The recent development of a nonredundant complex wavelet transform allows a novel framework for image analysis. Work on this representation has recognized that the phase and magnitude of complex coefficients can be related to important geometric properties in images. Existing work on human visual system (HVS) sensitivity offers little guidance in understanding the relative importance of noise (e.g., introduced by lossy coding) in phase components and magnitude components. The distinct geometric significance of the two components would suggest that their respective errors relate to different types of image structure, and thus each would have its own unique HVS sensitivity. In this paper, we extend the study of just-noticeable-differences (JND) to magnitude/phase sensitivities in complex wavelet representations and outline and report on preliminary experiments characterizing them.