I will present recent results on the related problems of denoising, covariance estimation, and principal component analysis for the spiked covariance model with heteroscedastic noise.  Specifically, I will present an estimator of the principal components based on whitening the noise, and optimal spectral shrinkers for use with these estimated principal components.  I will also show new results on the optimality of whitening for principal subspace estimation.  This is joint work with Elad Romanov of the Hebrew University.