Hyperspectral remote sensing is a commonly used technical means for mineral detection on the Martian surface, which has important implications for the study of Martian geological evolution and the study for potential biological signatures. The increasing volume of Martian remote sensing data and complex issues such as the intimate mixture of Martian minerals make research on Martian mineral detection challenging. This paper summarizes the existing achievements by analyzing the papers published in recent years and looks forward to the future research directions. Specifically, this paper introduces the currently used hyperspectral remote sensing data of Mars and systematically analyzes the characteristics and distribution of Martian minerals. The existing methods are then divided into two groups, according to their core idea, i.e., methods based on pixels and methods based on subpixels. In addition, some applications of Martian mineral detection at global and local scales are analyzed. Furthermore, the various typical methods are compared using synthetic and real data to assess their performance. The conclusion is drawn that approach based on spectral unmixing is more applicable to areas with limited and unknown mineral categories than pixel-based methods. Among them, the fully autonomous hyperspectral unmixing method can improve the overall accuracy in real CRISM images and has great potential for Martian mineral detection. The development trends are analyzed from three aspects. Firstly, in terms of data, a more complete spectral library, covering more spectral information of the Martian surface minerals, should be constructed to assist with mineral detection. Secondly, in terms of methods, spectral unmixing methods based on a nonlinear mixing model and a new generation of data-driven detection paradigms guided by Mars mineral knowledge should be developed. Finally, in terms of application, the global mapping of Martian minerals toward a more intelligent, global scale, and refined direction should be targeted in the future. The data and source code in the experiment are available at http://rsidea.whu.edu.cn/Martian_mineral_detection.htm.

中文翻译：

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基于火星高光谱遥感影像的矿物探测：从探测方法到精细制图


高光谱遥感是火星表面矿物探测常用的技术手段，对火星地质演化研究和潜在生物特征的研究具有重要意义。火星遥感数据量的增加和火星矿物的密切混合等复杂问题使火星矿物探测研究具有挑战性。本文通过分析近年来发表的论文，总结了现有成果，并对未来的研究方向进行了展望。具体来说，本文介绍了目前使用的火星高光谱遥感数据，并系统分析了火星矿物的特征和分布。然后将现有方法根据其核心思想分为两组，即基于像素的方法和基于子像素的方法。此外，还分析了火星矿物探测在全球和局部尺度上的一些应用。此外，使用合成数据和真实数据对各种典型方法进行比较，以评估它们的性能。得出的结论是，与基于像素的方法相比，基于光谱解混的方法更适用于矿物类别有限和未知的区域。其中，全自动高光谱解混方法可以提高真实 CRISM 图像的整体精度，在火星矿物探测方面具有巨大潜力。从三个方面分析了发展趋势。首先，在数据方面，构建更完整的光谱库，覆盖更多的火星表面矿物光谱信息，以辅助矿物探测。 其次，在方法方面，应开发基于非线性混合模型的光谱解混方法，以及以火星矿物知识为指导的新一代数据驱动探测范式。最后，在应用方面，未来应将火星矿物的全球地图绘制为更智能、更全球化、更精细的方向。实验中的数据和源代码可在 http://rsidea.whu.edu.cn/Martian_mineral_detection.htm 上获得。