Computational imaging pipelines (CIPs) convert the raw output of imaging sensors into the high-quality images that are used for further processing. This work studies how Block-Matching and 3D filtering (BM3D), a state-of-the-art denoising algorithm can be implemented to meet the demands of user-interactive (UI) applications. Denoising is the most computationally demanding stage of a CIP taking more than 95% of time on a highly-optimized software implementation [29]. We analyze the performance and energy consumption of optimized software implementations on three commodity platforms and find that their performance is inadequate.