CAMBI (Contrast Aware Multiscale Banding Index) is Netflix's detector for banding (aka contouring) artifacts.
For an introduction to CAMBI, please refer to the tech blog. For a detailed technical description, please refer to the technical paper published at PCS 2021. Note that the paper describes an initial version of CAMBI that no longer matches the code exactly, but it is still a good introduction.
By default, the current version of CAMBI is a no-reference metric, and operates on a frame-by-frame basis (no temporal information is leveraged). To integrate it as part of the VMAF framework, which employs a full-reference metric API, CAMBI takes both a reference and a distorted video as its input. For simplicity, one can point the input arguments --reference
and --distorted
to the same video path.
CAMBI also offers a full-reference mode which computes its score as MAX(0, distorted_score - reference_score)
. This mode can be activated with the --full_ref
command line option. In this case, both the --reference
and --distorted
inputs will be used.
The CAMBI score starts at 0, meaning no banding is detected. A higher CAMBI score means more visible banding artifacts are identified. The maximum CAMBI observed in a sequence is 24 (unwatchable). As a rule of thumb, a CAMBI score around 5 is where banding starts to become slightly annoying (also note that banding is highly dependent on the viewing environment - the brigher the display, and the dimmer the ambient light, the more visible banding is).
To invoke CAMBI using the VMAF command line, follow the instruction and use cambi
as the feature name. For example, after downloading the input video src01_hrc01_576x324.yuv
, invoke CAMBI via:
libvmaf/build/tools/vmaf \
--reference src01_hrc01_576x324.yuv \
--distorted src01_hrc01_576x324.yuv \
--width 576 --height 324 --pixel_format 420 --bitdepth 8 \
--no_prediction --feature cambi --output /dev/stdout
This will yield the output:
<VMAF version="4b42f672">
<params qualityWidth="576" qualityHeight="324" />
<fyi fps="52.47" />
<frames>
<frame frameNum="0" cambi="0.848047" />
<frame frameNum="1" cambi="0.723467" />
...
<frame frameNum="46" cambi="0.994815" />
<frame frameNum="47" cambi="1.019691" />
</frames>
<pooled_metrics>
<metric name="cambi" min="0.509878" max="1.019691" mean="0.689250" harmonic_mean="0.681308" />
</pooled_metrics>
<aggregate_metrics />
</VMAF>
CAMBI supports the same input bit depths as VMAF: 8, 10, 12 and 16. However, the computations in CAMBI will always be performed at the 10-bit level, and the other formats will be converted to 10-bit as a preprocessing step.
The CAMBI feature extractor also supports additional optional parameters as listed below:
window_size
(min: 15, max: 127, default: 63): Window size to compute CAMBI (default: 63 corresponds to ~1 degree at 4K resolution and 1.5H)topk
(min: 0, max: 1.0, default: 0.6): Ratio of pixels for the spatial pooling computationtvi_threshold
(min: 0.0001, max: 1.0, default: 0.019): Visibilty threshold for luminance ΔL < tvi_threshold*L_mean for BT.1886max_log_contrast
(min: 0, max: 5, default: 2): Maximum contrast in log luma level (2^max_log_contrast) at 10-bits. Default 2 is equivalent to 4 luma levels at 10-bit and 1 luma level at 8-bit. The default is recommended for banding artifacts coming from video compression.full_ref
: optional flag (default: false) to run CAMBI as a full-reference metric, outputting the per-frame difference between the encoded and source images as well as the existing no-reference score.enc_width
andenc_height
: Encoding/processing resolution to compute the banding score, useful in cases where scaling was applied to the input prior to the computation of metricssrc_width
andsrc_height
: Encoding/processing resolution to compute the banding score on the reference image, only used iffull_ref=true
.heatmaps_path
: Set to a folder where the heatmaps for different scales will be stored as.gray
files
An example using the enc_width
and enc_height
options on the input video KristenAndSara_1280x720_8bit_processed.yuv
which has been encoded at 540p and later upscaled to 1280p (specifying the accurate encoding width and height as input allows CAMBI to more accurately assess the banding artifact):
libvmaf/build/tools/vmaf \
--reference KristenAndSara_1280x720_8bit_processed.yuv \
--distorted KristenAndSara_1280x720_8bit_processed.yuv \
--width 1280 --height 720 --pixel_format 420 --bitdepth 8 \
--no_prediction --feature cambi=enc_width=960:enc_height=540 --output /dev/stdout
This will yield the output:
<VMAF version="4b42f672">
<params qualityWidth="1280" qualityHeight="720" />
<fyi fps="40000.00" />
<frames>
<frame frameNum="0" cambi="1.218365" />
</frames>
<pooled_metrics>
<metric name="cambi" min="1.218365" max="1.218365" mean="1.218365" harmonic_mean="1.218365" />
</pooled_metrics>
<aggregate_metrics />
</VMAF>
If no encoding width and height parameters are specified:
libvmaf/build/tools/vmaf \
--reference KristenAndSara_1280x720_8bit_processed.yuv \
--distorted KristenAndSara_1280x720_8bit_processed.yuv \
--width 1280 --height 720 --pixel_format 420 --bitdepth 8 \
--no_prediction --feature cambi --output /dev/stdout
The output will be:
<VMAF version="4b42f672">
<params qualityWidth="1280" qualityHeight="720" />
<fyi fps="47619.05" />
<frames>
<frame frameNum="0" cambi="0.341833" />
</frames>
<pooled_metrics>
<metric name="cambi" min="0.341833" max="0.341833" mean="0.341833" harmonic_mean="0.341833" />
</pooled_metrics>
<aggregate_metrics />
</VMAF>
To generate the heatmaps, run CAMBI with the heatmaps_path
option set to a local folder. It will write files such as:
cambi_heatmap_scale_0_1280x720_16b.gray
cambi_heatmap_scale_1_640x360_16b.gray
cambi_heatmap_scale_2_320x180_16b.gray
cambi_heatmap_scale_3_160x90_16b.gray
cambi_heatmap_scale_4_80x45_16b.gray
containing the raw grayscale heatmap data.
You can use ffmpeg
to convert them:
ffmpeg -f rawvideo -pix_fmt gray16le -s 1280x720 -i heatmaps/cambi_heatmap_scale_0_1280x720_16b.gray -frames:v 1 heatmaps/cambi_heatmap_scale_0_1280x720_16b.png
CAMBI can also be invoked in the Python library. Use CambiFeatureExtractor
as the feature extractor, and CambiQualityRunner
as the quality runner. Use CambiFullReferenceFeatureExtractor
and CambiFullReferenceQualityRunner
to run the full-reference version of CAMBI.
dis_path = VmafConfig.test_resource_path("yuv", "KristenAndSara_1280x720_8bit_processed.yuv")
asset = Asset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
ref_path=dis_path,
dis_path=dis_path,
asset_dict={'width': 1280, 'height': 720,
'dis_enc_width': 960, 'dis_enc_height': 540})
self.qrunner = CambiQualityRunner(
[asset, asset_original],
None, fifo_mode=False,
result_store=None,
optional_dict={}
)
self.qrunner.run(parallelize=True)
results = self.qrunner.results
# score: arithmetic mean score over all frames
self.assertAlmostEqual(results[0]['Cambi_score'],
1.218365, places=4)