Why is large kernel processing such a big deal?
By considering the data in a large neighborhood centered around each pixel as it is being processed, it allows us to address a much larger range of spatial frequencies in the image. Traditional small kernel processing can only enhance details in the very highest spatial frequencies, which typically contain little of the spectral content of the image, and is where noise is prevalent. Hence, small kernel processors must employ relatively large gain to have much noticeable effect on the image, thereby typically producing sharp outlining artifacts and greatly increased visibility of noise. Our large kernel processing (operating on much more of the “meat” of the image) can produce dramatic results with much lower gain, with the additional benefits of large area shading, yielding much more natural-appearing images with increased local contrast, added dimensionality, and improved visibility of subtle details and features.
