I am not familiar with your topic, but I think you can just arrange your data in a matrix with 10 lines (no. of images) and 2000 columns (no. samples). If possible, try to optimize your sample research with suitable criteria, for instance, by performing your research only in regions of interest and avoiding the background. Then, when you perform PCA try to understand uo to which extent you can compress information. PCA rank values between 1 and 3 have a spatial interpretation, but you can also try energy criteria, i.e. choosing the number of components retaining a certain percentage on input data energy (in general equal to 95 per cent).

Thanks a lot dear MArianna Meo for your answer. I am trying to follow your suggestions.

What is size of each measure ?? 2000 values ??

Yes, as you have 2000 samples