Is there a difference between resizing and rescaling an image in computer vision?

Question

I have a research paper to implement. The author has used words rescale and resize in the context of an image. Are these two different operations or both mean the same thing.

Answer 1

Resizing:

"Resizing an object changes only the object's dimensions (width and height). For example, when you resize an object that has a specific stroke thickness, the stroke thickness stays the same when the object resizes."

Scaling:

"Scaling applies a transform to the object that resizes the object based on a multiple of the initial X, Y, and Z (three-dimensional objects only) values. For example, when you scale an object that has a specific stroke thickness, the stroke thickness scales when the object scales. This means that if you scale the object only by its x-axis value (the object's width), the stroke thickness for the width of the object will differ from the stroke thickness for the object's height (y-axis)."

I think this answers your question.
I took this info from this website.
Hope this answers is enough.

Answer 2

Both involves in changing the shape of the image. In resizing we are changing height and width as necessary. While, in rescaling we have to maintain the width to height ratio. Hence, rescaling do not cause distortion or skewing.