Abstract: A method, processor, and computer readable medium for generating blended intensity data for processing by a further processor, the method comprising the steps of generating a local contrast map based on image data, the local contrast map comprising a plurality of contrast values. An alpha mask is generated by associating an alpha mask value to each contrast value. First intensity data based on the image data using a first intensity calculation method and second intensity data based on the image data using a second intensity calculation method are also generated. The blended intensity data is generated by blending from at least one of the first intensity data and the second intensity data based on the alpha mask values; and outputted to the further processor.

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.