Full-color light-field microscopy via single-pixel imaging

Light-field microscopy is a scanless volumetric imaging technique. Conventional color light microscope employs a micro-lens array at the image plane and samples the spatial, angular, and color information by a pixelated two-dimensional (2D) sensor (such as CCD). However, the space bandwidth product of the pixelated 2D sensor is a fixed value determined by its parameters, leading to the trade-offs between the spatial, angular, and color resolutions. In addition, the inherent chromatic aberration of the micro-lens array also reduces the viewing quality. Here we propose full-color light-field microscopy via single-pixel imaging that can distribute the sampling tasks of the spatial, angular, and color information to both illumination and detection sides, rather than condense on the detection side. Therefore, the space bandwidth product of the light-field microscope is increased and the spatial resolution of the reconstructed light-field can be improved. In addition, the proposed method can reconstruct full-color light-field without using a micro-lens array, thereby the chromatic aberration induced by the micro-lens array is avoided. Because distributing the three sampling tasks to both the illumination and detection sides has different possible sampling schemes, we present two sampling schemes and compare their advantages and disadvantages via several experiments. Our work provides insight for developing a high-resolution full-color light-field microscope. It may find potential applications in the biomedical and material sciences.

FIMic: design for ultimate 3D-integral microscopy of in-vivo biological samples

In this work, Fourier integral microscope (FIMic), an ultimate design of 3D-integral microscopy, is presented. By placing a multiplexing microlens array at the aperture stop of the microscope objective of the host microscope, FIMic shows extended depth of field and enhanced lateral resolution in comparison with regular integral microscopy. As FIMic directly produces a set of orthographic views of the 3D-micrometer-sized sample, it is suitable for real-time imaging. Following regular integral-imaging reconstruction algorithms, a 2.75-fold enhanced depth of field and [Formula: see text]-time better spatial resolution in comparison with conventional integral microscopy is reported. Our claims are supported by theoretical analysis and experimental images of a resolution test target, cotton fibers, and in-vivo 3D-imaging of biological specimens.

Resolution improvements in integral microscopy with Fourier plane recording

Integral microscopes (IMic) have been recently developed in order to capture the spatial and the angular information of 3D microscopic samples with a single exposure. Computational post-processing of this information permits to carry out a 3D reconstruction of the sample. By applying conventional algorithms, both depth and also view reconstructions are possible. However, the main drawback of IMic is that the resolution of the reconstructed images is low and axially heterogeneous. In this paper, we propose a new configuration of the IMic by placing the lens array not at the image plane, but at the pupil (or Fourier) plane of the microscope objective. With this novel system, the spatial resolution is increased by factor 1.4, and the depth of field is substantially enlarged. Our experiments show the feasibility of the proposed method.

Free-depths reconstruction with synthetic impulse response in integral imaging

Integral Imaging provides spatial and angular information of three-dimensional (3D) objects, which can be used both for 3D display and for computational post-processing purposes. In order to recover the depth information from an integral image, several algorithms have been developed. In this paper, we propose a new free depth synthesis and reconstruction method based on the two-dimensional (2D) deconvolution between the integral image and a simplified version of the periodic impulse response function (IRF) of the system. The period of the IRF depends directly on the axial position within the object space. Then, we can retrieve the depth information by performing the deconvolution with computed impulse responses with different periods. In addition, alternative reconstructions can be obtained by deconvolving with non-conventional synthetic impulse responses. Our experiments show the feasibility of the proposed method as well as its potential applications.

Resolution enhancement in integral microscopy by physical interpolation

Integral-imaging technology has demonstrated its capability for computing depth images from the microimages recorded after a single shot. This capability has been shown in macroscopic imaging and also in microscopy. Despite the possibility of refocusing different planes from one snap-shot is crucial for the study of some biological processes, the main drawback in integral imaging is the substantial reduction of the spatial resolution. In this contribution we report a technique, which permits to increase the two-dimensional spatial resolution of the computed depth images in integral microscopy by a factor of √2. This is made by a double-shot approach, carried out by means of a rotating glass plate, which shifts the microimages in the sensor plane. We experimentally validate the resolution enhancement as well as we show the benefit of applying the technique to biological specimens.

Voxel model for evaluation of a three-dimensional display and reconstruction in integral imaging

An approximate voxel model for integral imaging is proposed by ray tracing. By analyzing the case of corresponding pixels overlapping completely and partially in the image space, the voxel is defined with an appropriate approximation, and the voxel size and its distribution feature in imaging space are derived. The model is verified in a reconstruction experiment of a resolution target and compared with the calculation result of an integral imaging display or reconstruction system. The proposed model is simple and easy to calculate and thus useful for the evaluation and optimization of integral imaging systems.