**Hyperspectral Nonlinear Unmixing by Using PlugȬandȬPlay Prior for Abundance Maps**

**Zhicheng Wang 1,2, Lina Zhuang 3, Lianru Gao 1,\*, Andrea Marinoni 4, Bing Zhang 1,2 and Michael K. Ng <sup>5</sup>**


This paper proposed a new nonlinear unmixing method based on a general bilinear model. Instead of investing effort in designing more regularizing abundance fractions, a plug-and-play prior technique was developed to exploit the spatial correlation of abundance maps and nonlinear interaction maps. The numerical results in simulated data and a real hyperspectral dataset showed that the proposed method could improve the estimation of abundances dramatically compared with state-of-the-art nonlinear unmixing methods.

VI. **Hyperspectral Sensor Hardware Design (one paper)**

remotesensingȬ13Ȭ03295Ȭv2
