A companding approach for nonuniform quantization of digital holograms of three-dimensional objects

We apply two novel nonuniform quantization techniques to digital holograms of three-dimensional real-world objects. Our companding approach, combines the efficiency of uniform quantization with the improved performance of nonuniform quantization. We show that the performance of companding techniques can be comparable with k-means clustering and a competitive neural network, while only requiring a single-pass processing step. The quantized holographic pixels are coded using lossless techniques for the calculation of compression ratio.