediction. The functions highlighted in blue are where CfL prediction takes place.
Figure 3. Continuation of Figure 2 showing the details of CfL processing in the function CfLPrediction.
CfL prediction takes place in MD through the function CflPrediction and in the encode pass through the function Av1EncodeLoop/Av1EncodeLoop16bit. The details of the CfL prediction in the function CflPrediction are presented in Figure 3. Similar flow is also followed in the function Av1EncodeLoop/Av1EncodeLoop16bit. In the following, the details of the CfL processing in the function CflPrediction are presented.
For an intra coded block, the function CflPrediction is called when the intra_chroma_mode is set to UV_CFL_PRED. There are four steps in the function:
Step 1: Reconstruct the Luma samples (AV1PerformInverseTransformReconLuma)
The first step is to reconstruct the luma samples, since the latter would be used to generate the chroma prediction. At this stage in the encoder pipeline, the luma residuals are transformed, quantized and inverse quantized. In this step, the inverse transform is applied, and the reconstructed luma residuals are added to the prediction to build the reconstructed samples.
Step 2: Compute the AC component of the luma intra prediction
In this step, the luma reconstructed samples are down sampled to match
the size of chroma samples using the cfl_luma_subsampling_420
function. Then the AC luma values are calculated by subtracting the DC luma
value using the svt_subtract_average function. The resulting AC values are stored
in the pred_buf_q3 buffer.
Step 3: Find the best
The best values for the chroma components are calculated by
minimizing the overall full cost. The algorithm performs a search over the 16 possible
values of
and finds the best value that minimizes the joint prediction cost.
The search is performed in the context of a joint sign between the two chroma components.
After the best value for
is calculated, the joint cost is compared with the cost of DC prediction and the winner is selected.
Step 4: Generate the chroma prediction
After the best is selected, the prediction using the
CfL mode is performed using the
svt_cfl_predict function. The chroma
residuals are then calculated using the function residual_kernel.
Finding the best requires searching different
values in the set of allowed
values and calculating the cost
associated with each value. Performing this
search
process in MD for every luma mode and block size
at MD would be very complex. In order to find the best quality-speed
trade off, there is an option to perform the selection of the best
at the encode pass and only on the final chosen intra coding mode.
This option is signaled using the
evaluate_cfl_ep flag. The flag depends on the chroma
level, which in turn depends on the chroma mode. The description of the chroma mode settings is given in Table 2.
| chroma_Mode | evaluate_cfl_ep |
|---|---|
| CHROMA_MODE_0 (0) | Full chroma search @ MD, including CfL |
| CHROMA_MODE_1 (1) | Fast chroma search @ MD, including CfL |
| CHROMA_MODE_2 (2) | Chroma blind @ MD + CfL @ Encode Pass |
| CHROMA_MODE_3 (3) | Chroma blind @ MD + no CfL @ Encode Pass |
The chroma_level settings as a function of the encoder settings are given in Table 3.
The settings of evaluate_cfl_ep as a function of chroma _level are as indicated in Table 4.
| chroma_level | evaluate_cfl_ep |
|---|---|
| 0 | α selection at MD |
| 1 | α selection at MD |
| 2 | α selection at encode pass |
| 3 | no CFL mode |
As the chroma_level increases, so does the complexity of the feature
and the quality of the chroma prediction.
CfL is a chroma mode that is only allowed for blocks with height and width of 32 or smaller. The entropy encoder signals the chroma mode per block and if the mode is CfL, extra parameters are included in the bit stream:
-
cfl_alpha_signscontains the sign of the alpha values for U and V packed together into a single syntax element with 8 possible values. (The combination of two zero signs is prohibited as it is redundant with DC Intra prediction.) -
cfl_alpha_ucontains the absolute value of alpha minus one for the U component. -
cfl_alpha_vcontains the absolute value of alpha minus one for the U component.
[1] Luc N. Trudeau, Nathan E. Egge and David Barr, “Predicting Chroma from Luma in AV1”, Data Compression Conference, 2017.