Yongri Piao

Occlusion-removed scheme using depth-reversed method in computational integral imaging

We present a computational scheme for removing an occlusion in a partially occluded, far object in a computational integral imaging (CII) system. In order to obtain the high resolution elemental image array (EIA) with enhanced information of the occluded image for better applying block matching, a smart pixel mapping process and a subimage transform process are adopted. Based on depth maps produced between adjacent subimages, we acquire the expected EIA without occlusion information. Theoretical analysis of the proposed scheme is given. To show the effectiveness of the proposed scheme, we carry out some experiments. As demonstrated using test images, experimental results show that the proposed scheme outperforms Shin’s scheme and the CII scheme under the same situations.

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. Preliminary experimental results are presented to illustrate the feasibility of the proposed system. To the best of our knowledge, this is the first report on 3D imaging and visualization using ODIS.

Resolution-enhanced reconstruction of far 3-D objects by using a direct pixel mapping method in computational curving-effective integral imaging

In this paper, we propose a novel approach for resolution-enhanced computational reconstruction of far 3-D objects by employing a direct pixel mapping (DPM) method in the curving-effective integral imaging (CEII) system. In this method, by using the DPM method, an elemental image array (EIA) picked up from a far 3-D object can be computationally transformed into a new EIA, which virtually looks like the EIA picked up from a near object. Therefore, with this newly transformed EIA a much better resolution-enhanced object image can be reconstructed in the CEII system. Good experimental results confirmed the feasibility of the proposed method.

Computational Depth Conversion of Reconstructed Three-Dimensional Object Images in Curving-Effective Integral Imaging System

In this paper, we propose a novel method for the computational depth conversion of reconstructed three-dimensional (3D) object images by a direct pixel mapping (DPM) method in curving-effective integral imaging (CEII) system. In this proposed method, the elemental image array (EIA) of the 3D object is picked up in the CEII system, and then, this EIA is computationally transformed into a depth-converted EIA by the DPM method. Thus, in contrast to a conventional method, with this proposed method, a real and orthoscopic 3D object image with a wide viewing angle can be provided to observers without any data loss in the depth conversion process. Good experimental results finally confirmed the feasibility of the proposed method.

Distortion-free wide-angle 3D imaging and visualization using off-axially distributed image sensing

We propose a new off-axially distributed image sensing (ODIS) using a wide-angle lens for reconstructing distortion-free wide-angle slice images computationally. In the proposed system, the wide-angle image sensor captures a wide-angle 3D scene, and thus the collected information of the 3D objects is severely distorted. To correct this distortion, we introduce a new correction process involving a wide-angle lens to the computational reconstruction in ODIS. This enables us to reconstruct distortion-free, wide-angle slice images for visualization of 3D objects. Experimental results are carried out to verify the proposed method. To the best of our knowledge, this is the first time the use of a wide-angle lens in a multiple-perspective 3D imaging system is described.

Accelerated Generation Algorithm for an Elemental Image Array Using Depth Information in Computational Integral Imaging

In this paper, an accelerated generation algorithm to effectively generate an elemental image array in computational integral imaging system is proposed. In the proposed method, the depth information of 3D object is extracted from the images picked up by a stereo camera or depth camera. Then, the elemental image array can be generated by using the proposed accelerated generation algorithm with the depth information of 3D object. The resultant 3D image generated by the proposed accelerated generation algorithm was compared with that the conventional direct algorithm for verifying the efficiency of the proposed method. From the experimental results, the accuracy of elemental image generated by the proposed method could be confirmed.

3D Image Encryption Using Integral Imaging Scheme and MLCA Technology

A new 3D image encryption method using integral imaging technology and maximum length cellular automata (MLCA) is proposed in this paper. First, an elemental image (EI) is generated by the integral imaging pickup process. The Wolfram rule is then selected and the state transition matrix, T, is created by MLCA. A random number matrix (RNM) is generated according to the MLCA rule. The generated EI and RNM are compared and pixel values are transitioned. Finally, a basis image is generated by another MLCA rule. The basis image is applied by performing a logic bit exclusive-OR (XOR) operation on the final encrypted image. This method changes the basic image information. Using pixel values to visualize image data gives better encryption results than the previous method. The robustness of the encryption method for lost data, including added noise or cropping attacks, was analyzed and the results of encryption method safety test experiments are presented using histograms.

Visibility-enhanced reconstruction of three-dimensional objects under a heavily scattering medium through combined use of intermediate view reconstruction, multipixel extraction, and histogram equalization methods in the conventional integral imaging system

In this paper, we propose an effective approach for reconstructing visibility-enhanced three-dimensional (3D) objects under the heavily scattering medium of dense fog in the conventional integral imaging system through the combined use of the intermediate view reconstruction (IVR), multipixel extraction (MPE), and histogram equalization (HE) methods. In the proposed system, the limited number of elemental images (EIs) picked up from the 3D objects under the dense fog is increased by as many as required by using the IVR technique. The increased number of EIs is transformed into the subimages (SIs) in which the resolution of the transformed SIs has been also improved as much as possible with the MPE method. Subsequently, by using the HE algorithm, the histogram of the resolution-enhanced SIs is uniformly redistributed over the entire range of discrete pixel levels of the image in a way that the subimage contrast can be much enhanced. Then, these equalized SIs are converted back into the newly modified EIs, and consequently a visibility-enhanced 3D object image can be reconstructed. Successful experimental results with the test object confirmed the feasibility of the proposed method.

Resolution Enhanced Computational Integral Imaging Reconstruction by Using Boundary Folding Mirrors

In this paper, we present a resolution-enhanced computational integral imaging reconstruction method by using boundary folding mirrors. In the proposed method, to improve the resolution of the computationally reconstructed 3D images, the direct and reflected light information of the 3D objects through a lenslet array with boundary folding mirrors is recorded as a combined elemental image array. Then, the ray tracing method is employed to synthesize the regular elemental image array by using a combined elemental image array. From the experimental results, we can verify that the proposed method can improve the visual quality of the computationally reconstructed 3D images.

Depth-of-field extension in integral imaging using multi-focus elemental images

In integral imaging, one of the main challenges is the limited depth of field (DOF), which is mainly caused by the short focal length of the microlenses. In this paper, we propose a method to extend the DOF of a synthetic aperture integral imaging (SAII) system by realizing the image fusion method on the multi-focus elemental images with different perspectives. In the proposed system, the contour-based object extraction method combined with size correction is developed to solve size inconsistency of the objects in the misaligned elemental images. The all-in-focus elemental images (EIs) combining selected features of multi-focus elemental images are then obtained by the block-based image fusion method. In the last step, the reconstructed images with the extended DOF can be generated based on the all-in-focus EIs in the SAII system. Experimental results are presented to demonstrate the feasibility of the proposed system.