Intellindust Information Technology (Shenzhen) Co., Ltd.

Yaohui Sun

Xiao Zhou

Caizhi Zhu

Lin Wang

Peizhe Ru

Shengning Xiang

The embodiments of the present application provide a denoising method, apparatus, electronic device and medium, which relates to the technical field of image processing. The method comprises: inputting an image to be processed into an image denoising model, which is a model obtained by training a convolutional neural network model based on a preset training set, wherein the preset training set includes multiple groups of annotation data and sample data corresponding to each group of annotation data, and each group of annotation data includes multiple noiseless images obtained by performing motion simulation processing on one reference noiseless image, and the sample data corresponding to the group of annotation data includes images obtained by superimposing noise to the multiple noiseless images respectively; acquiring denoised image data output by the image denoising model; converting the image data into an image, to obtain a denoised image corresponding to the image to be processed. This can effectively solve the problem of ghost existed in the denoised image.

Denoising method, apparatus, electronic device and medium

The embodiments of the present disclosure provide a method and an apparatus for acquiring a RAW image, and an electronic device, the method including: obtaining an sRGB image; inputting the sRGB image into a preset image restoration model to obtain an initial RAW image corresponding to the sRGB image, wherein the preset image restoration model is a model obtained by training a preset neural network based on a first preset training set; adding a first preset noise to the initial RAW image to obtain a first noise RAW image; adding a second preset noise to the initial RAW image to obtain a second noise RAW image; inputting the first noise RAW image and the second noise RAW image into a preset noise addition model to obtain a target RAW image, wherein the preset noise addition model is a model obtained by training a preset neural network based on a second preset training set.

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Shenzhen, China

Yaohui Sun