Rank Filters

Denoising images is not restricted to linear filters, another family of filters is powerful for such an image enhancement: the Rank Filters.

Noise Distributions

  

Noise present in  a scientific image can be described depending of its distribution. Thus, it is important to figure out how to define the type of noise in order to elaborate a strategy to denoise the images...

Linear Filters

In Image Processing, one of the most important application of the convolution is the filter. Here is a small introduction...

Convolution

In Image Processing, one of the most important operation is the convolution because it is used everywhere for designing filters, mathematical morphology operators, analyzing particles, etc. Here is a small introduction...

Perspective Transform

Among the various geometric transformations, the Perspective transform is very useful. By default, this transform is not available in Image > Transform. However, it is very easy to implement such a tool...

Enhancement: Subtract Background

In ImageJ, non uniform illumination may be corrected with the function Process > Subtract Background...

Enhancement: Non uniform illumination

In the Image Enhancement series, the non uniform illumination is the second main defect that you must correct in your images.

Enhancement: Brightness/Contrast and Histogram

The previous method based on the transfer function [Link] is powerful but you have to manually define the slope and the y-intercept of the transfer function. It is faster to directly modify the histogram.

Enhancement: Brightness/Contrast and Transfer Function

The brightness and contrast of an image can be enhanced by modifying the transfer function or playing with the pixel distribution of the histogram. Here is the first part with the transfer function...

Image Enhancement: TOC

Table of Contents of the series of posts dedicated to Image Enhancement.