Looking into a Pixel by Nonlinear Unmixing -- A Generative Approach
Due to the large footprint of pixels in remote sensing imagery, hyperspectral unmixing (HU) has become an important and necessary procedure in hyperspectral image analysis. Traditional HU methods rely on a prior spectral mixing model, especially for nonlinear mixtures, which has largely limited the performance and generalization capacity of the unmixing approach. In this paper, we address the challenging problem of hyperspectral nonlinear unmixing (HNU) without explicit knowledge of the mixing model. Inspired by the principle of generative models, where images of the same distribution can be generated as that of the training images without knowing the exact probability distribution functi...
| Authors | Maofeng Tang, Hairong Qi |
|---|---|
| Primary category | cs.CV |
| Published | 1 April 2026 |
| Last updated at source | 1 April 2026 |
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