Because I'm working with coastal imagery, nearly every photo in the dataset (~4,000) has water pixels in it. This has caused a lot of noise in the dense cloud, particularly near the land-water interface (which is were I'm interested in studying) I think it'd be rather inefficient to try and mask every photo manually in Photoscan or photoshop. I had a tip from someone to, during the gradual selection phase, remove all tie-points that had an image count of 2. Not only did this remove much more than half of the points (not the best overlap), but I still ended up with a bunch of noisy points in the water. T
Since the ROI is rather large, my next thought was to try filtering these points out systematically with a filter (maybe in cloud compare) looking for areas of high frequency z change.
Has anyone had any luck with filters in or outside of cloud compare filtering out noise due to water? I've attached a screenshot of some of the noise.
Thanks.