Images and matrices are 2D data structures of numbers, but that is where the similarities end. An image is more like a vector, which matrices can be applied to. You would never matrix multiply an image onto another vector. Still, it isn’t uncommon to visualize matrices as images.
Well a matrix is a collection of vectors so... I guess I somewhat agree.. You can certainly apply projections to images, I mean this is what photoshop does.
> "You would never matrix multiply an image onto another vector."
That wasn't me. But I can still elaborate: while you can certainly consider a non-color image as a matrix, the operation of multiplying this matrix with a vector is rather meaningless.
While a lot of things can be made into or viewed as matrices, a matrix is typically only meaningful as a representation of a linear map.
Typical use on PCA/SVD on image, what you do is treat each image as a vector, create a matrix out of a collection of images, and then do PCA/SVD on the matrix to analyze the distribution of the images, normalize, get the eigen-images (principal components), etc.
Yeah, in retrospect that seems like the way to do it. The toy examples I learned from in college did it on a single image split up by row, but I can’t think of a great use case for that besides some naive compression.
