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.     

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.     

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.     

基于反向映射的元素图像生成算法

传统方法是建立从光场到显示面的映射计算生成元素图像,但会存在很多冗余映射.针对这一问题,提出沿光路逆向迭代的算法,建立从元素图像显示面到重建光场的单射,使元素图像中的每个像素只对应唯一的光场像素,这可以提高像素的匹配精度,消除深度阶跃处的空洞.所提算法的核心是以元素图像显示面每一点为始点,经过透镜的光心作射线,通过迭代...     

基于光孔阵列的集成成像三维显示方法

集成成像较小的再现深度一直都限制着集成成像的发展和应用,针对此问题提出了一种增大集成成像再现深度的方法。该方法在微透镜阵列与显示屏之间附加一个光孔阵列,利用光孔阵列限制显示屏上像素发出光线的发散角,从而有效地增大集成成像的再现深度。对集成成像的再现原理进行了深入分析,讨论了光孔直径与集成成像再现深度的关系。采用ASAP光学模拟软件对所提方法和传统方法进行了模拟对比实验,实验结果显示当光孔直径占透镜元节距的64%时,所提方法的再现深度是传统集成成像再现深度的1.5倍,实验结果验证了理论推导的正确性。     

光盘上集成的液体微透镜阵列与可重构超分辨成像

微透镜辅助显微镜实现超分辨成像观测,具有免标记、无损伤、实时、定域和环境兼容性好等优势.液体微透镜阵列具有均一、易操控的特性,可实现无复杂机械扫描与驱动的超分辨成像.然而,简单高效地精确控制成像距离是微透镜实现超分辨成像的关键技术挑战.本文利用紫外曝光技术,实现了光盘上光刻胶微孔深度的均一性.结合液体自组装技术,在微孔中填充甘油液滴,保证微透镜辅助超分辨的成像距离.在光学显微镜下实现了对226 nm光栅栅线的可重构超分辨观测与1.59倍成像放大.本文从液体微透镜的阿贝显微成像原理出发,通过理论与模拟解释了液体微透镜的成像放大与超分辨特性.由此可见,光盘上集成的液体微透镜阵列在光学纳米测量与传感等器件中展现了巨大的应用潜力.     

基于计算机视觉的非朗伯表面三维重构

基于计算机视觉的三维重构方法已经广泛应用在各行各业中。目前的三维重构研究主要针对不透明的朗伯表面,且已经比较成熟,但对非朗伯表面仍然面临诸多问题。而实际场景中的物体表面大多是非朗伯表面,因而,随着实际应用的推广,非朗伯表面的三维重构问题在计算机视觉领域越来越受到关注。虽然本现状研究不能完全涵盖针对非朗伯表面三维重构的所有方法,但它包涵了三维重构每个步骤中的各种典型方法。文中按照图像获取过程中的照明方式和重构原理对现有方法进行了分类,并逐类进行了介绍。由于不存在公共测试网络平台和带有标准视差的非朗伯表面立体图像集,因而,很难对各种算法的计算效率和匹配质量进行比较,文中主要对非朗伯表面的现有三维重构方法的原理、特点、适用范围和最新研究方向进行了介绍,对非朗伯表面三维重构的现有问题和发展前景进行了讨论。     

基于计算机视觉的非朗伯表面三维重构

基于计算机视觉的三维重构方法已经广泛应用在各行各业中。目前的三维重构研究主要针对不透明的朗伯表面,且已经比较成熟,但对非朗伯表面仍然面临诸多问题。而实际场景中的物体表面大多是非朗伯表面,因而,随着实际应用的推广,非朗伯表面的三维重构问题在计算机视觉领域越来越受到关注。虽然本现状研究不能完全涵盖针对非朗伯表面三维重构的所有方法,但它包涵了三维重构每个步骤中的各种典型方法。文中按照图像获取过程中的照明方式和重构原理对现有方法进行了分类,并逐类进行了介绍。由于不存在公共测试网络平台和带有标准视差的非朗伯表面立体图像集,因而,很难对各种算法的计算效率和匹配质量进行比较,文中主要对非朗伯表面的现有三维重构方法的原理、特点、适用范围和最新研究方向进行了介绍,对非朗伯表面三维重构的现有问题和发展前景进行了讨论。     

基于元素图像阵列采样的集成成像重构方法

高质量的集成成像系统需要采集和存储大量图像数据。提出了一种新的计算机重构方法,可以减少集成成像系统显示端在计算机重构时所需要使用的数据量。传统的计算机重构方法要利用每个元素图像,而此方法对CCD相机采集的元素图像阵列进行周期采样,仅利用被采样的元素图像即可重构出多视点图像。这种方法充分利用集成成像中邻近的元素图像中具有匹配像素的特点,将未被采样的元素图像信息由邻近的被采样的元素图像中的匹配像素替代,从而减少了重构过程中使用的数据量,这给不同性能的集成成像显示端带来很大的灵活性,降低了对存储空间和传输带宽的要求。     

Computational integral imaging reconstruction method of 3D images using pixel-to-pixel mapping and image interpolation

In this paper, we propose a novel computational integral imaging reconstruction (CIIR) method to improve the visual quality of the reconstructed images using a pixel-to-pixel mapping and an interpolation technique. Since an elemental image is magnified inversely through the corresponding pinhole and mapped on the reconstruction output plane based on pinhole-array model in the conventional CIIR method, the visual quality of reconstructed output image (ROI) degrades due to the interference problem between adjacent pixels during the superposition of the magnified elemental images. To avoid this problem, the proposed CIIR method generates dot-pattern ROIs using a pixel-to-pixel mapping and substitutes interpolated values for the empty pixels within the dot-pattern ROIs using an interpolation technique. The interpolated ROIs provides a much improved visual quality compared with the conventional method because of the exact regeneration of pixel positions sampled in the pickup process without interference between pixels. Moreover, it can enable us to reduce a computational cost by eliminating the magnification process used in the conventional CIIR. To confirm the feasibility of the proposed system, some experiments are carried out and the results are presented.     

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.     

Three-dimensional image correlator using fast computational integral imaging reconstruction method based on pixel-to-pixel mapping

In this paper, a three-dimensional (3D) image correlator using a fast computational integral imaging reconstruction (CIIR) method based on a pixel-to-pixel mapping is proposed. In order to implement the fast CIIR method, we replace the magnification process in the conventional CIIR by a pixel-to-pixel mapping. The proposed fast CIIR method reconstructs two sorts of plane images; a plane image whose quality is sufficient, and a dot pattern plane image insufficient to view. This property is very useful to enhance the performance of a CIIR-based image correlator. Thus, we apply the fast CIIR method to a CIIR-based image correlator. To show the feasibility of the proposed method, some preliminary experiments on both pattern correlation and computational cost are carried out, and the results are presented. Our experimental results indicate that the proposed image correlator is superior to the previous method in terms of both correlation performance and complexity.     

Computational integral imaging reconstruction scheme of far 3D objects by additional use of an imaging lens

In this paper, we propose a novel performance-enhanced computational integral imaging reconstruction (CIIR) scheme by additional use of an imaging lens. In the proposed scheme, elemental images can be obtained by using a simultaneous pickup scheme of far three-dimensional (3D) objects from the lenslet array in both real and virtual image fields. And additional imaging lens produces an image shift effect of 3D objects located far away from the lenslet array and improve the visual quality of reconstructed images in CIIR by overcoming limitation of pickup range in integral imaging. To show the usefulness of the proposed system, some experiments are carried out for real 3D objects and its results are presented.     

Occlusion removal technique for improved recognition of partially occluded 3D objects in computational integral imaging

In this paper, we propose an occlusion removal technique for improved recognition of 3D objects that are partially occluded in computational integral imaging (CII). In the reconstruction process of a 3D object which is partially occluded by other objects, occlusion degrades the resolution of reconstructed 3D images and thus this affects negatively the recognition of a 3D object in CII. To overcome this problem, we introduce a method to eliminate occluding objects in elemental image array (EIA) and the proposed method is applied to 3D object recognition by use of CII. To our best knowledge, this is the first time to remove occlusion in CII. In our method, we apply the elemental image to sub-image (ES) transform to EIA obtained by a pickup process and those sub-images are employed for occlusion removal. After the transformation, we correlate those sub-images with a reference sub-image to locate occluding objects and then we eliminate the objects. The inverse ES transform provides a modified EIA. Actually, the modified EIA is considered to be an EIA without the object that occludes the object to be reconstructed. This can provide a substantial gain in terms of the image quality of 3D objects and in terms of recognition performance. To verify the usefulness of the proposed technique, some experimental results are carried out and the results are presented.     

基于光线追踪的实时可交互计算生成集成成像方法

为提高计算生成集成成像实时交互显示性能和灵活性,构建与集成成像再现系统结构一致的集成光场视见模型,通过该模型为单元图像阵列中每个像素生成一条逆向追踪的光线,使用光线追踪技术并行渲染光线为单元图像阵列像素着色.实验结果表明,顶点数为565880的点云模型、面数为977308的含纹理网格模型在透镜数为22×13、视点数为175×175的4K显示系统上显示帧率40fps以上,并实现了缩放、移动、旋转、显示微调等交互功能.该方法摆脱了虚拟相机模型,降低了算法复杂度,利于实现实时交互,能够应用于基于不同分布形式透镜阵列的集成成像显示系统.     

Improved depth extraction method of 3D objects using computational integral imaging reconstruction based on multiple windowing techniques

This paper presents an improved depth extraction method of 3D objects using computational integral imaging reconstruction (CIIR) based on the multiple windowing models. The proposed method records 3D objects using the lenslet array; and it reconstructs multiple sets of slice images from multiple CIIR methods based on the different windowing models. A depth map is then extracted by a block matching algorithm among multiple set of slice images. A preliminary experiment is carried out to show the feasibility of the proposed method. Experimental results indicate the proposed method outperforms the previous method with two windowing models.