Digital video processing requires significant hardware resources to achieve acceptable performance. Digital video processing based on dynamic partial reconfiguration (DPR) allows the designers to control resources based on energy, performance, and accuracy considerations. In this paper, we present a dynamically reconfigurable implementation of a 2D FIR filter where the number of coefficients and coefficients values can be varied to control energy, performance, and precision requirements. We also present a high-performance GPU implementation to help understand the trade-offs between these two technologies. Results using a standard example of 2D Difference of Gaussians (DOG) filter indicate that the DPR implementation can deliver real-time performance with energy per frame consumption that is an order of magnitude less than the GPU. On the other hand, at significantly higher energy consumption levels, the GPU implementation can deliver very high performance. © 2011 IEEE.