Three-Dimensional Imaging With Multiple Degrees of Freedom Using Data Fusion

Carmona, Pedro; Pla, Filiberto; Stern, Adrian; Moon, Inkyu; Javidi, Bahram

doi:10.1109/jproc.2015.2451734

Cited by 8 publications

(3 citation statements)

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“…The principle of this technique is to record a 3D scene from multiple perspectives by using a lenslet array and a 2D recording medium, such as film [56][57] [58], since optoelectronic image sensors were not available at the time. Thanks to the rapid technological improvement in optoelectronic sensors, materials and devices, such as CCD and CMOS cameras, LC display screens, and the commercialization of computers, integral imaging has been revived in the recent decades [59][60] [61][62] [63]. There are two procedures in a typical integral imaging system for 3D information acquisition and visualization, known as the pickup and reconstruction stages, respectively.…”

Section: Principle and Recent Progress Of Integral Imagingmentioning

confidence: 99%

Multidimensional Optical Sensing and Imaging System (MOSIS): From Macroscales to Microscales

et al. 2017

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Abstract-Multidimensional optical imaging systems for information processing and visualization technologies have numerous applications in fields such as manufacturing, medical sciences, entertainment, robotics, surveillance, and defense. Among different three-dimensional (3D) imaging methods, integral imaging is a promising multiperspective sensing and display technique. Compared with other 3D imaging techniques, integral imaging can capture a scene using an incoherent light source and generate real 3D images for observation without any special viewing devices. This review paper describes passive multidimensional imaging systems combined with different integral imaging configurations. One example is the integral imaging based Multidimensional Optical Sensing and Imaging Systems (MOSIS), which can be used for 3D visualization, seeing through obscurations, material inspection, and object recognition from micro scales to long range imaging. This system utilizes many degrees of freedom such as time and space multiplexing, depth information, polarimetric, temporal, photon flux and multispectral information based on integral imaging to record and reconstruct the multidimensionally integrated scene. Image fusion may be used to integrate the multidimensional images obtained by polarimetric sensors, multispectral cameras, and various multiplexing techniques. The multidimensional images contain substantially more information compared with two-dimensional (2D) images or conventional 3D images. In addition, we present recent progress and applications of 3D integral imaging including human gesture recognition in the time domain, depth estimation, mid-wave infrared photon counting, 3D polarimetric imaging for object shape and material identification, dynamic integral imaging implemented with liquid crystal devices, and 3D endoscopy for healthcare applications.

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Section: Principle and Recent Progress Of Integral Imagingmentioning

confidence: 99%

Multidimensional Optical Sensing and Imaging System (MOSIS): From Macroscales to Microscales

et al. 2017

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“…In the pickup process of integral imaging, the researchers utilize the Bayer color filter array (CFA) to capture 3D scene. Then 3D scene can be reconstructed by the computing integral imaging (CIIR) algorithm [36][37][38][39]. With the Bayer CFA, color image information can be efficiently acquired from single sensor camera.…”

Section: Introductionmentioning

confidence: 99%

Modified integral imaging reconstruction and encryption using an improved SR reconstruction algorithm

Wang

et al. 2019

Optics and Lasers in Engineering

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We propose a monospectral image encryption method in which the multispectral color image acquisition by using heterogeneous monospectral cameras. Because the captured monospectral elemental images (EIs) belongs to grayscale image, it is means that the captured EIs can be directly encrypted by the proposed encoding method. Subsequently, the linear cellular automata (CA) and hyperchaotic encoding algorithm are employed to encrypt the captured EIs. Different from previous methods, the proposed method can directly encrypt the multispectral color information rather than having to divide into three color channels (R, G and B), thereby, the proposed method can greatly reduce the encryption calculation. MonospectralEIs encrypted by linear CA and hyper-chaotic system 2.2.1. M-sequence generated by linear CA CA can offer significant benefit over existing algorithms [33,34]. In a one-dimensional (1D), two-state, three-site neighbourhood CA, where the next state of a cell is updated according to its neighborhood, the value of each cell is 0 or 1. The value of each cells can be generated by a specified rule. The value of next state is calculated by the Boolean function with three parameters.where s i (t + 1) denotes the value of cell i at time t + 1, s i (t) denotes the value of the cell i at time t, y i−1 (t) is the the left neighboring cell value at time t, s i+1 (t) is the right neighboring cell value at time t, and F () represents the Boolean function defining a specified rule. According his theory of Wolfram, for the 2-state, 3-site CA, it has 2 8 rules. The Wolfram rules are defined from 0 to 255. Among the rules, eight Wolfram rules are linear. They are 0, 60, 90, 102, 150, 170, 204, and 240, respectively. The eight Wolfram linear rules are represented as follows:Rule 0 : s i (t + 1) = 0, Rule 60 : s i (t + 1) = s i−1 (t) ⊕ s i (t), Rule 90 : s i (t + 1) = s i−1 (t) ⊕ s i+1 (t), Rule 102 : s i (t + 1) = s i (t) ⊕ s i+1 (t), Rule 150 : s i (t + 1) = s i−1 (t) ⊕ s i (t) ⊕ s i+1 (t), Rule 170 : s i (t + 1) = s i−1 (t), Rule 204 : s i (t + 1) = s i (t), Rule 240 : s i (t + 1) = s t−1 (t).

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“…1 Also emerging in the market are multimodal sensors capable of both video imaging and 3-D lidar imaging. 6,7 2 Selecting Operating Wavelength The cost and performance of the current lidar systems can be traced to the choice of sensor architecture, based on the chosen laser transmitter and detector technologies. While use of commercially available 905-nm diodes is often attributed to its compatibility with cost-effective silicon detector technology, the large depletion depth of near-infrared optical radiation in silicon makes photodetectors manufactured using deep-submicron CMOS processes largely inefficient or slow to respond to pulsed 905-nm light.…”

Section: Introductionmentioning

confidence: 99%

Optimization of eyesafe avalanche photodiode lidar for automobile safety and autonomous navigation systems

Williams

2017

Opt. Eng

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Abstract. Newly emerging accident-reducing, driver-assistance, and autonomous-navigation technology for automobiles is based on real-time three-dimensional mapping and object detection, tracking, and classification using lidar sensors. Yet, the lack of lidar sensors suitable for meeting application requirements appreciably limits practical widespread use of lidar in trucking, public livery, consumer cars, and fleet automobiles. To address this need, a system-engineering perspective to eyesafe lidar-system design for high-level advanced driverassistance sensor systems and a design trade study including 1.5-μm spot-scanned, line-scanned, and flashlidar systems are presented. A cost-effective lidar instrument design is then proposed based on high-repetitionrate diode-pumped solid-state lasers and high-gain, low-excess-noise InGaAs avalanche photodiode receivers and focal plane arrays. Using probabilistic receiver-operating-characteristic analysis, derived from measured component performance, a compact lidar system is proposed that is capable of 220 m ranging with 5-cm accuracy, which can be readily scaled to a 360-deg field of regard.

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Three-Dimensional Imaging With Multiple Degrees of Freedom Using Data Fusion

Abstract: | This paper presents an overview of research work and some novel strategies and results on using data fusion in 3-D imaging when using multiple information sources. We ex-

Cited by 8 publications

References 106 publications

Multidimensional Optical Sensing and Imaging System (MOSIS): From Macroscales to Microscales

Multidimensional Optical Sensing and Imaging System (MOSIS): From Macroscales to Microscales

Modified integral imaging reconstruction and encryption using an improved SR reconstruction algorithm

Optimization of eyesafe avalanche photodiode lidar for automobile safety and autonomous navigation systems

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