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Numcodecs implementation of photon conversion using poisson statistics

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Poisson - numcodecs implementation

This codec is designed for compressing movies with Poisson noise, which are produced by photon-limited modalities such multiphoton microscopy, radiography, and astronomy.

The codec assumes that the video is linearly encoded with a potential offset (zero_level) and that the photon_sensitivity (the average increase in intensity per photon) is known or can be accurately estimated from the data.

The codec re-quantizes the grayscale efficiently with a square-root-like transformation to equalize the noise variance across the grayscale levels: the Anscombe Transform. This results in a smaller number of unique grayscale levels and significant improvements in the compressibility of the data without sacrificing signal accuracy.

To use the codec, one must supply two pieces of information: zero_level (the input value corresponding to the absence of light) and photon_sensitivity (levels/photon).

The codec is used in Zarr as a filter prior to compression.

Zarr.

Installation

Install via pip:

pip install poisson-numcodecs

Developer installation

conda create -n poisson_numcodecs python=3.xx
conda activate poisson_numcodecs
git clone https://github.com/AllenNeuralDynamics/poisson-numcodecs.git
cd poisson-numcodecs
pip install -r requirements.txt
pip install -e .

Make sure everything works:

pip install pytest
pytest tests/

Usage

An complete example is provided in examples/workbook.ipynb

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