Cost Aggregation
Theoretical basics
The second step is to aggregate the matching costs:
Cross-based Cost Aggregation [Zhang2009]. This method consists in creating aggregation support regions that adapt to the structures present in the scene, it is performed in 5 steps:
a 3x3 median filter is applied to the left image (left image) and the right image (right image),
cross support region computation of each pixel of the left image,
cross support region computation of each pixel of the right image,
combination of the left and right support region,
the matching cost is averaged over the combined support region.
Zhang, K., Lu, J., & Lafruit, G. (2009). Cross-based local stereo matching using orthogonal integral images. IEEE transactions on circuits and systems for video technology, 19(7), 1073-1079.
Configuration and parameters
Name |
Description |
Type |
Default value |
Available value |
Required |
---|---|---|---|---|---|
aggregation_method |
Aggregation method |
string |
“cbca” |
Yes |
|
cbca_intensity |
Maximum intensity difference between 2 points |
float |
30.0 |
>0 |
No. Only available if “cbca” method |
cbca_distance |
Maximum distance difference between 2 points |
int |
5 |
>0 |
No. Only available if “cbca” method |
Example
{
"input" :
{
// ...
},
"pipeline" :
{
// ...
"aggregation":
{
"aggregation_method": "cbca",
"cbca_intensity": 25.0
}
// ...
}
}