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Improved resolution 3D object reconstruction using computational integral imaging with time multiplexing
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AI
DOI：10.1364/OPEX.12.004579.png)
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摘要
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In the computational three-dimensional (3D) volumetric reconstruction integral imaging (II) system, volume pixels of the scene are reconstructed by superimposing the inversely mapped elemental images through a computationally simulated optical reconstruction process according to ray optics. Close placement of a 3D object to the lenslet array in the pickup process may result in significant variation in intensity between the adjacent pixels of the reconstructed image, degrading the quality of the image. The intensity differences result from the different number of the superimposed elemental images used for reconstructing the corresponding pixels. In this paper, we propose improvements of the reconstructed image quality in two ways using 1) normalized computational 3D volumetric reconstruction II, and 2) hybrid moving lenslet array technique ( MALT). To reduce the intensity irregularities between the pixels, we normalize the intensities of the reconstructed image pixels by the overlapping numbers of the inversely mapped elemental images. To capture the elemental image sets for the MALT process, a stationary 3D object pickup process is performed repeatedly at various locations of the pickup lenslet array's focal plane, which is perpendicular to the optical axis. With MALT, we are able to enhance the quality of the reconstructed images by increasing the sampling rate. We present experimental results of volume pixel reconstruction to test and verify the performance of the proposed reconstruction algorithm. We have shown that substantial improvement in the visual quality of the 3D reconstruction is obtained using the proposed technique. (C) 2004 Optical Society of America.
Keyword:
LIMITATION
DESIGN
期刊
IF:
3.3
论文数:
6.1W
被引数:
14.3W
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