The richness of hyperspectral imaging (HSI)-collected signals makes possible quantitative inference by the inverse problem-solving of the chemical and biophysical parameters of the imaged object. In this article, we first propose a classification of the large variety of literature on invertible physics-based hyperspectral signature models by analyzing their founding hypotheses and methodologies. All the models found in the literature are based on the radiative transfer theory (RTT), but they are divided into three main branches. In the first one, the models rely on the Beer-Lambert law. In the second and the third ones, the models are based on Lommel’s radiative transfer equation (RTE), which they simplify into a diffusion approximation equation or into a single- and multiple-scattering approximation equation, respectively. Thereafter, we present the most recent models available for each branch for applications in geoscience and remote sensing domains: MARMIT-1 and MARMIT-2 for soil, the Microphytobenthos Optical Model (MPBOM) for algae and bacteria biofilm, PROSPECT for plant leaves, Farrell for fruits and vegetables, and Hapke for solar system objects. On the one hand, this article provides an overview of the different works in the literature. On the other hand, it proposes a classification tree of the different models, allowing one to know the similarities and differences of the different models. Ultimately, the aim is to assist researchers in selecting an appropriate model based on their specific targeted application.

中文翻译：

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基于可逆物理的高光谱特征模型：综述

高光谱成像（HSI）收集的信号丰富，使得通过成像对象的化学和生物物理参数的逆向问题解决来进行定量推断成为可能。在本文中，我们首先通过分析基于可逆物理的高光谱特征模型的大量文献的基本假设和方法，提出了分类。文献中发现的所有模型都基于辐射传输理论（RTT），但它们分为三个主要分支。在第一个模型中，模型依赖于比尔-朗伯定律。在第二个和第三个模型中，模型基于 Lommel 辐射传递方程 (RTE)，它们分别将其简化为扩散近似方程或单散射和多散射近似方程。此后，我们介绍了每个分支在地球科学和遥感领域应用的最新模型：用于土壤的 MARMIT-1 和 MARMIT-2、用于藻类和细菌生物膜的底栖微生物光学模型 (MPBOM)、用于植物叶子的 PROSPECT、Farrell水果和蔬菜，Hapke 代表太阳系天体。一方面，本文概述了文献中的不同作品。另一方面，它提出了不同模型的分类树，使人们能够了解不同模型的异同。最终的目的是帮助研究人员根据其特定的目标应用选择合适的模型。