ImageProcessing step overview


The ImageProcessing step provides a comprehensive set of image processing operations that enhance or transform an image or a region of the image to create a new output image.

Matrox Design Assistant supports such operations as:

  • Point-to-point operations. These operations include constant thresholding, image comparison, image subtraction, and image mapping. They compute each pixel result as a function of the pixel value at a corresponding location in either one or 2 source images.

  • Spatial filtering operations. These operations are also known as convolutions. They include operations that can smooth images, enhance and detect image edges, and remove 'noise' from an image. Most of these operations compute results based on an underlying neighborhood process: the weighted sum of a pixel value and its neighbors' values.

  • Morphological operations. These operations include erosion, dilation, opening, and closing of images. They compute new values according to geometric relationships and matches to known patterns in the input image.

  • Geometric transformation operations. These operations can properly orient an image, flip the image vertically or horizontally, and resize an image.

  • Copy and convert operations. These operations can fill a portion of an image with a fixed value or with pixels copied from another image. They also allow RGB color images to be converted to another color space, for example, hue, color, or lightness.

  • Color operations. These operations can fill a portion of an image with distance or projection values. You can calculate the color distance (difference) between 2 images or an image and a specific color. You can also use color projection techniques to produce the most optimal grayscale image from a color image.

The ImageProcessing step's operations can be applied sequentially to an image by adding them to the list of operations. The output image of an operation can be the input image of the next operation in the list. Each operation can independently work on a region of the image or the full image.

For an example of the ImageProcessing step, see the Image Processing example project.