Detecting a pixelated image in python

Question

I\'m trying to determine if an image is squared(pixelated).

I\'ve heard of 2D fourrier transform with numpy or scipy but it is a bit complicated.

The goal is

Answer 1

If you scan through lines of it it's abit easier because then you deal with linear graphs instead of 2d image graphs, which is always simpler.

Solution:

scan a line across the pixels, put the line in an array if it is faster to access for computations, and then run algorithms on the line(s) to determine the blockiness:

1/ run through every pixel in your line and compare it to the previous pixel by substracting the value between the two pixels. make an array of previous pixel values. if large jumps in pixel values are at regular invervals, it's blocky. if there are large jumps in values combined with small jumps in values, it's blocky... you can assume that if there are many equal pixel differences, it's blocky, especially if you repeat the analysis twice at 2 and 4 neighbour pixel intervals, and on multiple lines.

you can also make graphs of pixel differences between pixels 3-5-10 pixels apart, to have additional information on gradient changes of sampled lines of pics. if the ratio of pixel differences of neighbour pixels and 5th neighbour pixels is similar, it also indicates unsmooth colors.

there can be many algorythms, including fast fourrier on a linear graph, same as audio, that you would use on line(s) from the pic, that is simpler than a 2d image algorythm.