Algorithm

Chuck suggested merging algorithm for photons split between pixels as follows.

Original array

This algorithm consumes (float) calibrated data expressed in terms of number of photons. For test purpose use image shape=(50,50) random standard normal distribution with sigma=10

Split array for integer and float

Input array with float number of photons per pixel is split for two

• floor of input (uint) and
• difference between input and previuos uint array - (float) fractional array [0,1).

Pixels with intensity below zero and masked are set to 0 (photon) in both arrays.

Find local maximums

Fractional float array is used to search for local maximums in the rank=1 cross region (among 4 pixels closest to the central):

Color coding:

• (0) dark blue - not maximum
• (1) bright blue - local maximum of rank 1 in the row
• (2) yellow - local maximum of rank 1 in the column
• (3) red - local maximum of rank 1 in the cross region

Find couples of connected pixels

Local maximum (with threshold>0.25) is connected to the nearest (not yet used) neighbor with maximal intensity:

Different colors show pairs of connected pixels

Merge coupled pixels

Each pair total intensity (with threshold 0.75) is used to count additional integer number of photons.

Sum arrays

Add array with merged photons with array of integer number of photons:

Implementation

• C++ algorithm is implemented in ImgAlgos::AlgImgPros::mapOfPhotonNumbersV1 for 2-d arrays only
• Boost-python wrapper is in  ImgAlgos.pyImgAlgos.cpp
• Pure python wrapper ImgAlgos.PyAlgos.py - supports 2-d and n-d arrays.

Presentation in the Detector package

• Reference to ImgAlgos.PyAlgos.photon is in AlgoAccess.py

• AreaDetector.py has photon(...) method