mirror of
https://github.com/Ponce/slackbuilds
synced 2024-11-21 19:42:24 +01:00
…
|
||
---|---|---|
.. | ||
doinst.sh | ||
fiji | ||
fiji.info | ||
fiji.SlackBuild | ||
ImageJ2.desktop | ||
README | ||
References | ||
slack-desc |
Fiji: Fiji is just ImageJ Fiji is an image processing package, a "batteries-included" distribution of ImageJ, bundling a lot of plugins which facilitate scientific image analysis. ImageJ is a Java image processing program inspired by NIH Image for the Macintosh. It can display, edit, analyze, process, save and print 8-bit, 16-bit and 32-bit images. It can read many image formats including TIFF, GIF, JPEG, BMP, DICOM, FITS and "raw". It supports "stacks", a series of images that share a single window. It is multi- threaded, so time-consuming operations such as image file reading can be performed in parallel with other operations. ImageJ can calculate area and pixel value statistics of user-defined selections. It can measure distances and angles. It can create density histograms and line profile plots. It supports standard image processing functions such as contrast manipulation, sharpening, smoothing, edge detection and median filtering. ImageJ does geometric transformations such as scaling, rotation and flips. Image can be zoomed up to 32:1 and down to 1:32. All analysis and processing functions are available at any magnification factor. The program supports any number of windows (images) simultaneously, limited only by available memory. Spatial calibration is available to provide real world dimensional measurements in units such as millimeters. Density or gray scale calibration is also available. Fiji is Just ImageJ, with extras. It is a distribution of ImageJ with many plugins useful for scientific image analysis in fields such as life sciences. It is actively maintained, with updates released often. NOTE: This comes with its own Java environment. Citing Schindelin, J.; Arganda-Carreras, I. & Frise, E. et al. (2012) "Fiji: an open-source platform for biological-image analysis" Nature methods 9(7): 676-682, PMID 22743772, doi:10.1038/nmeth.2019