Adaptive non-iterative histogram-based hologram quantization

GAEA / GAEA-2 Spatial Light Modulators
Deep Learning / Neuronal Network Digital-/ Computer Holography/ CGH
Published on:
Authors: Ekaterina A. Savchenkova, Andrey S. Ovchinnikov, Vladislav G. Rodin, Rostislav S. Starikov, Nikolay N. Evtikhiev, Pavel A. Cheremkhin
Abstract:

Quantization is widely used for compression, storage, transmission and display of computer-generated and digital holograms. It reduces number of hologram gradations to obtain better ratio of the quality of reconstructed 2D and 3D objects to the size of holographic images or videos. This paper proposes 2 methods of non-iterative quantization of holograms: adaptive non-uniform quantization based on histogram processing with peak shift (ANHS method) and additional application of logarithmic companding (ANHSL method). They were compared with 4 methods of iterative and non-iterative quantization on holograms with sizes up to 2048 × 2048 pixels. The proposed methods showed the best reconstruction quality that is higher up to 59 % in comparison with non-iterative uniform quantization. Especially the proposed methods give higher quality at little number of hologram gradations (from 2 to 16 gradations). In comparison with the most qualitative iterative methods (Lloyd-Max and k-means) the quality is increased up to 9 %, and processing time is reduced in 10–1000 times.

Restricted Access

Publication: Optik
Issue/Year: Optik, Volume 311, 2024, 171933
DOI: 10.1016/j.ijleo.2024.171933
Link: https://doi.org/10.1016/j.ijleo.2024.171933

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