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.     

Depth-controlled reconstruction of 3D integral image using synthesized intermediate sub-images

In this paper, we propose a method that controls the depth of the three-dimensional (3D) object existing over the depth-of-focus in integral imaging. The depth control method is performed only in a computer by synthesizing the intermediate sub-images between original sub-images obtained by transforming the captured elemental images. In the reconstruction process, we can obtain reconstructed 3D images with the better image quality within depth-of-focus than that reconstructed over the depth-of-focus. To demonstrate the feasibility of our method, optical and computational experiments are carried out and its results are presented.     

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.     

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.     

Enhanced computational integral imaging system for partially occluded 3D objects using occlusion removal technique and recursive PCA reconstruction

In this paper, we propose an enhanced computational integral imaging system by both eliminating the occlusion in the elemental images recorded from the partially occluded 3D object and recovering the entire elemental images of the 3D object. In the proposed system, we first obtain the elemental images for partially occluded object using computational integral imaging system and it is transformed to sub-images. Then we eliminate the occlusion within the sub-images by use of an occlusion removal technique. To compensate the removed part from occlusion-removed sub-images, we use a recursive application of PCA reconstruction and error compensation. Finally, we generate the entire elemental images without a loss from the newly reconstructed sub-images and perform the process of object recognition. To show the usefulness of the proposed system, we carry out the computational experiments for face recognition and its results are presented. Our experimental results show that the proposed system might improve the recognition performance dramatically.     

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.     

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.     

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.     

A 3D image encryption technique using computer-generated integral imaging and cellular automata transform

A novel three-dimensional (3D) image encryption approach by using the computer-generated integral imaging and cellular automata transform (CAT) is proposed, in which, the two-dimensional (2D) elemental image array (EIA) digitally recorded by light rays coming from the 3D image is mapped inversely through the virtual pinhole array according to the ray-tracing theory. Next, the encrypted image is generated by using the 2D CAT scrambling transform for the 2D EIA. The reconstructed process is carried out by using the modified computational integral-imaging reconstruction (CIIR) technique; the depth-dependent plane images are reconstructed on the output plane. The reconstructed 3D image quality of the proposed scheme can be greatly improved, because the proposed encryption scheme carries out in a computer which can avoid the light diffraction caused by optical device CIIR, and solves blur problem caused by CIIR by using the pixel-averaging algorithm. Furthermore, the CAT-based encryption algorithm is an error-free encryption method; CAT as an orthogonal transformation offers considerable simplicity in the calculation of the transform coefficient, that is, it can improve the quality of the reconstructed image by reducing energy loss compared with the traditional complicated transform process. To show the effectiveness of the proposed scheme, we perform computational experiments. Experimental results show that the proposed scheme outperforms conventional encryption methods.     

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.     

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.     

Efficient compression of rearranged time-multiplexed elemental image arrays in MALT-based three-dimensional integral imaging

In this paper, an approach to efficiently compress the time-multiplexed EIAs picked up from the MALT-based integral imaging system is proposed. In this method, the time-multiplexed EIAs are rearranged by collecting the elemental images occupied at the same position in each EIA to enhance the similarity among the elemental images. Then, MPEG-4 is applied to these rearranged elemental images for compression. From the experimental results, it is shown that the average correlation quality (ACQ) value representing a degree of similarity between the elemental images, and the resultant compression efficiency have been enhanced by 11.50% and 9.97%, respectively on the average for three kinds of test scenarios in the proposed method, compared to those of the conventional method. Good experimental results finally confirmed the feasibility of the proposed scheme.     

A novel three-dimensional imaging method by means of coded cameras array recording and computational reconstruction

In this paper, we propose a novel three-dimensional imaging method by which the object is captured by a coded cameras array (CCA) and computationally reconstructed as a series of longitudinal layered surface images of the object. The distribution of cameras in array, named code pattern, is crucial for reconstructed images fidelity when the correlation decoding is used. We use DIRECT global optimization algorithm to design the code patterns that possess proper imaging property. We have conducted primary experiments to verify and test the performance of the proposed method with a simple discontinuous object and a small-scale CCA including nine cameras. After certain procedures such as capturing, photograph integrating, computational reconstructing and filtering, etc., we obtain reconstructed longitudinal layered surface images of the object with higher signal-to-noise ratio. The results of experiments show that the proposed method is feasible. It is a promising method to be used in fields such as remote sensing, machine vision, etc.     

Optical display of true 3D objects in depth-priority integral imaging using an active sensor

In this paper, we propose a system combining the pickup process using an active sensor and the display process using depth-priority integral imaging (DPII) system to display true three-dimensional (3D) objects within large depth through real and virtual image fields. The active sensor provides depth map and color images of 3D objects. Using captured depth map and original color images, elemental images are computationally synthesized and displayed optically in DPII system. Proposed system provides scaling of 3D scenes for true 3D object. To show the usefulness of proposed system, we carry out the experiment for true 3D objects of three character patterns and present the experimental results.     

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.     

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.     

Enhanced compression of integral images by combined use of residual images and MPEG-4 algorithm in three-dimensional integral imaging

In this paper, we proposed a novel approach to enhance the compression rate of integral images by combined use of the residual images generated from the sub-images and the MPEG-4 algorithm. In the proposed method, elemental images picked up from a three-dimensional object are transformed into sub-images, and these sub-images are sequentially rearranged with a spiral scanning topology and the first sub-image is assigned as the reference image. Then, by sequentially computing the differences between the reference image and other consecutive sub-images, a sequence of residual images is generated. Here, the residual images together with the reference image are modeled as the consecutive video frames just like a conventional moving picture. Finally, these residual images are compressed with the MPEG-4 algorithm. Experimental results show that compression efficiency of the proposed method has been improved up to 61.56% as compared to those of the JPEG-based compression scheme and up to 151.54% as compared to those of the conventional method averagely.     

Robust image encryption by combined use of integral imaging and pixel scrambling techniques

A robust image encryption method by using the integral imaging and pixel scrambling (PS) techniques is proposed. In this method, pixels of the cover image are scrambled with the PS technique and elemental images for this scrambled image are picked up through a lenslet array. Subsequently, an encrypted image is obtained by scrambling these picked-up elemental images. Since this encrypted image has the hologram-like property of data redundancy resulted from the integral imaging scheme, while it can as well be decoded by multiple keys such as the orders of pixel scrambling and the pickup conditions of the elemental images, its security against the various attacks could be dramatically improved. Good experimental results also confirm that the proposed method could provide more enhanced robustness against data loss and Gaussian noises compared to the conventional methods.     

Compression scheme of sub-images using Karhunen-Loeve transform in three-dimensional integral imaging

In this paper, a compression scheme of sub-image-transformed elemental images using Karhunen-Loeve transform (KLT) in three-dimensional integral imaging is proposed. The proposed scheme provides improved compression efficiency by improving the similarity between elemental images using sub-image transformation. To test the proposed scheme, various elemental images of 3D objects are picked up and the compression process is carried out using KLT. From the experimental results, it is showed that the proposed compression scheme gives us an improved efficiency of 26% as compared with the conventional compression method.