Image Processing Tools: Difference between revisions

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Image Processing filters transform digital images.
They are quite easy to implement using either Processing or Python.

Processing Tools

DIY Filters

Processing makes it simple to handle images, iterate over the pixels of an image and perform operations on them.

Standard Filters

Processing comes loaded with a bunch of filters that are commonly used in Image processing programs such as Photoshop or the Gimp.

GPU Filters

You can also implement filters using OpenGL pixelshaders.
These harness the power of the GPU.

OpenCV Filters

OpenCV offers all kinds of algorithms from basic image processing to advanced computer vision.
The OpenCV library for processing provides access to those.

ImageJ Filters

Martin Schneider is currently working on a Processing Library / Wrapper for ImageJ. It will let you access image operations like skeletonization from inside Processing.

Python Tools

PIL

The Python Imaging Library provides you with the power to handle and process images. Multimedia Programming Tutorials by the Software Carpentry:

SciKit-Image

Scikit-image is a collection of algorithms for image processing.

SimpleCV

SimpleCV is a python wrapper for OpenCV (and a couple of other tools) that makes image processing really easy.

Software

FilterForge

FilterForge is a commercial application that lets you create filters using a node based dataflow programming language.
It can be used as a Plugin for Adobe Photoshop, and has crodsourced over 10.000 Image Processing Filters.