• Journal of information and communication convergence engineering
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• v.13 no.4
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• pp.275-279
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• 2015

There are several methods to record three dimensional (3D) information of objects such as lens array based integral imaging, synthetic aperture integral imaging (SAII), computer synthesized integral imaging (CSII), axially distributed image sensing (ADS), and axially distributed stereo image sensing (ADSS). ADSS method is capable of recording partially occluded 3D objects and reconstructing high-resolution slice plane images. In this paper, we present a computational method for depth extraction of partially occluded 3D objects using ADSS. In the proposed method, the high resolution elemental stereo image pairs are recorded by simply moving the stereo camera along the optical axis and the recorded elemental image pairs are used to reconstruct 3D slice images using the computational reconstruction algorithm. To extract depth information of partially occluded 3D object, we utilize the edge enhancement and simple block matching algorithm between two reconstructed slice image pair. To demonstrate the proposed method, we carry out the preliminary experiments and the results are presented.

• Journal of the Optical Society of Korea
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• v.18 no.4
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• pp.414-418
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• 2014

In this paper, we present a method to detect the position of a 3D object in scattering media by using the axially distributed sensing (ADS) method. Due to the scattering noise of the elemental images recorded by the ADS method, we apply a statistical image processing algorithm where the scattering elemental images are converted into scatter-reduced ones. With the scatter-reduced elemental images, we reconstruct the 3D images using the digital reconstruction algorithm based on ray back-projection. The reconstructed images are used for the position detection of a 3D object in the scattering medium. We perform the preliminary experiments and present experimental results.

• Journal of the Optical Society of Korea
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• v.17 no.5
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• pp.405-409
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• 2013

In this paper, a unifying framework to evaluate the depth resolution of axially distributed image sensing (ADS) systems under fixed resource constraints is proposed. The proposed framework enables one to evaluate the system performance as a function of system parameters such as the number of cameras, the number of pixels, pixel size, and so on. The Monte Carlo simulations are carried out to evaluate ADS system performance as a function of system parameters. To the best of our knowledge, this is the first report on quantitative analysis of ADS systems under fixed resource constraints.

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.517-522
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• 2014

In this paper we propose an axially distributed image-sensing method with a wide-angle lens to capture the wide-area scene of 3D objects. A lot of parallax information can be collected by translating the wide-angle camera along the optical axis. The recorded wide-area elemental images are calibrated using compensation of radial distortion. With these images we generate volumetric slice images using a computational reconstruction algorithm based on ray back-projection. To show the feasibility of the proposed method, we performed optical experiments for visualization of a partially occluded 3D object.