Impulse noise detection is a critical issue when removing impulse noise and impulse/Gaussian mixed noise. In this paper, we propose a new detection mechanism for universal noise and a universal noise-filtering framework based on the nonlocal means (NL-means). The operation is carried out in two stages, i.e., detection followed by filtering. For detection, first, we propose the robust outlyingness ratio (ROR) for measuring how impulselike each pixel is, and then all the pixels are divided into four clusters according to the ROR values. Second, different decision rules are used to detect the impulse noise based on the absolute deviation to the median in each cluster. In order to make the detection results more accurate and more robust, the from-coarse-to-fine strategy and the iterative framework are used. In addition, the detection procedure consists of two stages, i.e., the coarse and fine detection stages. For filtering, the NL-means are extended to the impulse noise by introducing a reference image. Then, a universal denoising framework is proposed by combining the new detection mechanism with the NL-means (ROR-NLM). Finally, extensive simulation results show that the proposed noise detector is superior to most existing detectors, and the ROR-NLM produces excellent results and outperforms most existing filters for different noise models. Unlike most of the other impulse noise filters, the proposed ROR-NLM also achieves high peak signal-to-noise ratio and great image quality by efficiently removing impulse/Gaussian mixed noise.

The comprehensive analysis of biological specimens brings about the demand for capturing the spatial, temporal and spectral dimensions of visual information together. However, such high-dimensional video acquisition faces major challenges in developing large data throughput and effective multiplexing techniques. Here, we report the snapshot hyperspectral volumetric microscopy that computationally reconstructs hyperspectral profiles for high-resolution volumes of ~1000 μm × 1000 μm × 500 μm at video rate by a novel four-dimensional (4D) deconvolution algorithm. We validated the proposed approach with both numerical simulations for quantitative evaluation and various real experimental results on the prototype system. Different applications such as biological component analysis in bright field and spectral unmixing of multiple fluorescence are demonstrated. The experiments on moving fluorescent beads and GFP labelled drosophila larvae indicate the great potential of our method for observing multiple fluorescent markers in dynamic specimens.

Light-sheet microscopy has been widely used in high-speed fluorescence imaging with low phototoxicity, while the trade-off between the field-of-view and optical sectioning capability limits its application in large-scale imaging. Although Bessel beam light-sheet microscopy greatly enhances the light-sheet length with the self-healing ability, it suffers from the strong side-lobe effect. To solve these problems, we introduce the photobleaching imprinting technique in Bessel beam light-sheet microscopy. By extracting the non-linear photobleaching-induced fluorescence decay, we get rid of the large concentric side lobe structures of the Bessel beam to achieve uniform isotropic resolution across a large field-of-view for large-scale fluorescence imaging. Both numerical simulations and experimental results on various samples are demonstrated to show our enhanced resolution and contrast over traditional Bessel-beam light-sheet microscopy.

Integrating light field microscopy techniques with existing miniscope architectures has allowed for volumetric imaging of targeted brain regions in freely moving animals. However, the current design of light field miniscopes is limited by non-uniform resolution and long imaging path length. In an effort to overcome these limitations, this paper proposes an optimized Galilean-mode light field miniscope (Gali-MiniLFM), which achieves a more consistent resolution and a significantly shorter imaging path than its conventional counterparts. In addition, this paper provides a novel framework that incorporates the anticipated aberrations of the proposed Gali-MiniLFM into the point spread function (PSF) modeling. This more accurate PSF model can then be used in 3D reconstruction algorithms to further improve the resolution of the platform. Volumetric imaging in the brain necessitates the consideration of the effects of scattering. We conduct Monte Carlo simulations to demonstrate the robustness of the proposed Gali-MiniLFM for volumetric imaging in scattering tissue.

Various biological behaviors can only be observed in 3D at high speed over the long term with low phototoxicity. Light-field microscopy (LFM) provides an elegant compact solution to record 3D information in a tomographic manner simultaneously, which can facilitate high photon efficiency. However, LFM still suffers from the missing-cone problem, leading to degraded axial resolution and ringing effects after deconvolution. Here, we propose a mirror-enhanced scanning LFM (MiSLFM) to achieve long-term high-speed 3D imaging at super-resolved axial resolution with a single objective, by fully exploiting the extended depth of field of LFM with a tilted mirror placed below samples. To establish the unique capabilities of MiSLFM, we performed extensive experiments, we observed various organelle interactions and intercellular interactions in different types of photosensitive cells under extremely low light conditions. Moreover, we demonstrated that superior axial resolution facilitates more robust blood cell tracking in zebrafish larvae at high speed.

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Light field microscopy (LFM) has been widely used for recording 3D biological dynamics at camera frame rate. However, LFM suffers from artifact contaminations due to the illness of the reconstruction problem via naïve Richardson–Lucy (RL) deconvolution. Moreover, the performance of LFM significantly dropped in low-light conditions due to the absence of sample priors. In this paper, we thoroughly analyze different kinds of artifacts and present a new LFM technique termed dictionary LFM (DiLFM) that substantially suppresses various kinds of reconstruction artifacts and improves the noise robustness with an over-complete dictionary. We demonstrate artifact-suppressed reconstructions in scattering samples such as Drosophila embryos and brains. Furthermore, we show our DiLFM can achieve robust blood cell counting in noisy conditions by imaging blood cell dynamic at 100 Hz and unveil more neurons in whole-brain calcium recording of zebrafish with low illumination power in vivo.

Micro-endoscopes are widely used for detecting and visualizing hard-to-reach areas of the human body and for in vivo observation of animals. A micro-endoscope that can realize 3D imaging at the camera framerate could benefit various clinical and biological applications. In this work, we report the development of a compact light-field micro-endoscope (LFME) that can obtain snapshot 3D fluorescence imaging, by jointly using a single-mode fiber bundle and a small-size light-field configuration. To demonstrate the real imaging performance of our method, we put a resolution chart in different z positions and capture the z-stack images successively for reconstruction, achieving 333-μm-diameter field of view, 24 μm optimal depth of field, and up to 3.91 μm spatial resolution near the focal plane. We also test our method on a human skin tissue section and HeLa cells. Our LFME prototype provides epi-fluorescence imaging ability with a relatively small (2-mm-diameter) imaging probe, making it suitable for in vivo detection of brain activity and gastrointestinal diseases of animals.