It can occur even under good lighting conditions due to sensor limitations or compression artifacts. In these cases, reducing noise improves clarity and efficiency. But in low-light scenarios, effective denoising can make the difference between an unusable and a usable signal. What might look like a harmless grainy texture at first glance has a significant impact on both quality and efficiency: Noise reduces perceived visual quality by masking fine details and creating a restless, unstable image. It severely complicates video compression. Encoders struggle to distinguish between actual motion and noise, leading to higher bitrates for the same content. This means: more data, worse quality. What's often overlooked is that denoising isn't just an aesthetic improvement—it's a highly effective pre-processing step for video pipelines. Removing noise before encoding results in cleaner visuals and smaller file sizes or lower streaming bitrates.

In the still image below, we have added the motion vectors to the red channel. This is a blue box shot in the studio and it shows that noise is present even in good lighting conditions. Our GPU-based denoising engine, IRIS, is designed to enhance video quality at scale. For live applications, IRIS.BROADCAST brings real-time denoising up to UHD resolutions, ensuring cleaner signals without added latency. We’ll be showcasing our latest advancements at IBC this year.