HoloSpec: Dispersion‐Based 4D Computational Holographic Hyperspectral Imaging

Multidimensional imaging, integrating three‐dimensional spatial information with spectral data, is a powerful tool for characterizing target objects. In recent years, the development of low‐cost and miniaturized spectral imaging devices has gained significant research interest. Traditional hyperspectral imaging systems typically rely on time‐consuming scanning techniques or compromise spatial resolution by employing masks and filter arrays, and they are inherently incapable of retrieving phase information. In this paper, we develop a compact, high‐resolution four‐dimensional (4D) imaging system. The system compresses hundreds of spectral channels using a single prism and computationally decodes 4D information (3D spatial and 1D spectral) via holographic back‐propagation and dispersion decompression, and achieves 10–20 times higher spectral resolution in particular. A 4D image is reconstructed from only two monochromatic snapshots by solving a sparsity‐constrained inverse imaging problem. Experimental results demonstrate that the prototype reconstructs 430 computational spectral channels and experimentally resolves spectral peaks separated by , while maintaining high spatial resolution. This system represents the first high‐throughput computational holography device capable of acquiring high‐resolution 4D information. The cost‐effective approach holds great promise for revolutionizing multidimensional imaging and contributing to advancements in various applications.