6 April 2017 Sparsity-based fast CGH generation using layer-based approach for 3D point cloud model
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Abstract
Computer generated hologram (CGH) is becoming increasingly important for a 3-D display in various applications including virtual reality. In the CGH, holographic fringe patterns are generated by numerically calculating them on computer simulation systems. However, a heavy computational cost is required to calculate the complex amplitude on CGH plane for all points of 3D objects. This paper proposes a new fast CGH generation based on the sparsity of CGH for 3D point cloud model. The aim of the proposed method is to significantly reduce computational complexity while maintaining the quality of the holographic fringe patterns. To that end, we present a new layer-based approach for calculating the complex amplitude distribution on the CGH plane by using sparse FFT (sFFT). We observe the CGH of a layer of 3D objects is sparse so that dominant CGH is rapidly generated from a small set of signals by sFFT. Experimental results have shown that the proposed method is one order of magnitude faster than recently reported fast CGH generation.
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Hak Gu Kim, Hak Gu Kim, Hyunwook Jeong, Hyunwook Jeong, Yong Man Ro, Yong Man Ro, } "Sparsity-based fast CGH generation using layer-based approach for 3D point cloud model", Proc. SPIE 10127, Practical Holography XXXI: Materials and Applications, 101270I (6 April 2017); doi: 10.1117/12.2250523; https://doi.org/10.1117/12.2250523
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