Amp-vortex edge-camera: a lensless multi-modality imaging system with edge enhancement

CFZA camera: a high-resolution lensless imaging technique based on compound Fresnel zone aperture

In lensless imaging using a Fresnel zone aperture (FZA), it is generally believed that the resolution is limited by the outermost ring breadth of the FZA. The limitation has the potential to be broken according to the multi-order property of binary FZAs. In this Letter, we propose to use a high-order component of the FZA as the point spread function (PSF) to develop a high-order transfer function backpropagation (HBP) algorithm to enhance the resolution. The proportion of high-order diffraction energy is low, leading to severe defocus noise in the reconstructed image. To address this issue, we propose a Compound FZA (CFZA), which merges two partial FZAs operating at different orders as the mask to strike a balance between the noise and resolution. Experimental results verify that the CFZA-based camera has a resolution that is double that of a traditional FZA-based camera with an identical outer ring breadth and can be reconstructed with high quality by a single HBP without calibration. Our method offers a cost-effective solution for achieving high-resolution imaging, expanding the potential applications of FZA-based lensless imaging in a variety of areas.

Temporal compressive edge imaging enabled by a lensless diffuser camera

Lensless imagers based on diffusers or encoding masks enable high-dimensional imaging from a single-shot measurement and have been applied in various applications. However, to further extract image information such as edge detection, conventional post-processing filtering operations are needed after the reconstruction of the original object images in the diffuser imaging systems. Here, we present the concept of a temporal compressive edge detection method based on a lensless diffuser camera, which can directly recover a time sequence of edge images of a moving object from a single-shot measurement, without further post-processing steps. Our approach provides higher image quality during edge detection, compared with the "conventional post-processing method." We demonstrate the effectiveness of this approach by both numerical simulation and experiments. The proof-of-concept approach can be further developed with other image post-processing operations or versatile computer vision assignments toward task-oriented intelligent lensless imaging systems.

Nonlinear edge enhancement imaging based on Laguerre-Gaussian superimposed vortex filters

Nonlinear reconstruction, which is based on the principle of cross correlation, is a commonly employed reconstruction technique in incoherent correlated digital holography systems. However, the modulation of phase masks in these systems is suppressed during the reconstruction process, resulting in an inability to express the characteristics of the phase masks. Consequently, achieving edge enhancement within these systems is constrained. We propose a nonlinear reconstruction method utilizing Laguerre-Gaussian superimposed vortex filters, which modulates the spectrum of the target during the reconstruction process. Experimental results demonstrate that this method performs well in reconstructing image edges for various phase-masked incoherent imaging systems and effectively suppresses noise. Additionally, this method enables directional edge enhancement.