In this work, a method of decision-feedback equalization is developed for a digital holographic channel that experiences moderate-to-severe imaging errors. Decision feedback is utilized, not only where the channel is well-behaved, but also near the edges of the camera grid that are subject to a high degree of imaging error. In addition to these effects, the channel is worsened by typical problems of holographic channels, including non-uniform illumination, dropouts, and stuck bits. The approach described in this paper builds on established methods for performing trained and blind equalization on time-varying channels. The approach is tested on experimental data sets. On most of these data sets, the method of equalization described in this work delivers at least an order of magnitude improvement in bit-error rate (BER) before error-correction coding (ECC). When ECC is introduced, the approach is able to recover stored data with no errors for many of the tested data sets. Furthermore, a low BER was maintained even over a range of small alignment perturbations in the system. It is believed that this equalization method can allow cost reductions to be made in page-memory systems, by allowing for a larger image area per page or less complex imaging components, without sacrificing the low BER required by data storage applications.