Channel mapping is the process of assigning captured data to specific output color channels, such as red, green, or blue. In imaging workflows, raw sensor values do not always match the final colors a human sees, so software decides how each input stream is translated and combined. This is common in infrared, multispectral, and other nonstandard camera systems, where the sensor output must be remapped before it becomes a usable picture.
In cyber security, channel mapping matters because the visual result is only as trustworthy as the processing pipeline behind it. A wrong mapping can hide details, create false contrast, or make a scene look more normal than it is. Defenders check these steps in forensic imaging, surveillance, and machine-vision systems to ensure the output reflects the original data. Attackers can also abuse color-channel manipulation to mislead analysts, disguise artifacts, or obscure hidden content in altered images.