meditation: edge division

Problem

1. hole-based edge detection has the advantage of finding the true depth-present edge(top edges)
   
2. but the shape of the holes are more versatile in that there are inwards stings that cause problems in inner/outer edge division, e.g. no easy reference radius to look at even at a very narrow azimuth window.
3. the wrong division (incorporate extraneous blobs) will cause a sting if we sample that azimuth and take only the outermost/innermost point.

Dilemma

1. we want to interpolate based on a continuous edge array
2. but the array contains wrong data (stings)
3. to remove the wrong data, we need to do angular-sampling to evaluate the edge
4. this sampling would be a downsampling and could cause blur.

Question

1. do we wanna downsample at first to get the resampled-edge or thereafter?

Answer

1. whichever helps us preserve the resolution....
2. then it should be after the raw edge extracted.
3. so during sting-removal, for normal edge data, we keep them all (more than sampled data), but only exclude detected stings among the sampled data.

Raw edge detection

1. CC-based or hole-based?
2. CC-based: simple and straightforward to implement but not physically reasonable, no real depth data at the lateral position, need interpolation.
3. hole-based: physically reasonable, but hard to implement when it comes to inner/outer division, because more susceptible to CC-stings.

Solution

1. CC-based: after raw edge detection, get depth from neighbor hole-points (radius extrapolation), need interpolation; ring shaped part needs to look at wider adjacency.
2. Hole-based: after raw edge detection, do a CC-HO band division; for each hole edge point, look at its 8-neighbor and find the dominant CC index and assign it to the CC as either inner/outer edge depending on the band-division.(NO INTERPOLATION INVOLVED)