Process Spectral RTI Images in ImageJ
Switch branches/tags
Nothing to show
Clone or download
Pull request Compare This branch is 125 commits ahead, 13 commits behind thanneken:master.
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
Guide
src/main/java/com/slu/imagej
.gitignore
LICENSE
Light_Positions-RTI-Rotation90-20170113.lp lp file Apr 26, 2018
README.md
SpectralRTI_Dataset.bash
SpectralRTI_Toolkit-0.0.9.jar
Stack_Manipulation-2.0.1.zip
bij_plugin.zip
ijp-toolkit_bin_2.1.0.zip
imglib2-2.4.0.jar
pom.xml
runtimesRTI.xlsx

README.md

SpectralRTI_Toolkit

Process Spectral RTI Images in ImageJ

The toolkit processes the data from a Spectral RTI capture session. This data includes diffuse narrowband spectral images, monochrome RTI captures from 35 or more light positions, and an accurate color image. The toolkit guides processing of the light position (lp) file, and outputs to HSH RTI, PTM, and WebRTI formats. The base color processing options are Accurate Color, Extended Spectrum, and PCA Pseudocolor. The Toolkit is intended to be usable by general users without requiring any editing of text files, command line arguments, or regular expressions. For more information about Spectral RTI see [http://palimpsest.stmarytx.edu/integrating] (http://palimpsest.stmarytx.edu/integrating).

##Version History Version 0.1 is an ImageJ Macro.

##Roadmap The major development goals are:

  1. Rewrite as Java Plugin for ImageJ2, optimize for speed
  2. Create documentation for basic users

Additional plans include:

  • More helpful error messages (check dependencies, instructions for fixing errors)

##Current Iteration

  • This fork of the project is the creation of the ImageJ2 Macro by the Walter J. Ong S.J. Center for Digitial Humanities at Saint Louis University.

  • The first pass is a strict conversion of the macro to Java, which can be packaged as a .jar file and used as an ImageJ plugin. More helpful error messages and error handling are being implemented during this first pass.

  • The second pass will look at the Java conversion and find points for speed optimization.

  • The third pass will look at the Java conversion and find points for memory and disk space optimization.

  • Throughout the coding process, code documentation will be created following the JavaDoc standard.