Skip to main content

DIRSIG 4.4.1 Final Release

By
The Final Release of DIRSIG 4.4.1 is out. This release is primarily a maintenance release to address a few bugs in the 4.4.0 release.

The following is a summary of fixes and features added in this release:
  • First release to include a Windows 64-bit version
  • Improvements to correlated deviate models used for jitter
    • The frequency spectrum can now (optionally) include the phase
  • New demonstrations
    • Indoors1
    • ExtinctionProps1
  • Blender plug-ins for DIRSIG file formats
  • Various LIDAR related improvements
    • Speedups for atmospheric backscatter returns
    • Bug fix for Linear-mode APD LIDAR detector model
  • Various GUI bug fixes and improvements
  • Improvements to streamline integration with SUMO and CityEngine
    • SUMO vehicle track import utility included on all platforms
  • Simplified shared library requirements for Solaris 9 and Solaris 10.
  • Initial MuSES support built-in for the following platforms
    • Windows 32-bit
    • Windows 64-bit
We wish to thank those early adopter users for their participation in this release. And we invite you all to give the new features in 4.4.1 a try. It is available for immediate download on myDIRSIG.

Scott, Niek and Adam
The DIRSIG Team
Labels:

Comments

Post a Comment

Popular posts from this blog

LIDAR Point Cloud Visualization

By
A common question we get asked is how to visualize the point cloud data produced by either the Linear-mode or Geiger-mode LIDAR simulations. First, you should remember that the point cloud files produced by the "APD Processor" are simple ASCII/text files. Each line is the entry for a single return or "point" in the point cloud, including the point location and some attributes that vary depending on whether you modeled a Linear-mode or Geiger-mode system. For a Linear-mode system, a point cloud file will generally look like the example below: 12.7388 -45.3612 -0.0256 5.0290 0 0 0 0 12.8169 -45.3612 -0.0264 4.8362 0 1 0 0 12.8950 -45.3612 -0.0271 4.8362 0 2 0 0 ... 32.4008 -25.5446 10.5945 4.6783 0 65533 0 0 32.4781 -25.5446 10.5953 5.8959 0 65534 0 0 32.5360 -25.5640 12.5408 5.9185 0 65535 0 0 The first three columns are the X/Y/Z location of the point return. The 4th column is the intensity (in photons). Since Linear mode can support multiple returns per pulse, t...
4 comments
Read more

Viewing and Importing DIRSIG Output Images

By
We are often asked what programs can view DIRSIG's image outputs and how to import the raw DIRSIG image data files into other tools for further processing. For basic image viewing, DIRSIG-4.4.0 now includes a very simple viewing tool. Launch it from the main simulation editor window by selecting the "Start image viewer" option from the "Tools" menu. If you run your simulation from the GUI simulation editor, new image files are automatically added to the list in the image viewer as they are generated. If you want to manually add files to the list, simply select the "Open" item from the "File" menu or the toolbar. Here is a screenshot of the main image viewer window. The top part contains the list of currently opened files and the bands within those image files. To view a single band as a gray-scale image, choose "Single Band Display" from the combo box and then click on the image band that you want. Finally, click "Load Band...
Post a Comment
Read more

DIRSIG5: An introduction, a timeline and a paper

By
Although we will be devoting more time to this topic in the blog, many of you are aware that the next generation version of DIRSIG (aka DIRSIG5) has been under development for the past 2 years. This was a ground-up, restart from zero, etc. effort that establishes the DIRSIG modeling toolkit for the next decade. New core, new approach Although we have developed a compatibility layer to allow existing DIRSIG4 simulations to run, the DIRSIG5 model is radically different under the hood. The lightweight and highly optimized radiometry core uses a different numerical radiometry (light transport) approach than we used in DIRSIG4. In addition to being faster (less work to get an accurate answer) this algorithm is far better suited for parallelization. As a result, we have implemented micro-scale parallelization (multi-threading on multi-core CPUs) from the start and work on macro-scale parallelization (MPI distribution on cluster-style computing) is getting underway. This radiometry core al...
5 comments
Read more