Constrained Directional Enhancement Filter (CDEF) Appendix

1. Description of the algorithm

The constrained directional enhancement filter (CDEF) is applied after the deblocking filter and aims at improving the reconstructed picture by addressing ringing artifacts. CDEF is a combination of the directional de-ringing filter from the Daala codec (Mozilla) and the Constrained Low Pass Filter (CLPF) from the Thor codec (Cisco).

Filtering is applied on an 8x8 block level. 8x8 blocks have enough pixels that an edge can be accurately detected, which would not be possible for 4x4 blocks. However, 8x8 blocks don't have so many pixels that the detected edge will have more than one direction, which would be much more likely to occur for an edge present in a 16x16 block. Filtering is applied to both luma and chroma samples. For a given block, the algorithm consists of the two main steps outlined below:

Identify the direction d of the block (i.e. direction of edges). One of eight possible directions {0,…,7} can be utilized to identify the direction of the block.
Filtering
- Apply a nonlinear filter along the edge in the identified direction. Filter taps are aligned in the direction of the block. The main goal is to address ringing artifacts.
- Filter mildly along a 45 degree direction from the edge.

The two steps are outlined in more detail in the following section.

Step 1 – Identification of edge direction. Eight edge directions could be considered. The directions are indexed with d=0,…,7 as indicated in Figure 1 below.

Figure 1. Block directions.

For a given input block, the identification of edge direction is performed as follows:

Input pixels along each of the lines k=0,1,… are averaged. The original sample values along each on the lines k=0,1,… are replaced by the average value of the samples on the line. The resulting block is referred to as the averaged block.
The variance of the error between the source block and the averaged block is computed.
The operations above are repeated for each of the eight directions.
The direction with the lowest variance is selected as the filtering direction.

The example in Figure 2 below illustrates this step for an 8x8 input block. In this example, direction 0 has the smallest error variance and is selected as the block direction.

Figure 2. Example of block direction identification.

Step 2 – Filtering. The filtering operation consists of two main steps, namely a primary filtering operation and a secondary filtering operation. The primary filter acts along the identified block direction. The secondary filter acts at $45^o$ from the identified direction. In the example shown in Figure 3 below, the block direction is d=0, $45^o$. The sample to be filtered is highlighted in red. During primary filtering of the red sample the four green samples are considered. During secondary filtering of the red sample the eight blue samples located at a $45^o$ angle from the block direction are considered.

Figure 3. Example of primary and secondary filtering directions.

The nonlinear low-pass filters used in the filtering process are given by [1]:

$P_{filtered}(i,j)=p(i,j)+\sum_{m,n}w_{m,n}f(p(m,n)-p(i,j),S,D)$

Where $p(i,j)$ is the sample to be filtered, $P_{filtered}(i,j)$ is the filtered value of sample $p(i,j)$, $w$ are the filter weights, $f$ is a nonlinear constraint function, $S$ is the filter strength and $D$ is the filter damping.

When $|p(m,n)-p(i,j)|$ is small, $f(p(m,n)-p(i,j),S,D)=p(m,n)-p(i,j)$, implying that the filter behaves as an FIR filter. When $|p(m,n)-p(i,j)|$ is large, $f(p(m,n)-p(i,j),S,D)=0$ and no filtering is applied to the sample. The function $f$ de-emphasizes neighboring pixels $p(m,n)$ with large contrast (i.e. large magnitude of $p(m,n)-p(i,j)$. The strength $S$ and damping $D$ parameters control the attenuation of the large magnitude differences.

Filtering along the identified block direction is referred to as primary filtering, and makes use of primary filtering strength and primary damping values. The filter weights for primary filtering are shown in Figure 4 below. The sample to be filtered is shown in blue. For even strengths, a = 2 and b = 4, whereas for odd strengths a = 3 and b = 3.

Figure 4. Filter weights for primary filtering.

Filtering of samples that are at 45 degrees from the identified edge direction for the block is referred to as secondary filtering. Secondary filtering makes use of secondary strength and secondary damping values. The filter weights for secondary filtering are indicated in Figure 5 below as a function of the block direction. The sample to be filtered is shown in blue.

Figure 5. Filter weights for secondary filtering.

2. Implementation

Inputs to cdef_kernel: Output frame from the deblocking filter.

Outputs of cdef_kernel: CDEF filtered frame, filter parameters.

Controlling flags:

Control flags associated with CDEF are listed in Table 1 below.

Table 1. Control flags for CDEF.

Flag	Level	Description
--enable-cdef	Configuration	CDEF filter control (0:OFF, 1: ON (Default))
cdef_level	Sequence	Indicates whether to use CDEF for the whole sequence.
cdef_level	Picture	Indicates the level of complexity of the CDEF strength search as a function of the encoder mode (enc_mode).

Implementation details

The main steps involved in the implementation of the algorithm are outlined below, followed by more details on some of the important functions.

Step 1: Split the frame to be filtered into segments to allow for parallel filtering operations on different parts of the frame. The segments are set according to the following rules (see load_default_buffer_configuration_settings in EbEncHandle.c):

The number of segment rows is set to 1 if using a single core or (luma height/64)<6, else it is set to 6.
The number of segment columns is set to 1 if using a single core or (luma width/64)<10, else it is set to 6.

The segments are processed in cdef_kernel. Each segment is split into 64x64 filter blocks.

Step 2: CDEF search is performed for each segment using a separate thread. Each segment goes through a filter search operation through the function (cdef_seg_search). For a given 64x64 filter block in a segment, the main purpose of the search is to identify the directions of the 8x8 blocks in the filter block, and the best filter (Primary strength, Secondary strength) pair to use in filtering the filter block. The primary filter strength can take any value between 0 and 15 inclusive, whereas the secondary filter strength can take one of the following values: 0, 1, 2 or 4. The (primary strength, secondary strength) pairs are then indexed and ordered as indicated in Table 2 below:

Table 2. (primary strength, secondary strength) pairs.

Filter Strength Index	(Primary Strength, Secondary Strength) Pair
0	(0,0)
1	(0,1)
2	(0,2)
3	(0,4)
4	(1,0)
5	(1,1)
…	(...,…)
63	(15,4)

Searching for the best filter (Primary strength, Secondary strength) pair is equivalent to searching for the best filter strength index.

The primary luma damping (pri_damping) and secondary luma damping (sec_damping) values are set as a function of the base qindex for the picture and are given by:

pri_damping = 3 + (base_qindex/64);
sec_damping = 3 + (pcs->ppcs->base_qindex/64);

Chroma damping values are always one less than the luma damping values.

The CDEF search (cdef_seg_search) proceeds along the following steps.

Loop over all 64x64 filter blocks in the segment.
Loop over the picture planes
Loop over the specified filter strengths (see “Reducing Number of Filter Strengths Tested” in the Optimization section for more info on how to set which strengths to test.)
- Perform the following for each 8x8 non-skip block (cdef_filter_fb):
  - Find the direction for each 8x8 block (cdef_find_dir).
  - Filter the 8x8 block according to the identified direction using the set filter strength (cdef_filter_block). More details on the C-only version of this function, cdef_filter_block_c, are provided below.
- Compute the filtering mse for the filter block corresponding to the filter strength being considered (compute_cdef_dist).

Step 3: Select a subset of filter strengths to use in the final filtering of the 64x64 filter blocks using the results from step 2. The entire frame will be filtered using the subset of filter strenghts chosen, therefore before the subset can be chosen all segements must be completed in order to collect the filter strength data from all 64x64 filter blocks. This step is frame-based and is performed using only one thread (finish_cdef_search). More details on finish_cdef_search are provided below.

Step 4: Complete the filtering of the frame using the subset of filtering strengths chosen in Step 3. (av1_cdef_frame). More details on av1_cdef_frame are provided below

More details about cdef_filter_block_c

For a given 8x8 block, filtering is applied to all samples in the 8x8 block. Filtering is to be applied according to the identified direction for the 8x8 block. For a given sample to be filtered in the block, the position of the neighboring samples to be considered in the filtering operation are given by the array cdef_directions according to the identified direction.

The primary and secondary filter coefficients are given in Section 1.

More details on finish_cdef_search in step 3

For each 64x64 filter block, the output from Step 2 is an array of distortion values corresponding to different filter strength pairs (Primary strength, Secondary strength). To reduce the overhead associated with the signaling of the individual filter strength index for each 64x64 filter block, only a subset of the identified filter strength pairs is selected. Final filtering of the 64x64 filter blocks in the frame is then redone using the best among the selected subset of filter strengths. The encoder needs to signal to the decoder only the selected subset of filter strengths for the decoder to use in the filtering operation. The encoder could signal a set that consists of only 1, 2, 4, or 8 different (Primary strength, Secondary strength) pairs to be used for the frame. The specific pair to use for each 64x64 filter block is signaled separately. The search performed in finish_cdef_search is to find the best RDO option (i.e. 1, 2, 4, or 8 filter strength pairs for the frame) to work with.

Loop over the cardinality of the set of the strength pair options (1 then 2 then 4 then 8)

Call the function joint_strength_search_dual to determine the best such set for each of the options based on filtering distortion (joint_strength_search_dual function makes use of a greedy search algorithm). Compute the RDO cost of each of the options and keep track of the best option (i.e. the best number of bits and the corresponding set of best (Primary strength, Secondary strength) pairs. The latter are stored in the cdef_strengths and cdef_uv_strengths arrays.
Loop over the filter blocks in the frame and select for each filter block the best (Primary strength, Secondary strength) pair. The selected pair is signaled in mbmi.cdef_strength whereas damping values are stored in cdef_pri_damping and cdef_sec_damping.
The most used filter strength pair in the filter blocks for the frame is then identified as the frame strength and its corresponding index is stored in pPcs->cdef_frame_strength.

More details on av1_cdef_frame

Loop over the 64x64 filter blocks
   Loop over the three picture planes
    Call cdef_filter_fb to filter the samples in the filter block using the selected filter strength pairs

(selected in finish_cdef_search).

3. Optimization of the algorithm

The search for the best filter strength pair for each 64x64 block can be algorithmically optimized using the features described below. The aggressiveness of the CDEF algorithm depends on the CDEF filter mode (pcs->cdef_level), which is specified based on the encoder preset (pcs->enc_mode).

Reducing Number of Filter Strengths Tested

The search in cdef_seg_search for the filter strength is performed by considering a subset of the allowable filter strength indices [0,63]. For each cdef_level, a set of primary and secondary filter strengths are specified to be tested. The search is performed in two stages:

1st stage: Test the specified primary filter strengths. The number of primary filter strengths to test is specified by cdef_ctrls->first_pass_fs_num, and the values of the primary strengths are set in the array cdef_ctrls->default_first_pass_fs.

2nd stage: Test the specified secondary filter strengths. The number of secondary filter strengths to test is specified by cdef_ctrls->default_second_pass_fs_num, and the values of the primary strengths are set in the array cdef_ctrls->default_second_pass_fs.

Reducing Number of Rows Used in CDEF search

The CDEF search can be performed on subsampled blocks to reduce the number of required computations. A subsampling factor is specified using cdef_ctrls->subsampling_factor, according to the allowable values in Table 3.

Table 3. Allowable subsampling factors in CDEF search.

Subsampling_Factor	Action
1	No subsampling
2	Subsample each block by 2 (i.e. perform CDEF filtering on every 2nd row)
3	Subsample each block by 4 (i.e. perform CDEF filtering on every 4th row)

Using Reference Frame Info to Reduce CDEF Search

Information from the nearest reference frames can be used to reduce the number of filter strengths tested for each frame. The selected CDEF filter strengths for each frame are saved in the EbReferenceObject to be used by subsequent frames.

When cdef_ctrls->search_best_ref_fs is enabled, only the best filter strengths from the reference frames are tested, as follows:

If (list0_best_filter == list1_best_filter)
    Skip CDEF search; use the filter selected by the reference frames
Else if (list0_best_filter == OFF && list1_best_filter == OFF)
    Skip CDEF search; assume CDEF is off for this frame
Else {
    add list0_best_filter to be tested
    if (list1_best_filter != list0_best_filter)
        add list1_best_filter to be tested
    if (list0_best_filter_uv == OFF && list1_best_filter_uv == OFF)
        Disallow CDEF search for the chroma planes only
}

When cdef_ctrls->use_reference_cdef_fs is enabled, CDEF search is skipped and the filter strengths are set to the average of the lowest and highest filter strengths of the reference frames, as follows:

Lowest_fs = MIN(lowest_selected_fs_from_list0, lowest_selected_fs_from_list1)
Highest_fs = MAX(highest_selected_fs_from_list0, highest_selected_fs_from_list1)
Luma_cdef_fs = MIN( 63, (lowest_fs + highest_fs) / 2)
Chroma_cdef_fs = 0

When cdef_ctrls->use_skip_detector is enabled, CDEF will be disabled if the skip area percentage of the nearest reference frames (i.e. the percentage of zero coefficients in the nearest ref frames) is above 75%.

Cost Biasing to Reduce CDEF Application

After the CDEF search, the best selected filters must be applied to each filter block; however, if the best selected filter for a filter block is (0,0), then no filtering is required. By enabling cdef_ctrls->zero_fs_cost_bias, the cost of the (0,0) filter can be scaled down to make it more favourable, resulting in fewer filter blocks requiring filtering in av1_cdef_frame.

When cdef_ctrls->zero_fs_cost_bias is non-zero, the cost of the (0,0) filter for each filter block will be scaled by cdef_ctrls->zero_fs_cost_bias /64.

4. Signaling

At the frame level, the algorithm signals the luma damping value and up to 8 different filter strength pairs to choose from. Each pair includes luma primary strength, chroma primary strength, luma secondary strength, chroma secondary strength and the number of bits used to signal the 64x64 level pairs. Table 4 summarizes the parameters signaled at the frame level.

At the 64x64 filter block level, the algorithm signals the index for the specific filter strength pair to work with for the 64x64 filter block from among the set of filter strength pairs specified at the frame level. Table 5 summarizes the parameters signaled at the filter block level.

Table 4. CDEF parameters signaled at the frame level.

Frame level Parameters	Values (for 8-bit content)
Luma Damping D	{3, 4, 5, 6}
Number of bits used for filter block signaling	{0,..,3}
List of 1, 2, 4 or 8 filter strength pairs. Each pair contains the following:
Luma primary strength	{0,…,15}
Chroma primary strength	{0,…,15}
Luma secondary strength	{0,1,2,3}
Chroma secondary strength	{0,1,2,3}

Table 5. CDEF parameters signaled at the filter block level.

Filter-Block-level Parameters	Values
Index for the filter strength pair to use	Up to 7

Notes

The feature settings that are described in this document were compiled at v2.2.0 of the code and may not reflect the current status of the code. The description in this document represents an example showing how features would interact with the SVT architecture. For the most up-to-date settings, it's recommended to review the section of the code implementing this feature.

References

[1] Steiner Midtskogen and Jean-Marc Valin, The AV1 Constrained Directional Enhancement Filter (CDEF), 2017.

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Appendix-CDEF.md

Appendix-CDEF.md

Constrained Directional Enhancement Filter (CDEF) Appendix

1. Description of the algorithm

Figure 1. Block directions.

Figure 2. Example of block direction identification.

Figure 3. Example of primary and secondary filtering directions.

Figure 4. Filter weights for primary filtering.

Figure 5. Filter weights for secondary filtering.

2. Implementation

Table 1. Control flags for CDEF.

Table 2. (primary strength, secondary strength) pairs.

3. Optimization of the algorithm

Reducing Number of Filter Strengths Tested

Reducing Number of Rows Used in CDEF search

Table 3. Allowable subsampling factors in CDEF search.

Using Reference Frame Info to Reduce CDEF Search

Cost Biasing to Reduce CDEF Application

4. Signaling

Table 4. CDEF parameters signaled at the frame level.

Table 5. CDEF parameters signaled at the filter block level.

Notes

References

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Constrained Directional Enhancement Filter (CDEF) Appendix

1. Description of the algorithm

Figure 1. Block directions.

Figure 2. Example of block direction identification.

Figure 3. Example of primary and secondary filtering directions.

Figure 4. Filter weights for primary filtering.

Figure 5. Filter weights for secondary filtering.

2. Implementation

Table 1. Control flags for CDEF.

Table 2. (primary strength, secondary strength) pairs.

3. Optimization of the algorithm

Reducing Number of Filter Strengths Tested

Reducing Number of Rows Used in CDEF search

Table 3. Allowable subsampling factors in CDEF search.

Using Reference Frame Info to Reduce CDEF Search

Cost Biasing to Reduce CDEF Application

4. Signaling

Table 4. CDEF parameters signaled at the frame level.

Table 5. CDEF parameters signaled at the filter block level.

Notes

References