ImageJ Macros

An ImageJ macro for correcting frame drift occurred during image acquisition.

It often happens that you have an image sequence that shows problematic drifting of image frame and at the same time you have some landmarks that could be used for correcting the drift. This ImageJ macro allows you to Manually track the landmark using ImageJ Manual Tracking Plugin. Using the coordinates recorded in the Result window, each frame is shifted back so that the landmark stays in a single place.

Dithering is a type of half tone thresholding where greyscale (or RGB channel) intensity is converted into a local density of binary pixels. This is ideal for rendering images in devices with a binary output such as printers (greyscale) or with a small number of colours (colour dithering). The following methods have been implemented (there are several more):

• Floyd-Steinberg
• Atkinson
• Jarvis-Judice-Ninke
• Stucki
• Bayer_2x2
• Bayer_4x4
• Bayer_8x8
• Clustered_4x4
• Random

Here is a good text explaining various dithering algorithm.