Huawei Technologies Co., Limited

Ioannis Alexiou

Ioannis Marras

Tao Wang

Liu Liu

Gang Chen

Jiangwei Li

Sean Moran

Youliang Yan

Gregory Gibran Slabaugh

Fenglong Song

Stefanos Zafeiriou

Steven George McDonagh

Gregory Slabaugh

Jose Costa Pereira

Viktor Vladimirovich Smirnov

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 processing apparatus and a method are provided. The apparatus comprises a plurality of processing modules configured to operate in series to refine a raw image captured by a camera, the modules comprising a first module and a second module, each of which independently implements a respective trained artificial intelligence model, wherein: the first module implements an image transformation operation that performs an operation from the set comprising: (i) an essentially pixel-level operation that increases sharpness of an image input to the module, (ii) an essentially pixel-level operation that decreases sharpness of an image input to the module, (iii) an essentially pixel-block-level operation on an image input to the module; and the second module as a whole implements a different operation from the said set.

Image processor and method

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London, United Kingdom

Ioannis Alexiou