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.

Abstract: A method of performing tone mapping in a stream of images (Fr1 . . . N) includes, for each image (FrN) in the stream: sparsely reading image data values (IDN) corresponding to the image (FrN) to provide sparse image data from a plurality of sparsely distributed positions (Pos1 . . . k) in the image (FrN); generating, based on the sparse image data, tone mapping parameters of a tone mapping algorithm (TMA) for each position in the image (FrN); each position in the image (FrN) including the sparsely distributed positions (Pos1 . . . k) and a plurality of further positions (PosF1 . . . j) in the image (FrN); reading the image data values (IDN) corresponding to the image (FrN) to provide image data from each position in the image (FrN); and tone mapping the image by mapping the image data from each position in the image (FrN) to adjusted image data using the generated tone mapping parameters.

Abstract: A method of performing tone mapping in a stream of images (Fr1 . . . N) includes, for each image (FrN) in the stream: sparsely reading image data values (IDN) corresponding to the image (FrN) to provide sparse image data from a plurality of sparsely distributed positions (Pos1 . . . k) in the image (FrN); generating, based on the sparse image data, tone mapping parameters of a tone mapping algorithm (TMA) for each position in the image (FrN); each position in the image (FrN) including the sparsely distributed positions (Pos1 . . . k) and a plurality of further positions (PosF1 . . . j) in the image (FrN); reading the image data values (IDN) corresponding to the image (FrN) to provide image data from each position in the image (FrN); and tone mapping the image by mapping the image data from each position in the image (FrN) to adjusted image data using the generated tone mapping parameters.