Fast ambient occlusion using 2D depth buffer technique. Much faster than PCV as it works on projected depth maps.
compute_ssao(
las,
kernel_size = 5,
pixel_size = 0.1,
num_samples = 16,
ncpu = 4
)Numeric vector of SSAO values (ambient occlusion) for each point
LAS object
Integer kernel size in pixels for sampling
Numeric resolution of the depth map in spatial units
Integer number of samples per point
Integer number of CPUs to use for parallel processing
The SSAO algorithm computes ambient occlusion by:
Projecting the point cloud to a 2D depth map (grid)
For each point, sampling the depth buffer around it
Calculating occlusion based on depth differences
Applying distance and angle-based falloff
This is significantly faster than full 3D PCV because it only requires 2D image processing operations rather than 3D neighbor searches and ray tracing.