Abstract: A computer-implemented method includes accessing a video frame that includes a plurality of pixels. The method also includes generating a spatial mask that identifies pixels whose likelihood of causing banding within the video frame meets at least a minimum threshold likelihood. The method also includes computing a local distribution for a region of the video frame that includes at least those pixels that were identified by the spatial mask to detect bands in the video frame. The method further includes determining that the detected bands in the video frame are at least a minimum threshold size. The method also includes applying dithering to those detected bands in the video frame that were determined to meet the minimum threshold size. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A banding detection application generates a first set of pixel confidence values based on a first intensity difference value and first image scale associated with a first image, wherein each pixel confidence value included in the first set of pixel confidence values indicates a likelihood that a corresponding pixel included in the first image at the first image scale corresponds to banding in the first image. The banding detection application then generates a banding index corresponding to the first image based on the first set of pixel confidence values.

Abstract: In various embodiments, a banding detection application generates a first set of pixel confidence values based on a first intensity difference value and first image scale associated with a first image, wherein each pixel confidence value included in the first set of pixel confidence values indicates a likelihood that a corresponding pixel included in the first image at the first image scale corresponds to banding in the first image. The banding detection application then generates a banding index corresponding to the first image based on the first set of pixel confidence values.