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Gerbil

Project Release infomations and Project Resources. Note that these informations are from this projects Freecode.com page and the downloads themselves may not be hosted with SourceForge.JP.

Project Release Information

2012-02-05 02:06
Two important new functionalities are introduced in this release. First, gerbil now comes with a module for multispectral edge detection. Second, gerbil now provides a flexible commandline interface. It allows running algorithms in a batch, which is very valuable for benchmarking purposes.
2011-03-03 09:21
This release makes gerbil more useful for common tasks and enlarges its scope. You can now import and export labeling images. Newly introduced handling of data normalization and other usability enhancements greatly facilitate the visual analysis of image data. Landsat images (.lan format) are now supported for reading. Many bugs were fixed, and the internal API is more powerful and better documented.
2010-12-10 07:09
Compatibility with recent OpenCV and Boost libraries.
2010-12-02 23:11
A Windows installer is available. Fixes were made to the build system and for better platform support. The functionality of multi_img API was enhanced. Improvements were made to the Graph Segmentation interface. Fixes were made to various GUI bugs. Drawing was improved. A new feature was added to draw spectral vectors in RGB.
2010-10-20 22:35
This is the initial online release.

Project Resources

http://freecode.com/projects/gerbil

Project Description

Gerbil consists of an interactive visualization tool targeted at multispectral and hyperspectral image data, and a toolbox of common algorithms, e.g. for segmentation. Multispectral imaging has been gaining popularity and has been gradually applied to many fields besides remote sensing. However, due to the high dimensionality of the data, both human observers and computers have difficulty interpreting this wealth of information. Gerbil facilitates the visualization of the relationship between spectral and topological information in a novel fashion. It puts emphasis on the spectral gradient, which is shown to provide enhanced information for many reflectance analysis tasks. It also includes a rich toolbox for evaluation of image segmentation and other algorithms in the multispectral domain. The parallel coordinates visualization technique is combined with hashing for a highly interactive visual connection between spectral distribution, spectral gradient, and topology.

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