Principal Component Analysis seems to be a good choice at that point, because I had this idea in the beginning of removing useless pixels and pca just takes it some steps further by considering the variance of each feature. If you compare my naive approach with pca in terms of weapons, then my approach would be stick and stones and pca the orbital laser cannon So, i started with pca in matlab. There are two choices at this point. We can scale and center the data before performing pca or we just let the data as it is and perform pca.
- noise removal (how?)
- subsampling/downsampling (feature reduction)
- removal of outliers
- pca (feature reduction)