Atmospheric turbulence degrades imagery by imparting scintillation and warping effects that blur the collected pictures and reduce the effective level of detail. While this reduction in image quality can occur in a wide range of scenarios, it is particularly noticeable when capturing over long distances, when close to the ground, or in hot and humid environments. For decades, researchers have attempted to correct these problems through device and signal processing solutions. While fully digital approaches have the advantage of not requiring specialized hardware, they have been difficult to realize in real-time scenarios due to a variety of practical considerations, including computational performance, the need to integrate with cameras, and the ability to handle complex scenes. We address these challenges and our experience overcoming them. We enumerate the considerations for developing an image processing approach to atmospheric turbulence correction and describe how we approached them to develop software capable of real-time enhancement of long-range imagery.