Ultra-high-speed imaging serves as a foundation for modern science. While in biomedicine, optical-fiber-based endoscopy is often required for in vivo applications, the combination of high speed with the fiber endoscopy, which is vital for exploring transient biomedical phenomena, still confronts some challenges. We propose all-fiber imaging at high speeds, which is achieved based on the transformation of two-dimensional spatial information into one-dimensional temporal pulsed streams by leveraging high intermodal dispersion in a multimode fiber. Neural networks are trained to reconstruct images from the temporal waveforms. It can not only detect content-aware images with high quality, but also detect images of different kinds from the training images with slightly reduced quality. The fiber probe can detect micron-scale objects with a high frame rate (15.4 Mfps) and large frame depth (10,000). This scheme combines high speeds with high mechanical flexibility and integration and may stimulate future research exploring various phenomena in vivo.

Single fiber imaging has evolved into a powerful method for detecting minute objects in narrow spaces. However, existing systems are not conducive to imaging dynamic objects at depth due to their bulky probes, time-consuming scanning acquisition methods, and transmissive illumination mode. Minimally invasive reflection mode imaging with high spatial and temporal resolution remains an open challenge. Here, a precise and high-speed imaging scheme without scanning is proposed. Multimode fiber imaging technology is incorporated into an all-fiber aberration-free precision detection system. High temporal resolution (5000 fps) detection of tiny natural scenes is experimentally realized by optimizing the approximation of the inverse transmission matrix in a simple and compact setup. The system can display the detected screen in real-time and the computational imaging with a large depth of field (1 mm) is enabled by jointly learning. The recovery results are superior compared to typical deep neural networks. The demonstrated scheme offers a new possibility for many applications, for example, microendoscopy, all-optical computing, and remote high-speed video transmission.

By amplifying the cascaded random Raman fiber laser (RRFL) oscillator and ytterbium fiber laser oscillator, we present the first, to the best of our knowledge, demonstration of a 10-kW-level high-spectral-purity all-fiber ytterbium–Raman fiber amplifier (Yb-RFA). With a carefully designed backward-pumped RRFL oscillator structure, the parasitic oscillation between the cascaded seeds is avoided. Leveraging the RRFL with full-open-cavity as the Raman seed, the Yb-RFA realizes 10.7-kW Raman lasing at 1125 nm, which is beyond the operating wavelengths of all the reflection components used in the system. The spectral purity of the Raman lasing reaches 94.7% and the 3-dB bandwidth is 3.9 nm. This work paves a way to combine the temporal stability of the RRFL seed and the power scaling of Yb-RFA, enabling the wavelength extension of high-power fiber lasers with high spectral purity.

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