KEYWORDS: Computer generated holography, Video, Holograms, 3D image processing, Fringe analysis, Video acceleration, 3D displays, Data processing, Video processing, Motion estimation
A new approach for fast generation of computer-generated-holograms (CGHs) by combined use of the N-LUT method and block matching motion compensation technique is proposed. Here, we apply block matching-based motion compensation algorithm to N-LUT-based CGH generation method by which a higher similarity between adjacent frames can be obtained. In the proposed method, the input video images are divided into blocks of fixed size and the CGHs of every block in reference frames are pre-calculated with the N-LUT method. The motion vectors of every block in the reference frame are extracted between reference frame and current frame, and a compensated frame image can be obtained by shifting every block’s position according to the motion vectors. Through this process, 3-D objects data to be calculated for its video holograms are dramatically reduced leading to the greater reduction of the calculation time compared with the conventional temporal redundancy-based N-LUT (TR-N-LUT) method. The experiments have found that the average number of calculated object points for one frame and the average calculation time for one object point of the proposed method are reduced by 30.05% and 21.23% respectively compared to those with the conventional TRNLUT method.
KEYWORDS: Computer generated holography, Video, 3D image processing, Holograms, Image segmentation, Fringe analysis, 3D video compression, Video compression, Holography, 3D displays
Thus far, various approaches to generate the computer-generated holograms (CGHs) of 3-D objects have been suggested
but, most of them have been applied to the still images, not to the video images due to their computational complexity.
Recently, a method to fast compute the CGH patterns of 3-D video images has been proposed by combined use of data
compression and novel look-up table (N-LUT) techniques. In this method, temporally redundant data of 3-D video
images are removed with the differential pulse code modulation (DPCM) algorithm and then the CGH patterns for these
compressed video images are calculated with the N-LUT method. However, as the 3-D objects move rapidly, image
differences between the video frames may increase, which results in a massive growth of calculation time of the video
holograms. Therefore, we propose a novel approach to significantly reduce the computation time of 3-D video holograms
by employing a new concept of motion-vector of the 3-D object. In the proposed method, 3-D objects are firstly
segmented from the 1st frame of the 3-D videos, and the CGH patterns for each segmented object are computed with the
N-LUT algorithm. Secondly, motion vectors between each segmented object and the corresponding objects in the
consecutive 3-D video frames are calculated. Thirdly, the CGH patterns for each segmented object are shifted with the
calculated motion vectors. Finally, all these shifted CGH patterns are added up to generate the hologram patterns of the
consecutive 3-D video frames. To confirm the feasibility of the proposed method, experiments are performed and the
results are comparatively discussed with the conventional methods in terms of the number of object points and
computation time.
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