Spectrum Optix Inc.

Martin Humphreys

Kevin Gordon

Darcy Daugela

Yeefang Xiao

Colin D'Amore

An image processing pipeline including a still or video camera includes a first neural network arranged to process and provide a neural network based result for at least one of an image capture setting, sensor processing, global post processing, local post processing, and portfolio post processing. A second neural network is arranged to receive the neural network result and further provide at least one of an image capture setting, sensor processing, global post processing, local post processing, and portfolio post processing, wherein at least one of the first and second neural networks generate data on local processors supported by the still or video camera.

Neural network supported camera image or video processing pipelines

A method for image capture includes determining an exposure range and setting at least one camera parameter to capture an underexposed image outside the exposure range. The underexposed image is processed using a neural network to recover image details. Image defects due to camera or object motion blur can be reduced.

Photographic underexposure correction using a neural network

A method for image capture includes identifying a bright spot in an image. A neural network is used to recover details in bright spot area through a trained de-noising process. Post-processing of the image is conducted to match image parameters of recovered details in the bright spot area to another area of the image.

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Sherwood Park, Canada

Martin Humphreys