Image Grayscale
As a first step in image processing it is common to convert a coloured image into grayscale. Rather than colour convert images using high level functions of Mathematica I wanted to test the idea of averaging the red, green and blue channels of each pixel in a colour image.
1. Iterate through the
columns of each row
of the image
​
2. Take the average of
each pixel RGB value
Image Blur
Continuing on from averaging the RGB channels of images, now I Iterate through each row of the image, taking the moving average along each pixel, using its two closes neighbours to create a new image of the same colour space.
GitHub Repository
Image Correlation
To apply a function, such as averaging, to each pixel in an image.
1. Apply Gaussian 3x3 matrix per pixel.
​
2. Repeat the process 50 times.
Usefulness of burring an image
This method reduces noise and cats like a low pass filter
Convert to grayscale and blur the image.
Number of white pixels
Number of white pixels reduced as the amount of blurring increases
Count the number of white pixels
Image threshold to create a binary image
Blur iterations