Apply any other desired filters.Įncode with settings that various searches of The Google have suggested are good for high-grain input: Take a second input of the same source video and blend it with the final noise mask. Invert the output of this, so that areas where no noise is desired are pure white, and noise 'pulls down' on the white. Multiply the uniform noise field by the luma field, so that areas selected (by luma) for more noise have brighter noise, and areas far away from the desired luma are almost if not entirely black. I experimentally determined this to be around luma 75, which seems to be where faces are in the first few minutes of my video source. Take an input of our source video and convert it to a luma plane that is brightest in the areas most obvious to the viewer. EDIT: Be sure to give this source the same framerate as your video!

Scaling it down by 50% scales these features down too. This is done at twice the video resolution, and then scaled down, because the deflate and dilation filters create features larger than we want.

Initially, every pixel is randomized to a desaturated gray field of noise, then the deflate and dilation filters are used to subtly spread out the noise so that it isn't just lined up exactly with pixels.

Red giant film grain