In this paper, a method for separating stereophonic mixtures into their harmonic constituents is proposed. The method is based on a harmonic signal model. An observed mixture is decomposed by first estimating the panning parameters of the sources, and then estimating the fundamental frequencies and the amplitudes of the harmonic components. The number of sources and their panning parameters are estimated using an approach based on clustering of narrowband interaural level and time differences. The panning parameter distribution is modelled as a Gaussian mixture and the generalized variance is used for selecting the number of sources. The fundamental frequencies of the sources are estimated using an iterative approach. To enforce spectral smoothness when estimating the fundamental frequencies, a codebook of magnitude amplitudes is used to limit the amount of energy assigned to each harmonic. The source models are used to form Wiener filters which are used to reconstruct the sources. The proposed method can be used for source re-panning (demonstration given), remixing, and multi-channel upmixing, e.g. for hi-fi systems with multiple loudspeakers.