Lossless Compression of Binary Holograms with Context Models and Adaptive Segmentation
 
Lossless Compression of Binary Holograms with Context Models and Adaptive Segmentation 
 
 
Abstract 

We demonstrate how applying adaptive segmentation on context modelling schemes can be used for lossless compression of binary holograms. A tree-based scheme using Bayesian inference is introduced to improve the compression rate over fixed sized models.