Hello,
I have been writing code for a paper and I'm reading an image in RGB space in OpenCV which means that its read as a 3D matrix (HEIGHT x WIDTH x 3 (RGB) ).
I'm flattening the image into a 2D matrix ( NB_PIXELS x 3 (RGB) ) using this code :
image = image.reshape(len(image) * len(image[0]), len(image[0][0]))
This flattening process is an important step in the method that I'm going over in the paper.
Since I can't have the paper depend on a library like NumPy I would like a more elegant way to explain the flattening. Are there any papers that I can reference or any equations, methods ..etc that I can use as a replacement to the code that I shared?
Thank you!
do you mean you can't using py libraries to show the flatting process? Or just can't use Numpy?
I would say, that there is nothing wrong with citations to a library like NumPy, which is massively used in a lot of different research areas. You can even give a citation to the function reshape (https://numpy.org/doc/stable/reference/generated/numpy.reshape.html) with the date & version of NumPy. The only thing, you are doing, is combining the three rbg byte values into one int value. If you describes this like you do in the question, this should be sufficient for a paper.
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