Hi! I am new to Computer Vision. I am curious as to whether it is possible to decompress a low dimensional image to a high dimensional one if I don't have an original image. What methods are applicable for this purpose? All the information, I came across on the web, is related to image compression (dimensionality reduction using PCA and reconstructing original image). I am interested in the reverse process provided I don't have the original image. I use Python. TIA
$\begingroup$
$\endgroup$
Add a comment
|
1 Answer
$\begingroup$
$\endgroup$
This is related to the subject of Image Quantisation.
You can reduce the dimensionality of your image (compress it) by Clustering -over colours, for instance.
When you do this you reduce the number of bits you need to save the whole image but you also need to save something like a dictionary that can map the reduced image into the original one.
Now, if you are given a certain compressed image, if you know how the reduction was carried, you could get something close to the original image.