A Multispectral Automated Transfer Technique (MATT) for machine-driven image labeling utilizing the Segment Anything Model (SAM)

Understand

Segment Anything Model (SAM) is drastically accelerating the speed and accuracy of automatically segmenting and labeling large Red-Green-Blue (RGB) imagery datasets.

• However, SAM is unable to segment and label images outside of the visible light spectrum, for example, for multispectral or hyperspectral imagery.
• Therefore, this paper outlines a method we call the Multispectral Automated Transfer Technique (MATT).
• By transposing SAM segmentation masks from RGB images we can automatically segment and label multispectral imagery with high precision and efficiency.