Huawei Technologies Co., Limited

Gregory Slabaugh

Stefanos Zafeiriou

Ioannis Marras

Ales Leonardis

Ioannis Alexiou

Filippos Kokkinos

Benjamin Busam

Jifei Song

Matteo Maggioni

Eduardo Perez Pellitero

The present disclosure provides example apparatuses, methods, and devices for denoising an image. One example apparatus performs operations including receiving an input image. A trained artificial intelligence model is implemented to form an estimate of a noise pattern in the input image and form an output image by subtracting the estimate of the noise pattern from the input image, where the model is configured to form the estimate of the noise pattern, and the estimate of the noise pattern is representative of a noise pattern that is characteristic to a specific image sensor type.

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.

Spatially adaptive image filtering

The present disclosure relates to methods and devices for performing depth estimation on image data. In one example, a device performs depth estimation on first and second images captured using one or more cameras having a color filter array. Each image of the first and second images comprises multiple color channels. Each color channel of the multiple color channels corresponds to a respective color channel of the color filter array. The device performs the depth estimation by estimating disparity from the color channels of the first and second images.

Device and method for depth estimation using color images

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London, United Kingdom

Gregory Slabaugh