Date of Award
2026
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
Committee Chair
Tathagata Mukherjee
Committee Member
Aaron Kaulfus
Committee Member
Brian Freitag
Research Advisor
Tathagata Mukherjee
Subject(s)
Image processing--Digital techniques, Remote sensing--Data processing, CubeSats
Abstract
The PlanetScope SuperDove constellation consists of approximately 130 CubeSats. Radiometric drift among the satellites degrades time-series workflows. We formulate inter-sensor harmonization as a supervised regression problem and train a single model across all eight spectral bands using overlapping regions from cross- sensor image pairs. Controlled experiments on same-day image pairs show that a cubic spline model with 20 uniform knots and joint Ridge regularization achieves the lowest error among the evaluated per-pixel regression approaches. The model converges to a Kullback-Leibler divergence between 0.001 and 0.003, and no alternative architecture studied achieves a statistically significant improvement. Models that fit on each spectral band independently generally perform worse, indicating that cross-band coupling contributes to harmonization performance. The cubic spline model performs poorly on cross-region image pairs, indicating that the harmonization fit on one region does not transfer to another and that training data quality has a greater impact on harmonization performance than model architecture.
Recommended Citation
Pathak, Biraj Bikram, "Methods for inter-sensor radiometric harmonization of PlanetScope SuperDove constellation" (2026). Theses. 845.
https://louis.uah.edu/uah-theses/845