Biological imaging applications often employ molecular probes or nanoparticles for enhanced contrast. However, resolution and detection are still often limited by the intrinsic heterogeneity of the Isample, which can produce high levels of background that obscure the signals of interest. In this article we describe approaches to overcome this obstacle based on the concept of dynamic contrast, a strategy for elucidating signals by the suppression or removal of background noise. Dynamic contrast mechanisms can greatly reduce the loading requirement of contrast agents, and may be especially useful for single-probe imaging. Dynamic contrast modalities are also platform-independent, and can enhance the performance of sophisticated biomedical imaging systems or simple optical microscopes alike. Dynamic contrast is performed in two stages: i) a signal modulation scheme to introduce time-dependent changes in amplitude or phase, and ii) a demodulation step for signal recovery. Optical signals can be coupled with magnetic nanoparticles, photoswitchable probes, or plasmon-resonant nanostructures for modulation by magnetomotive, photonic, or photothermal mechanisms respectively. With respect to image demodulation, many of the strategies developed for signal processing in electronics and communication technologies can also be applied toward the editing of digital images. The image processing step can be as simple as differential imaging, or may involve multiple reference points for deconvolution using cross-correlation algorithms. Periodic signals are particularly amenable to image demodulation strategies based on Fourier transform; the contrast of the demodulated signal increases with acquisition time, and modulation frequencies in the kHz range are possible. Dynamic contrast is an emerging topic with considerable room for development, both with respect to molecular or nanoscale probes for signal modulation, and also to methods for more efficient image processing and editing.