Sony Interactive Entertainment Europe Limited

Isize Limited

Aaron Chadha

Ioannis Andreopoulos

Ilya Fadeev

Matthias Treder

A method of processing image data is provided. Pixel data for a first image is preprocessed to identify a subset of the pixel data corresponding to a region of interest depicting a scene element. The subset of the pixel data is processed at a first encoder to generate a first data structure representative of the region of interest, the first data structure identifying the scene element depicted in the region of interest. The subset of pixel data is also processed at a second encoder to generate a second data structure representative of the region of interest, the second data structure comprising values for visual characteristics associated with the scene element. The first and second data structures are outputted for use by a decoder to generate a second image approximating the region of interest of the first image.

Processing image data

A method of processing, prior to encoding using an external encoder, image data using an artificial neural network is provided. The external encoder is operable in a plurality of encoding modes. At the neural network, image data representing one or more images is received. The image data is processed using the neural network to generate output data indicative of an encoding mode selected from the plurality of encoding modes of the external encoder. The neural network trained to select using image data an encoding mode of the plurality of encoding modes of the external encoder using one or more differentiable functions configured to emulate an encoding process. The generated output data is outputted from the neural network to the external encoder to enable the external encoder to encode the image data using the selected encoding mode.

Certain aspects of the present disclosure provide techniques for preprocessing, prior to encoding with an external encoder, image data using a preprocessing network comprising a set of inter-connected weights is provided. At the preprocessing network, image data from one or more images is received. The image data is processed using the preprocessing network to generate an output pixel representation for encoding with the external encoder. The weights of the preprocessing network are trained to optimize a combination of at least one quality score indicative of the quality of the output pixel representation and a rate score indicative of the bits required by the external encoder to encode the output pixel representation.

Preprocessing image data

A method of preprocessing, prior to encoding with an external encoder, image data using a preprocessing network comprising a set of inter-connected learnable weights is provided. At the preprocessing network, image data from one or more images is received. The image data is processed using the preprocessing network to generate an output pixel representation for encoding with the external encoder. The preprocessing network is configured to take as an input encoder configuration data representing one or more configuration settings of the external encoder. The weights of the preprocessing network are dependent upon the one or more configuration settings of the external encoder.

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London, United Kingdom

Aaron Chadha