Abstract: The present disclosure relates to an image processing method for enhancing illumination in an input image representing a scene, said image processing method comprising: down-sampling the input image, processing the down-sampled input image with a machine learning model, wherein said machine learning model is previously trained to generate a multiplicative correction map, said multiplicative correction map comprising multiplicative correcting factors for enhancing the illumination of the down-sampled input image, up-sampling the multiplicative correction map, generating an output image by multiplying the input image by the up-sampled multiplicative correction map.

Abstract: The present disclosure relates to an image processing method for generating a training dataset for training a machine learning model to enhance illumination of input images, said training dataset comprising target image/low-light image pairs to be used to train the machine learning model, said image processing method comprising, for generating a target image/low-light image pair: obtaining a target image representing a scene in a first color space, said first color space comprising a plurality of color channels including a color channel representative of the brightness of the scene, referred to as brightness channel, wherein the first color space comprises two color channels independent of the brightness of the scene, or is the L*a*b* color space, applying a darkening function to the brightness channel of the target image, thereby obtaining a low-light image of the scene and the target image/low light image pair in the first color space.