This work deals with the Harmonic+Noise decomposition and, as targeted application, to extract transient background noise surrounded by a signal having a strong harmonic content (speech for instance). In that perspective, a method based on the reassigned spectrum and a High Resolution subspace tracker are compared, both on simulations and in a more realistic manner. The reassignment re-localizes the time-frequency energy around a given pair (analysis time index, analysis frequency bin) while the High Resolution method benefits from a characterization of the signal in terms of a space spanned by the harmonic content and a space spanned by the stochastic content. Both methods are adaptive and the estimations are updated from a sample to the next.