New top story on Hacker News: Show HN: Feature detection exploration in Lidar DEMs via differential decomp

Show HN: Feature detection exploration in Lidar DEMs via differential decomp
3 by DarkForestery | 0 comments on Hacker News.
I'm not a geospatial expert — I work in AI/ML. This started when I was exploring LiDAR data with agentic assitince and noticed that different signal decomposition methods revealed different terrain features. The core idea: if you systematically combine decomposition methods (Gaussian, bilateral, wavelet, morphological, etc.) with different upsampling techniques, each combination has characteristic "failure modes" that selectively preserve or eliminate certain features. The differences between outputs become feature-specific filters. The framework tests 25 decomposition × 19 upsampling methods across parameter ranges — about 40,000 combinations total. The visualization grid makes it easy to compare which methods work for what. Built in Cursor with Opus 4.5, NumPy, SciPy, scikit-image, PyWavelets, and OpenCV. Apache 2.0 licensed. I'd appreciate feedback from anyone who actually works with elevation data. What am I missing? What's obvious to practitioners that I wouldn't know?

Government suspends Gabon team, bans Aubameyang and sacks coach

Gabon's sports minister announces a series of punishments after the national team's "disgraceful performance" at the Africa Cup of Nations.

from BBC News https://ift.tt/6n2YFMi
via IFTTT