Automatic Dust Detection, Isolation, and Mass Measurement Pipeline

Abstract Dust in elliptical galaxy cores provides insights into the interstellar medium and galactic evolution. I present an automated pipeline analyzing archived Hubble Space Telescope WFPC2 and ACS images to detect and measure dust masses in early-type galaxies. Using iterative unsharp masking with Gaussian smoothing to reconstruct dust-free galaxy models, I derive dust surface densities and estimate total masses from extinction maps using a thin-screen approximation and dust mass absorption coefficient κ λ = 0.77. This automated method enables consistent application to large samples, providing a framework for future large-scale studies.