How to use PCA algorithm for feature reduction...?

i am new at this method and i just want to get a solution with in a short time...so please help me how can i implement this method effectively.. for example, we have 10 sample set each having 10 images and each image having 1*576 so,we have extracted 10 sample set feature size i.e 100*576 so i just want to reduce it 576 to 250. i applied [coeff,score,latent,tsquared,mu]=pca(x,'Numcomponents',inf); but i did not get the right output that means reduced feature, it is not working and getting trouble to select which one is the final output from this method..

Answer 1

[Nidhi]

A similar question was asked and the answer to the question is given below in this link:

https://www.mathworks.com/support/search.html/answers/167938-how-pca-can-be-applied-to-an-image-to-reduce-its-dimensionality-with-example.html?fq[]=asset_type_name:answer&fq[]=category:stats/dimensionality-reduction&page=1