Welcome ImageJ An open platform for scientific image analysis Download.
ImageJ is highly extensible , with thousands of plugins and scripts for performing a wide variety of tasks, and a large user community. This wiki documents all aspects of the ImageJ ecosystem , including:. This page was last modified on 3 August , at Create account Log in. Related software. Open source. ImageJ is a tool for the scientific community. To maintain transparency, the ImageJ application and its source code will always be freely available. Powerful tools such as the Script Editor and personal update sites help you develop and share reproducible analysis workflows.
Image Processing with ImageJ- Biomedical Informatics Hub - University of Exeter
The overall goal for processing images in the GPU is sparing time. GPUs can process images faster because they can calculate pixel values of many pixels in parallel. Thus, overall efficiency can only be achieved if whole pipelines are processed in the GPU.
Furthermore, repeatedly using the same operations on a GPU pays off because operations are cached. Reusing them is faster than using other methods.
ImageJ – Java image processing program
The example macro is benchmarking. It executes both operations ten times and measures the time each operation takes.
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This is just an excerpt of the macro:. The additional speedup comes from the caching mechanism mentioned above.
Image Processing with Imagej
And this works on a small laptop without dedicated GPU. This example should just motivate you to test your workflow on a GPU and guide you how to evaluate its performance. Side note: ImageJs mean filter runs inplace. That means the result is stored in the same memory as the input image. With every iteration in the for loop, the image becomes more and more blurry.
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Thus, the resulting images will look different. Be a sceptical scietist when processing images in the GPU.
Check that the workflow is indeed doing the right thing. This is especially important when working with experimental software. In presented case, have a look at mean. In some of the filters, I observed small differences between ImageJ and OpenCL especially at the borders of the images.
Related Image Processing with ImageJ
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