A Thermodynamic Energy Minimization Approach to Spectral Unmixing of Remote Sensing Imagery

One hurdle involved in remote sensing imagery analysis is the wide existence of mixed pixels, whose footprints cover more than one type of ground materials. The analysis of mixed pixels demands subpixel methods to identify the ground components and infer their relative proportions, a process referred to as spectral unmixing. This paper presents a new approach to mixed pixel analysis, termed thermodynamic energy minimization (TDEM) method. The system of spectral unmixing is considered as an open information system with the measured mixed pixel as input and relative proportions as output. To find the optimal solution at the equilibrium state, we formulate an optimization problem by minimizing the Helmholtz free energy of the information system, which is derived by applying the classical maximum entropy principle to the closed system consisting of both the information system and its surrounding environment. The experimental results based on synthetic images show the effectiveness of the proposed method.