Huawei Technologies Co., Limited

Filippos Kokkinos

Ioannis Marras

Stefanos Zafeiriou

Gregory Slabaugh

Matteo Maggioni

Stamatios Lefkimmiatis

The present disclosure relates to method and apparatuses for denoising an image. One example method includes receiving an input image captured by an image sensor, implement a trained artificial intelligence model to form an estimate of a noise pattern in the input image, to form an estimate of at least one noise statistic for the image sensor, and to refine the estimate of the noise pattern based on the estimate of the at least one noise statistic, and form an output image by subtracting the refined estimate of the noise pattern from the input image.

Noise reconstruction for image denoising

An image processor for transforming an input image, the image processor being configured to implement a trained artificial intelligence model, where the image processor is configured to: receive the input image; based on one or both of (i) the content of the input image and (ii) features extracted from the input image, process the image by the trained artificial intelligence model to: (i) determine a set of image filters; and (ii) for each of a plurality of subregions of the image, select an image filter from the set of image filters; and for each of the plurality of subregions of the image, apply the respective image filter to the subregion or to features extracted from that subregion. This may allow for differentiable selection of filters from a discrete learnable and decorrelated group of filters to allow for content based spatial adaptations.

Growing community of inventors

London, United Kingdom

Filippos Kokkinos