Spectral-Spatial Interpretation: A method for interpreting multispectral data models
In brief
- SSI provides a combined spatial-spectral attribution matrix for multispectral data models.
- It outperforms an existing estimator (MC-Owen) while cutting evaluation costs by 94%.
- Results are validated on multiple datasets (HLS Burn Scar, CUB-200, EuroSAT).
Researchers introduce Spectral-Spatial Interpretation (SSI), a post-hoc interpretation method for models handling multispectral data. According to the announcement, SSI generates a full attribution matrix covering both spatial and spectral dimensions, unlike traditional approaches that separate these aspects.
The study compares SSI to existing methods like the MC-Owen estimator across datasets such as HLS Burn Scar, CUB-200, and EuroSAT. Results show SSI outperforms MC-Owen while reducing evaluation costs by 94 %. The method is presented as offering clear local interpretation and strong theoretical properties, with open-source code available.
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