Filtering of the disparity map
Theoretical basics
The filtering methods allow to homogenize the disparity maps, those available in pandora are :
median filter.
bilateral filter.
median filter for intervals. See Cost volume confidence for more details.
Note
Invalid pixels are not filtered. If a valid pixel contains an invalid pixel in its filter, the invalid pixel is ignored for the calculation
Name |
Description |
Type |
Default value |
Available value |
Required |
---|---|---|---|---|---|
filter_method |
Filtering method |
str |
“median”,
“bilateral”,
“median_for_intervals”
|
Yes |
|
filter_size |
Filter’s size |
int |
3 |
>=1 |
No. Only available if “median” or “median_for_intervals” filter |
sigma_color |
Bilateral filter parameter |
float |
2.0 |
No. Only available if “bilateral” filter |
|
sigma_space |
Bilateral filter parameter |
float |
6.0 |
No. Only available if “bilateral” filter |
|
regularization |
Activate regularization |
bool |
false |
true, false |
No. Only available if “median_for_intervals” filter |
ambiguity_indicator |
Indicator for which ambiguity to use during regularization.
Ex: If cfg contains a step “confidence_from_ambiguity.amb”
then ambiguity_indicator should be “amb”
|
str |
“” |
No. Only available if “median_for_intervals” filter |
|
ambiguity_threshold |
A pixel is regularized if threshold>ambiguity |
float |
0.6 |
>0 and <1 |
No. Only available if “median_for_intervals” filter |
ambiguity_kernel_size |
Ambiguity kernel size for regularization. See publication for details. |
int |
5 |
>=0 |
No. Only available if “median_for_intervals” filter |
vertical_depth |
Depth for graph regularization. See publication for details. |
int |
2 |
>=0 |
No. Only available if “median_for_intervals” filter |
quantile_regularization |
Quantile used for regularization |
float |
0.9 |
>=0 and <=1 |
No. Only available if “median_for_intervals” filter |
Example
{
"input" :
{
// ...
},
"pipeline" :
{
// ...
"filter":
{
"filter_method": "median"
}
// ...
}
}