Metasurfaces represent a paradigm shift in optical device design, offering unprecedented capabilities for manipulating light at subwavelength scales. High-dimensional perceptual systems that integrate spectral, spatial, and geometric information are emerging as the core enablers of next-generation artificial intelligence (AI)-driven machine vision and autonomous decision-making. Leveraging their compact, ultrathin, and highly integrable design, metasurfaces are highly compatible with the demands of advanced high-dimensional perceptual systems. In advanced multispectral imaging and image feature detection, such as hyperspectral sensing, depth mapping, and edge recognition, metasurfaces enable functionalities that are difficult or impossible to realize with traditional bulky optics. By integrating these functionalities through metasurfaces, optical hardware can be significantly simplified while enabling new paradigms of intelligent and data-driven imaging. This is especially crucial for portable, energy-efficient, and high-resolution systems required in applications ranging from environmental monitoring to space exploration and biomedical diagnostics. We highlighted recent breakthroughs in metasurfaces-based spectral imaging and feature detection and emphasized the transformative potential of integrating AI into these systems. The synergy between metasurfaces and AI is expected to promote smart sensing and autonomous perception.

Over the past decade, metasurfaces have emerged as a groundbreaking new class of flat optical devices with significant application potential. Enabled by tailored nanoresonators and subwavelength structures, metasurfaces allow precise control over the phase, amplitude, polarization, and dispersion of optical waves. These capabilities have significantly advanced next-generation spectral imaging and optical information processing, particularly in scenarios where traditional bulky and multi-element optical systems are constrained by size and integration complexity.

In the field of hyperspectral imaging, a variety of novel approaches have been proposed to realize lightweight, high-resolution, and multi-band integrated spectral imaging systems. According to the underlying working principles, metasurfaces-based spectral imaging strategies can be classified into three main categories: dispersive type, narrowband filtering type, and computational reconstruction type. For each category, we outlined the fundamental operational mechanisms and summarized the current state-of-the-art developments. Unlike achromatic metasurfaces, dispersive spectral imaging metasurfaces spatially separate different wavelengths onto distinct positions on the image sensor, thereby enabling the acquisition of multispectral images (Fig. 1). Researchers have explored the applications from spectral detection toward multispectral imaging based on metasurfaces. Another promising method for multispectral imaging is to use narrowband filter arrays, where each filter is designed to transmit a specific wavelength band (Fig. 2). Metasurfaces-enabled narrowband filtering offers potential for lightweight integration and tunable spectral filtering functionalities. Computational spectral imaging reconstructs the original spectral image by establishing a spectral transfer model (Fig. 3 and Fig. 4). This approach mitigates the low efficiency caused by filtering and achieves high spatial and spectral resolution, making it a promising direction for the next-generation of spectral imaging technologies.

In parallel, researchers have also recently explored metasurfaces?based techniques for depth and edge feature detection. Depth sensing enables devices to perceive the spatial positions of objects, whereas edge detection facilitates the identification of their geometric contours. In this review, depth sensing techniques were classified as either passive or active, depending on whether external illumination is required. Passive methods based on meta-lenses (Fig. 6) and active approaches that employ metasurfaces to generate structured light (Fig. 7) currently represent the dominant research directions. In comparison, active depth sensing based on metasurfaces can achieve higher spatial/angular resolution and a wider measurement field of view (FOV), yielding markedly denser point clouds and broader angular coverage than traditional components. Edge feature detection is a paradigmatic optical analog computing application. It significantly reduces data?processing requirements while preserving essential image characteristics. Leveraging the principle of optical differentiation, metasurfaces-based devices can perform direct edge imaging, offering a low?power and real?time solution for extracting edges from large?volume image data (Fig. 8 and Fig. 9).

It is worth noting that with the rapid development of computer computing power over the past two decades and the breakthroughs in technologies such as deep learning, the convergence of AI and metasurfaces has emerged and was discussed in this review. In this context, AI serves both as a powerful tool for inverse design and optimization of metasurfaces and as a robust means for data?driven post?processing in metasurfaces?based optical systems (Fig. 5 and Fig. 10). Finally, building upon the aforementioned advances, we discussed the prospects of metasurfaces in demanding environments such as marine and space applications, underscoring their exceptional performance (Fig. 11).

With continuous advancements in nanofabrication techniques and optimization methodologies, a variety of high-performance metasurfaces-based devices have emerged these years. In the fields of hyperspectral remote sensing imaging and compact machine vision detection systems, metasurfaces-based devices have demonstrated performance that surpasses traditional complex optical systems. Moreover, their unique advantages of miniaturization and low power consumption make them more suitable for widespread integration into microdevices. It is widely anticipated that AI-assisted advancements in metasurface design and applications will represent a key direction for future development. These emerging breakthroughs are expected to enable the practical deployment of meta-devices in complex and demanding environments. In the near future, optical components based on metasurfaces are likely to become integral parts of our daily life, serving as core elements of next-generation optical systems.