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.     

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.     

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.     

Continuous imaging space in three-dimensional integral imaging

We report an integral imaging method with continuous imaging space. This method simultaneously reconstructs real and virtual images in the virtual mode, with a minimum gap that separates the entire imaging space into real and virtual space. Experimental results show that the gap is reduced to 45% of that in a conventional integral imaging system with the same parameters.     

Three-dimensional recognition of occluded objects by using computational integral imaging

We have proposed a method to recognize partially occluded three-dimensional (3D) objects by using 3D volumetric reconstruction integral imaging (II). An II system captures multiple perspectives of occluded objects by using a microlens array. The reconstruction of the occluded 3D scene and target recognition are done digitally to reduce the effects of the occlusion. To verify system performance, we have implemented an optimum filter for object recognition. Both two-dimensional (2D) images and 3D II volumetric reconstructed images are considered. The correlation results of occluded 3D images for volumetric reconstruction show substantial improvements compared with those for conventional 2D imaging of occluded images.     

Modified computational integral imaging-based double image encryption using fractional Fourier transform

In this paper, we propose an image encryption technique to simultaneously encrypt double or multiple images into one encrypted image using computational integral imaging (CII) and fractional Fourier transform (FrFT). In the encryption, each of the input plane images are located at different positions along a pickup plane, and simultaneously recorded in the form of an elemental image array (EIA) through a lenslet array. The recorded EIA to be encrypted is multiplied by FrFT with two different fractional orders. In order to mitigate the drawbacks of occlusion noise in computational integral imaging reconstruction (CIIR), the plane images can be reconstructed using a modified CIIR technique. To further improve the solution of the reconstructed plane images, a block matching algorithm is also introduced. Numerical simulation results verify the feasibility and effectiveness of the proposed method.     

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.     

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.     

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.     

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.     

Three-dimensional photon counting integral imaging using moving array lens technique

In this Letter, we present three-dimensional (3D) photon counting integral imaging using the moving array-lens technique (MALT) to improve the visualization of a reconstructed 3D scene. In 3D scene reconstruction of photon counting integral imaging, various techniques such as maximum likelihood estimation may be used. However, the visual quality depends on the number of scene photons or detector pixels activated by photons. We show that MALT may improve the viewing resolution of integral imaging for reconstructed 3D scene under photon-starved conditions.     

Three-dimensional image authentication using binarized images in double random phase integral imaging

We proposed a three-dimensional(3D) image authentication method using binarized phase images in double random phase integral imaging(InI). Two-dimensional(2D) element images obtained from InI are encoded using a double random phase encryption(DRPE) algorithm. Only part of the phase information is used in the proposed method rather than using all of the amplitude and phase information, which can make the final data sparse and beneficial to data compression, storage, and transmission. Experimental results verified the method and successfully proved the developed 3D authentication process using a nonlinear cross correlation method.     

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.     

3D image reconstruction with controllable spatial filtering based on correlation of multiple periodic functions in computational integral imaging

We propose a novel method of slice image reconstruction with controllable spatial filtering by using the correlation of periodic delta-function arrays(PDFAs) with elemental images in computational integral imaging. The multiple PDFAs, whose spatial periods correspond to object's depths with the elemental image array(EIA), can generate a set of spatially filtered EIAs for multiple object depths compared with the conventional method for the depth of a single object. We analyze a controllable spatial filtering effect by the proposed method.To show the feasibility of the proposed method, we carry out preliminary experiments for multiple objects and present the results.     

Information capacity gain by time-division multiplexing in three-dimensional integral imaging

We evaluate improvements in information capacity gained by use of time-division multiplexing (TDM) in three-dimensional integral imaging (II) systems. This analysis supports the motivation for two TDM methods in II [Opt. Lett. 27, 324 (2002); 1144 (2002)] that we previously developed.     

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.     

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.     

Selective edge enhancement in three-dimensional vortex imaging with incoherent light

We demonstrate a new imaging method enabling a selective edge contrast enhancement of three-dimensional amplitude objects with spatially incoherent light. The imaging process is achieved in a spiral modification of Fresnel incoherent correlation holography and uses a vortex impulse response function. The correlation recordings of the object are acquired in a one-way interferometer with the wavefront division carried out by a spatial light modulator. Two different methods based on applying a helical reference wave in the hologram recording and a digital spiral phase modulation in image reconstruction are proposed for edge enhancement of amplitude objects. Results of both isotropic and anisotropic spiral imaging are demonstrated in experiments using an LED as an incoherent source of light.     

Phase-only hologram generation based on integral imaging and its enhancement in depth resolution

We introduce a phase-only hologram generation method based on an integral imaging,and propose an enhancement method in representable depth interval.The computational integral imaging reconstruction method is modified based on optical flow to obtain depth-slice images for the focused objects only.A phaseonly hologram for multiple plane images is generated using the iterative Fresnel transform algorithm.In addition,a division method in hologram plane is proposed for enhancement in the representable minimum depth interval.     

Preoperative fast MRI of brain tumors using three-dimensional segmented echo planar imaging compared to three-dimensional gradient echo technique

The purpose of this study was to compare the diagnostic efficacy of a newly developed T(1)-weighted three-dimensional segmented echo planar imaging (3D EPI) sequence versus a conventional T(1)-weighted three dimensional spoiled gradient echo (3D GRE) sequence in the evaluation of brain tumors. Forty-four patients with cerebral tumors and infections were examined on a 1.0 T MR unit with 23 mT/m gradient strength. The total scan time for the T(1) 3D EPI sequence was 2 min 12 s, and for a conventional 3D GRE sequence it was 4 min 59 s. Both sequences were performed after administration of a contrast agent. The images were analyzed by three radiologists. Image assessment criteria included lesion conspicuity, contrast between different types of normal tissue, and image artifacts. In addition, signal-to-noise and contrast-to-noise-ratio (C/N) were calculated. The gray-white differentiation and C/N ratio of 3D EPI were found to be inferior to conventional 3D GRE images, but the difference was not statistically significant. In the qualitative comparison, lesion detection and conspicuity of 3D EPI images and conventional 3D GRE images were similar, but a tow-fold reduction of the scanning time was obtained. With the 3D EPI technique, a 50% scan time reduction could be achieved with acceptable image quality compared to conventional 3D GRE. Thus, the 3D EPI technique could replace conventional 3D GRE in the preoperative imaging of brain.