Accelerated computation of computer-generated holograms of a 3-D object with N×N-point principle fringe patterns in the novel look-up table method

In this paper, we propose a new approach for accelerated computation of the computer-generated hologram (CGH) of a 3-D object by using the N×N-point principle fringe patterns (PFPs)-based novel look-up table (N-LUT) method. Using the two-dimensional (2-D) run-length encoding (RLE) algorithm, redundant data of a 3-D object are extracted in image blocks and re-grouped into a N×N-point redundancy map depending on the block size. Basing on this redundancy map, the N×N-point PFPs are calculated, from which the CGH pattern of a 3-D object can be generated. With the block-based extraction of the redundant data and the N×N-point PFPs-based computation of the CGH pattern, the object points to be calculated could be significantly reduced, which results in a great increase in the computational speed. Experimental results show that for 3×3-point PFPs, the computational speed of the proposed method has been improved by 47.72% and 20.98% compared to the conventional N-LUT and the RLE-based N-LUT methods, respectively.

► We propose new method for accelerated computation of the CGH using block redundancy. ► Redundant data are extracted and re-grouped into a N×N-point redundancy map. ► CGH is computed with redundant data and N×N-point PFPs. ► Computational speed of the proposed method has been improved by 47.72% and 20.98%.