Resolution-enhanced integral imaging in focal mode with a time-multiplexed electrical mask array.

The inferior resolution of the three-dimensional (3D) image is one of the main problems to be resolved for realizing a commercial autosteresosopic 3D display device. In this paper, a time-multiplexing technique using electrically moving masks is proposed to enhance the resolution of the 3D image realized by integral imaging in a focal mode while preserving the viewing angle of it.

Multi-projection integral imaging by use of a convex mirror array.

We propose a new multi-projection integral imaging scheme using a convex mirror array. In the proposed scheme, to overcome the resolution limitation of the conventional method due to observing the single aperture imaging point (AIP) from each convex mirror, we introduce the multi-projection to obtain multiple AIPs per convex mirror so that the viewer observes the resolution-improved 3D reconstructed images. We validate the theoretical analysis of the proposed scheme and confirm its feasibility through the optical experiments.

Optical three-dimensional refocusing from elemental images based on a sifting property of the periodic δ-function array in integral-imaging.

We propose a novel approach to optically refocus three-dimensional (3-D) objects on their real depth from the captured elemental image array (EIA) by using a sifting property of the periodic δ-function array (PDFA) in integral-imaging. By convolving the PDFAs whose spatial periods correspond to each object's depth with the sub-image array (SIA) transformed from the EIA, a set of spatially filtered-SIAs (SF-SIAs) for each object's depth can be extracted. These SF-SIAs are then inverse-transformed into the corresponding versions of the EIAs, and from these, 3-D objects with their own perspectives can be reconstructed to be refocused on their depth in the space.

Three-dimensional imaging and visualization using off-axially distributed image sensing.

This Letter presents an off-axially distributed image sensing (ODIS) system for three-dimensional (3D) imaging and visualization. The off-axially distributed sensing method provides both lateral and longitudinal perspectives for 3D scenes even though the sensor moves along a slanted, one-dimensional path. A 3D volume is generated from a set of recorded images by use of a computational algorithm based on ray backprojection.

Depth extraction of 3D objects using axially distributed image sensing.

Axially distributed image sensing (ADS) technique is capable of capturing 3D objects and reconstructing high-resolution slice plane images for 3D objects. In this paper, we propose a computational method for depth extraction of 3D objects using ADS. In the proposed method, the high-resolution elemental images are recorded by simply moving the camera along the optical axis and the recorded elemental images are used to generate a set of 3D slice images using the computational reconstruction algorithm based on ray back-projection.

Three-dimensional integral imaging with improved visualization using subpixel optical ray sensing.

In this Letter, we propose an improved three-dimensional (3D) image reconstruction method for integral imaging. We use subpixel sensing of the optical rays of the 3D scene projected onto the image sensor. When reconstructing the 3D image, we use a calculated minimum subpixel distance for each sensor pixel instead of the average pixel value of integrated pixels from elemental images.

Three-dimensional imaging and visualization of partially occluded objects using axially distributed stereo image sensing.

In this Letter, we propose a multiperspective three-dimensional (3D) imaging system using axially distributed stereo image sensing. In this proposed method, the stereo camera is translated along its optical axis and multiple axial elemental image pairs for a 3D scene are collected. The captured elemental images are reconstructed in 3D using a computational reconstruction algorithm based on ray back-projection.

Generalization of three-dimensional N-ocular imaging systems under fixed resource constraints.

The performance of multiview three-dimensional imaging systems depends on several factors, including the number of sensors, sensor pixel size, relative sensor configuration, imaging optics, and computational reconstruction algorithm. Therefore, it is important to compare the performance of such systems under equally constrained resources. In this Letter, we develop a unifying framework to evaluate the lateral and axial resolution of N-ocular imaging systems ranging from stereo (two cameras) to multiple sensors (integral imaging) under fixed resource constraints.

Optofluidic system for three-dimensional sensing and identification of micro-organisms with digital holographic microscopy.

Optofluidic devices offer flexibility for a variety of tasks involving biological specimen. We propose a system for three-dimensional (3D) sensing and identification of biological micro-organisms. This system consists of a microfluidic device along with a digital holographic microscope and relevant statistical recognition algorithms.

Three-dimensional optical microscopy using axially distributed image sensing.

We propose three-dimensional (3D) optical microscopy using axially distributed image sensing. In the proposed method, the micro-objects are optically magnified and their axially distributed images are recorded by moving the image sensor along a common optical axis. The 3D volumetric images are generated from the recorded axial image set using a computational reconstruction algorithm based on ray backprojection.

Simple correction method of distorted elemental images using surface markers on lenslet array for computational integral imaging reconstruction.

In this paper, we propose a simple correction method of distorted elemental images for computational integral imaging reconstruction (CIIR) method by using surface markers on lenslet array. The position information of surface markers is extracted from distorted elemental images with geometric misalignments such as skew, rotation and so on. Then the elemental images can be corrected simply when applying linear transformation calculated from the extracted positions.

Signal model and granular-noise analysis of computational image reconstruction for curved integral imaging systems.

In this paper, we propose an improved analysis on the signal property of curved computational integral imaging reconstruction (C-CIIR). In the proposed model and analysis, we explain a general analysis of computational integral imaging by introducing a curvature effect that is obtained by the additional use of a large-aperture (LA) lens. Based on the proposed signal model in C-CIIR, we analyze the characteristics of the granular noise (GN) and conduct preliminary experiments to show the feasibility of our model.

Resolution-enhanced three-dimensional image reconstruction by use of smart pixel mapping in computational integral imaging.

Computational integral imaging method can digitally provide a series of plane images of three-dimensional (3D) objects. However, the resolution of 3D reconstructed images is dramatically degraded as the distance from the lenslet array increases. In this paper, to overcome this problem, we propose a novel computational integral imaging reconstruction (CIIR) method based on smart pixel mapping (SPM).

Occlusion removal method of partially occluded 3D object using sub-image block matching in computational integral imaging.

In this paper, we propose an occlusion removal method using sub-image block matching for improved recognition of partially occluded 3D objects in computational integral imaging (CII). When 3D plane images are reconstructed in CII, occlusion degrades the resolution of reconstructed images. To overcome this problem, we apply the sub-image transform to elemental image array (EIA) and these sub-images are employed using block matching method for depth estimation.

Depth extraction of three-dimensional objects in space by the computational integral imaging reconstruction technique.

A novel approach to extract the depth data of 3D objects in space by using the computational integral imaging reconstruction (CIIR) technique is proposed. With elemental images of 3D objects captured by the CCD camera through a pinhole array, depth-dependent object images can be reconstructed on the output plane by the CIIR technique. Only the images reconstructed on the output planes where 3D objects were located are clearly focused; so the depth data of 3D objects in space can be extracted by discriminating these focused output images from the others by using an image separation technique.

Scale-variant magnification for computational integral imaging and its application to 3D object correlator.

In this paper, we present a novel volumetric computational reconstruction (VCR) method for improved 3D object correlator. Basically, VCR consists of magnification and superposition. This paper presents new scale-variant magnification as a technique for VCR.

Curved computational integral imaging reconstruction technique for resolution-enhanced display of three-dimensional object images.

A novel curved computational integral imaging reconstruction (C-CIIR) technique for the virtually curved integral imaging (VCII) system is proposed, and its performances are analyzed. In the C-CIIR model, an additional virtual large-aperture lens is included to provide a multidirectional curving effect in the reconstruction process, and its effect is analyzed in detail by using the ABCD matrix. With this method, resolution-enhanced 3D object images can be computationally reconstructed from the picked-up elemental images of the VCII system.

Improved analysis on the signal property of computational integral imaging system.

In this paper, we introduce an improved signal analysis of the computational integral imaging (CII) system having a pickup process of three-dimensional object and a volumetric computational reconstruction (VCR) process. We propose a signal model for the CII system. From the signal model and its analysis, we can define a granular noise caused by the non-uniform overlapping.

Image quality enhancement in 3D computational integral imaging by use of interpolation methods.

In this paper, we propose a computational integral imaging reconstruction (CIIR) method by use of image interpolation algorithms to improve the visual quality of 3D reconstructed images. We investigate the characteristics of the conventional CIIR method along the distance between lenslet and objects. What we observe is that the visual quality of reconstructed images is periodically degraded.

Multidirectional curved integral imaging with large depth by additional use of a large-aperture lens.

We propose a curved integral imaging system with large depth achieved by the additional use of a large-aperture lens in a conventional large-depth integral imaging system. The additional large-aperture lens provides a multidirectional curvature effect and improves the viewing angle. The proposed system has a simple structure due to the use of well-fabricated, unmodified flat devices.

Magnification of 3D reconstructed images in integral imaging using an intermediate-view reconstruction technique.

A new integral imaging (II) system that can magnify 3D reconstructed images by employing an intermediate-view reconstruction technique (IVRT) is proposed in which the number of the elemental images obtained from a one-step pickup process can be computationally increased by use of an IVRT without mechanical movement and a long multistep pickup process. To show the feasibility of the proposed II system, some optical experiments on the magnification of 3D reconstructed images with a real 3D object have been carried out and results are presented.

Effect of illumination in an integral imaging system with large depth of focus.

We present the characteristics of integral imaging systems with large depth of focus (DOF) by use of two kinds of illumination: plane illumination and diffusing illumination. For each system, we perform ray analysis based on ray optics. To check the visual quality through optical experiments, we use an average image of observed images picked up at various positions within a large DOF.