Visit us at SPIE DSS in April

The RIT Digital Imaging and Remote Sensing (DIRS) Lab has a booth (#3014) in the Exhibition Hall at this year's SPIE Defense, Security, and Sensing symposium in Orlando, FL (April 25-27). Adam Goodenough, Niek Sanders and myself will be hanging out at our booth talking to conference goers about DIRSIG. Other lab personel will be on hand to discuss RIT's other research interests ranging from MSI and HSI algorithm development to rapid data collection and delivery.

In addition to the exhibition, we will be milling about the Technical Conference. Specifically, I am chairing Session #9 entitled "Landsat Data Continuity Mission" in the "Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVII" conference on Wednesday morning. In that session, I will be showing some of the work we are doing with DIRSIG to support pre-flight modeling of the next-generation Landsat system. These new features to streamline the modeling of space-based, multi-spectral systems will be made available to the rest of the DIRSIG community later this summer. Adam will be showing off some of his other talents in his Thursday morning talk titled "Interactive visualization of hyperspectral images on a hyperbolic disk" (also in the MSI/HSI conference). A large number of the faculty, staff and students from the DIRS Lab will be in attendance in order to present over 20 papers across the various conference sessions.

If you will be attending, please stop by and visit.

Comments

LIDAR Point Cloud Visualization

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...

Viewing and Importing DIRSIG Output Images

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...

DIRSIG5: An introduction, a timeline and a paper

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...

DIRSIG

Search This Blog