Computer Vision (URGENT): Please create PYTHON SCRIPT answering all parts for the prompt below, thanks! (will upvote IF CORRECT AND COMPLETE:))

PCA analysis (30\%): For six multispectral satellite images corresponding to six spectral a. please organize the images that leads to the formation of a six-element vector x from each set of corresponding pixels in the images (256256), so the population consisted of 2562=65536 vectors from which the mean vector mx=E{x}, covariance matrix Cx=E{(xmx)(xmx)T}, and corresponding eigenvalues and eigenvectors can be computed. b. using eigenvectors as rows of matrix A, compute a set of y vectors according to y= A(xmx). Similarly compute Cy=ACxAT which is a matrix with diagonal elements as eigenvalues of Cx. c. generate a set of six principal component images using the y vectors, notice the significant portion of the contrast detail is contained in the first two images and decreases rapidly from there. PCA analysis (30\%): For six multispectral satellite images corresponding to six spectral a. please organize the images that leads to the formation of a six-element vector x from each set of corresponding pixels in the images (256256), so the population consisted of 2562=65536 vectors from which the mean vector mx=E{x}, covariance matrix Cx=E{(xmx)(xmx)T}, and corresponding eigenvalues and eigenvectors can be computed. b. using eigenvectors as rows of matrix A, compute a set of y vectors according to y= A(xmx). Similarly compute Cy=ACxAT which is a matrix with diagonal elements as eigenvalues of Cx. c. generate a set of six principal component images using the y vectors, notice the significant portion of the contrast detail is contained in the first two images and decreases rapidly from there