Interpolation

Interpolation is the computational process of generating new data points between existing ones — essentially, software making an educated guess about what should exist in the gaps between known values. In video, interpolation appears most commonly in two contexts: frame interpolation (generating synthetic frames between existing frames to create slow-motion or high-frame-rate effects from lower-frame-rate source footage) and spatial interpolation (generating new pixels between existing pixels when upscaling resolution, so a 1080p image can fill a 4K display without simply repeating each pixel as a block).

Frame interpolation is the technology behind features like "motion smoothing" on consumer televisions (often called the "soap opera effect" because its over-smooth motion makes cinematic content look like video). The TV analyzes two consecutive film frames and generates synthetic intermediate frames — creating the appearance of 60fps or 120fps from 24fps source material. The result is hyper-smooth motion that many viewers find artificial and uncomfortable for narrative film content. For sports and gaming content, the same interpolation is often seen as beneficial. Dedicated AI interpolation tools like RIFE and Topaz Video AI take this further, using machine learning to generate more plausible intermediate frames.

In a production context, interpolation also refers to the keyframe interpolation used in motion graphics and animation — how software moves between two keyframe states. If a logo is at position A at frame 1 and position B at frame 30, interpolation determines the path and easing of the motion between those points. Linear interpolation moves at a constant speed. Ease-in/ease-out interpolation starts slow, accelerates through the middle, and decelerates at the end — matching the physics of how objects actually move. Getting interpolation right is the difference between motion graphics that feel mechanical and ones that feel alive.