Mort CantyThis page lists the most recent versions of my IDL programs for the ENVI environment discussed in my textbook Image Analysis, Classification and Change Detection in Remote Sensing, with Algorithms for ENVI/IDL, Second Revised Edition Taylor & Francis, CRC Press 2010 as well as some additional, mostly experimental, routines for parallel processing with Nvidia's CUDA and Python versions of some of the algorithms. This page was last modified 05/16/2013 13:01:43.- Included an ENVI/IDL extension for Scatterplot normalization Return to my private homepage here. If you don't have ENVI/IDL, you can try out some of the algorithms on the Google Cloud. See also Allan Nielsen's software page for Matlab versions of the change detection algorithms and my Python versions of IR-MAD, Radiometric Normalization and kernel PCA. Prerequisite LibrariesThe following libraries must be present in the IDL path before attempting to run any of the extensions: David Fanning's Coyote LibraryMy auxilliary routines (Documentation.) On 32bit Windows systems place PROVMEANS.x86.DLL and PROVMEANS.DLM from this library in your DLM path. Note: If you are running IDL on Windows x64, place PROVMEANS.x86_64.DLL and PROVMEANS.DLM in the DLM path. In addition, if you don't have Microsoft Visual C installed on your computer, you will need to download and install the Microsoft Visual C 2010 Redistributable Package (x64). If you're not running on Windows, see the textbook for instructions.
All extensions also assume that ENVI is up and running. Most of them can be integrated directly into the ENVI main menu by copying the programs with filenames of the form program_RUN.PRO to ENVI's SAVE_ADD directory. In addition some of the extensions can take advantage of the Tech-X Corp. GPULib interface to CUDA. (These extensions will now also run without GPULib/CUDA.) DocumentationKernel K-Means Clustering of Remote Sensing Imagery with CUDA, a detailed description of my GPULib implementation of the Kernel K-Means algorithm (Google Docs).The MAD MAN, a users manual for the IR-MAD (iMAD) and RADCAL extensions (Google Docs). ENVI/IDL Extensions Python routines DownloadsNote: If you use this software, please do not forget to acknowledge the source. If you use the extension(s) for IR-MAD (iMAD) analysis please cite Allan Nielsen's IR-MAD paper, if you use the extension(s) for IR-MAD radiometric normalization please cite the normalization paper by myself and Allan Nielsen, if you use the kMAF extension please cite Allan's kMAF/kMNF paper.
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