Transmissive Single-Pixel Microscopic Imaging through Scattering Media

Single-pixel imaging based on metasurface fuzzy coding

Single-pixel imaging, renowned for its high sensitivity, robustness against interference, and superior resolution, has become increasingly prominent in the field of optical research. Over recent years, a diverse array of light modulation devices and methodologies has been devised to accomplish megahertz modulations rates. This work presents a single-pixel imaging scheme based on the fuzzy coding of metasurfaces. This unique encoding technique manipulates the quality of the mask pattern by adjusting the pixel count within the metasurface units. Notably, we expand the metasurface units to effectively mitigate the position sensitivity during movement or rotations, thus easing the challenge for the detector in collecting the correct light intensity during sub-mask transitions. A detailed analysis is drawn of the reconstruction quality of fuzzy masks. Simultaneously, we provide simulations of single-pixel imaging under the condition where the fuzzy-coded metasurface is moving. This work provides a new, to the best of our knowledge, mask generation mode for high-speed spatial light modulation.

Comparison of Common Algorithms for Single-Pixel Imaging via Compressed Sensing

Single-pixel imaging (SPI) uses a single-pixel detector instead of a detector array with a lot of pixels in traditional imaging techniques to realize two-dimensional or even multi-dimensional imaging. For SPI using compressed sensing, the target to be imaged is illuminated by a series of patterns with spatial resolution, and then the reflected or transmitted intensity is compressively sampled by the single-pixel detector to reconstruct the target image while breaking the limitation of the Nyquist sampling theorem. Recently, in the area of signal processing using compressed sensing, many measurement matrices as well as reconstruction algorithms have been proposed. It is necessary to explore the application of these methods in SPI. Therefore, this paper reviews the concept of compressive sensing SPI and summarizes the main measurement matrices and reconstruction algorithms in compressive sensing. Further, the performance of their applications in SPI through simulations and experiments is explored in detail, and then their advantages and disadvantages are summarized. Finally, the prospect of compressive sensing with SPI is discussed.

A Single-Pixel Imaging Scheme with Obstacle Detection

Single-pixel imaging (SPI) utilizes a second-order correlation of structured illumination light field and a single-pixel detector to form images. As the single-pixel detector provides no spatial resolution, a structured illumination light field generated by devices such as a spatial light modulator substitutes the role of array camera to retrieve pixel-wise spatial information. Due to its unique imaging modality, SPI has certain advantages. Meanwhile, its counterintuitive configuration and reciprocity relation to traditional array cameras have been studied to understand its fundamental principle. According to previous studies, the non-spatial detection property makes it possible for SPI to resist scattering in the detection part. In this work, we study the influence of an obstacle aperture in the detection part of SPI. We notice that such an obstacle aperture can restrict the field-of-view (FOV) of SPI, which can be diminished by a scattering process. We investigate these properties with experiment results and analysis under geometry optics. We believe that our study will be helpful in understanding the counterintuitive configuration of SPI and its reciprocity to traditional imaging.