University of Joensuu Pattern Recognition
Eigenvectors and inner product images
Number of eigenvector:











In this application eigenvectors and inner product images generated for spectral images can be examined. Eigenvectors are calculated separately for each spectral image by using principal component analysis (PCA). Furthermore, n^th inner product image is produced by multiplying the original spectral image by its n^th eigenvector.

Choose an image and the number of desired eigenvector. sRGB-image of the chosen spectral image, the chosen eigenvector and the resulting inner product image will be shown as a result.