3D image reconstruction with a controllable overlapping number of elemental images in computational integral imaging

In this Letter, we propose a three-dimensional(3D) image reconstruction method with a controllable overlapping number of elemental images in computational integral imaging. The proposed method can control the overlapping number of pixels coming from the elemental images by using the subpixel distance based on ray optics between a 3D object and an image sensor. The use of a controllable overlapping number enables us to provide an improved 3D image visualization by controlling the inter-pixel interference within the reconstructed pixels.To find the optimal overlapping number, we simulate the pickup and reconstruction processes and utilize the numerical reconstruction results using a peak signal-to-noise ratio(PSNR) metric. To demonstrate the feasibility of our work in optical experiments, we carry out the preliminary experiments and present the results.     

基于立体像素匹配的图像重构技术研究

为了解决目前全景成像技术中分辨率低的问题,提出了一种新的基于3D场景立体像素光线映射的全景图像计算机重构技术.在全景成像技术中,3D场景的每个立体像素点经全景成像系统的编码系统分别映射在一定区域的多个体元素图像的不同像素点上.在计算机重构全景图像时,根据逆光学路径原理,提出了从立体像素映射到的体元素图像区域中提取对应立体像素的多个2D像素点来重构全景图像,使重构的全景图像最大分辨率可达到传统成像方法图像分辨率的N倍（N为映射区域面积）.提出的立体像素的匹配技术大大提高了重构的计算机全景图像分辨率.     

Three-dimensional free view reconstruction in axially distributed image sensing

In this Letter, we propose a three-dimensional(3D) free view reconstruction technique in axially distributed image sensing(ADS). In typical integral imaging, free view reconstructed images can be obtained by tilting all elemental images or tilting the reconstruction plane due to large lateral perspectives for 3D objects. In conventional ADS, the reconstructed images at only a front view can be generated since the sensor is moved along with its optical axis so that it has small lateral perspectives for 3D objects. However, the reconstructed 3D images at any viewing point may be obtained because the virtual viewing camera may capture these slightly different perspectives for 3D objects. Therefore, in this Letter, we employ the virtual viewing camera to visualize the 3D images at the arbitrary viewing point. To support our proposed method, we show the experimental results.     

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. The proposed method is applied to partially occluded object visualization. Optical experiments are performed to verify the approach.     

Three-dimensional polarimetric integral imaging

A three-dimensional (3D) polarimetric image sensing and display technique based on integral imaging is proposed. Three-dimensional polarization distribution of reflected light from a 3D object can be measured as elemental image arrays by a rotating linear polarizer. After the measurement of the polarization of the 3D object, the 3D polarimetric object can be reconstructed optically by displaying the polarization-selected elemental images in spatial light modulators with two quarter-wave plates. Experimental demonstration of 3D polarimetric imaging of a 3D object attached to two orthogonal linear polarizers is presented. To the best of our knowledge, this is the first report on 3D polarimetric sensing imaging and 3D optical reconstruction by integral imaging.     

Axially distributed sensing for three-dimensional imaging with unknown sensor positions

Recently, an axially distributed sensing system was proposed for three-dimensional (3D) imaging where the sensors are distributed along the optical axis. In this previously reported system, a priori knowledge of exact sensor positions was required for 3D image reconstruction. In this Letter, we present an axially distributed sensing with unknown sensor positions along the optical axis. In this system, only the relative positions of two sensors are needed, whereas all other sensor positions are assumed unknown. Experiments are presented to illustrate the feasibility of the proposed system and illustrate the visual quality of reconstructed 3D images by using the proposed calibrated sensor positions. To the best of our knowledge, this is the first report on axially distributed sensing with unknown sensor positions.     

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. Preliminary experimental results are presented. To the best of our knowledge, this is the first report on 3D optical microscopy using axially distributed sensing.     

Three-dimensional visualization of objects in scattering medium using integral imaging and spectral analysis

This paper presents a three-dimensional visualization method of 3D objects in a scattering medium. The proposed method employs integral imaging and spectral analysis to improve the visual quality of 3D images. The images observed from 3D objects in the scattering medium such as turbid water suffer from image degradation due to scattering. The main reason is that the observed image signal is very weak compared with the scattering signal. Common image enhancement techniques including histogram equalization and contrast enhancement works improperly to overcome the problem. Thus, integral imaging that enables to integrate the weak signals from multiple images was discussed to improve image quality. In this paper, we apply spectral analysis to an integral imaging system such as the computational integral imaging reconstruction. Also, we introduce a signal model with a visibility parameter to analyze the scattering signal. The proposed method based on spectral analysis efficiently estimates the original signal and it is applied to elemental images. The visibility-enhanced elemental images are then used to reconstruct 3D images using a computational integral imaging reconstruction algorithm. To evaluate the proposed method, we perform the optical experiments for 3D objects in turbid water. The experimental results indicate that the proposed method outperforms the existing methods.     

利用匹配区域的纹理特征改善重构三维图像的视觉质量

研究了计算机重构三维图像时分辨率低的问题,提出一种改善3D计算机全景重构图像的视觉质量的方法,该方法利用3D空间的物体部分在每个元素图像中形成的匹配区域的纹理特征,从两个相邻的元素图像中的匹配区域提取出多个像素,经过加权计算重构出相应的图像区域.该方法与传统的计算机重构方法相比,提高了图像分辨率,同时也消除了从每个元素图像中提取多个像素直接重构图像时存在的"像素块"效应,改善了重构图像的视觉质量.     

Single-shot subpixel response measurement with an aperture array pixel mask

We first point out that the subpixel response function is another kernel function in digital imaging. Then we show that the subpixel response function of CMOS imaging sensor pixels can be measured with an aperture array pixel mask in a single-shot image capture. Our technique permits high-resolution subpixel response function measurement of imaging pixels for superresolution imaging applications.     

基于视差信息的三维图像的计算机重构*

为了解决全景成像技术中观察者位于观察区域之外看到的图像会存在失真的问题,提出了一种基于视差信息的计算机重构3D视图技术.利用3D场景中的物体点经过不同微透镜在元素图像中记录的视差信息,根据光学路径分析,对重构视图中的失真部分用其它元素图像中存在的同一物体点的匹配像素进行替代,从而得到无失真的3D视图.该技术能够在更宽的观察区域内产生3D图像.     

A compressed sensing approach for enhancing infrared imaging resolution

This paper presents a novel approach for improving infrared imaging resolution by the use of Compressed Sensing (CS). Instead of sensing raw pixel data, the image sensor measures the compressed samples of the observed image through a coded aperture mask placed on the focal plane of the optical system, and then the image reconstruction can be conducted from these samples using an optimal algorithm. The resolution is determined by the size of the coded aperture mask other than that of the focal plane array (FPA). The attainable quality of the reconstructed image strongly depends on the choice of the coded aperture mode. Based on the framework of CS, we carefully design an optimum mask pattern and use a multiplexing scheme to achieve multiple samples. The gradient projection for sparse reconstruction (GPSR) algorithm is employed to recover the image. The mask radiation effect is discussed by theoretical analyses and numerical simulations. Experimental results are presented to show that the proposed method enhances infrared imaging resolution significantly and ensures imaging quality.     

基于视差信息的三维图像的计算机重构

为了解决全景成像技术中观察者位于观察区域之外看到的图像会存在失真的问题,提出了一种基于视差信息的计算机重构3D视图技术.利用3D场景中的物体点经过不同微透镜在元素图像中记录的视差信息,根据光学路径分析,对重构视图中的失真部分用其它元素图像中存在的同一物体点的匹配像素进行替代,从而得到无失真的3D视图.该技术能够在更宽的观察区域内产生3D图像.     

Modified smart pixel mapping method for displaying orthoscopic 3D images in integral imaging

In this paper, we propose a modified smart pixel mapping (MSPM) method for displaying orthoscopic three-dimensional (3D) images with a function of depth control in integral imaging system. In the proposed MSPM, the depth-converted elemental image array (EIA) is obtained through the pixel mapping process and the image interpolation technique. The proposed method gives us the depth conversion at distances different from the position of 3D object and provides various types of EIAs using only an original EIA for orthoscopic images. To show the usefulness of the proposed method, we carry out the preliminary experiments and present the experimental results.     

Directional variation adaptive image resolution enhancement

The goal of image interpolation is to produce a high-resolution image from its low-resolution counterpart. It has significant applications in video sensor network, where the resolution of images usually needs to be enhanced at the end user due to the limited transmission bandwidth. The key challenge of image interpolation is to preserve the edge structure of the image. In this paper, a new image interpolation approach is proposed to adaptively adjust the interpolation according to the directional variations of images. More specifically, at each pixel position to be interpolated, its neighboring pixels are projected onto 1D direction according to a number of proposed patterns. Then the direction, of which the variation is smallest, is chosen as the direction to perform image interpolation. Experimental results are provided to show that the proposed approach outperforms several conventional edge-directed image interpolation algorithms.     

A novel three-dimensional digital watermarking scheme basing on integral imaging

A novel integral imaging-based three-dimensional (3D) digital watermarking scheme is presented. In the proposed method, an elemental image array (EIA) obtained by recording the rays coming from a 3D object through a pinhole array in the integral imaging system is employed as a new 3D watermark. The EIA is composed of a number of small elemental images having their own perspectives of a 3D object, and from this recorded EIA various depth-dependent 3D object images can be reconstructed by using the computational integral imaging reconstruction (CIIR) technique. This 3D property of the EIA watermark can make a robust reconstruction of the watermark image available even though there are some data losses in the embedded watermark by attacks. To show the robustness of the proposed scheme against attacks, some experiments are carried out and the results are discussed.     

Orthoscopic integral imaging display by use of the computational method based on lenslet model

In this paper, we propose a computational depth conversion method based on the lenslet model to display the orthoscopic 3D images in 3D integral imaging display. The proposed method permits the synthesis of elemental images for the orthoscopic 3D images at any arbitrary position without any restrictions and requires no additional procedure during the depth conversion process. Due to the lenslet model involved in the depth conversion procedure, the proposed method can broaden the flexibility of 3D image reconstruction in the integral imaging display system. We carry out the preliminary experiments to prove the feasibility of the proposed method. The experimental results reveal that the proposed method is an effective depth conversion method that allows the reconstruction of the orthoscopic 3D images at any arbitrary position.     

基于Kinect传感器多深度图像融合的物体三维重建

物体的三维重建技术一直是计算机视觉领域研究的热点问题,提出一种利用Kinect传感器获取的深度图像实现多幅深度图像融合完成物体三维重建的方法。在图像空间中对深度图像进行三角化,然后在尺度空间中融合所有三角化的深度图像构建分层有向距离场（hierarchical signed distance field）,对距离场中所有的体素应用整体Delaunay三角剖分算法产生一个涵盖所有体素的凸包,并利用Marching Tetrahedra算法构造等值面,完成物体表面重建。实验结果表明,该方法利用Kinect传感器采集的不同方向37幅分辨率为640480的深度图像完成目标物体的三维重建,仅需要48 s,并且得到非常精细的重建效果。     

Resolution-enhanced 3D image correlator using computationally reconstructed integral images

In this paper, a novel resolution-enhanced three-dimensional (3D) image correlator using the computationally reconstructed integral images is proposed in order to extract target object’s 3D location data in a scene. Elemental images of the reference and target objects are picked up by lenslet arrays and using these elemental images, reference and target plane images are reconstructed on the output plane by means of a modified computational integral imaging reconstruction technique. Then, through cross-correlations between the reconstructed reference and the target plane images, 3D location data of the target object can be extracted from the correlation outputs. With the purpose of showing the feasibility of the proposed method, some computational and optical experiments on the target objects in space are carried out and the results are presented.     

Regeneration of elemental images in integral imaging for occluded objects using a plenoptic camera

In this Letter, we propose an elemental image regeneration method of three-dimensional(3D) integral imaging for occluded objects using a plenoptic camera. In conventional occlusion removal techniques, the information of the occlusion layers may be lost. Thus, elemental images have cracked parts, so the visual quality of the reconstructed 3D image is degraded. However, these cracked parts can be interpolated from adjacent elemental images. Therefore, in this Letter, we try to improve the visual quality of reconstructed 3D images by interpolating and regenerating virtual elemental images with adjacent elemental images after removing the occlusion layers. To prove our proposed method, we carry out optical experiments and calculate performance metrics such as the mean square error(MSE) and the peak signal-to-noise ratio(PSNR).