| CPC G06T 5/50 (2013.01) [G06N 3/08 (2013.01); G06T 5/002 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20212 (2013.01)] | 23 Claims |
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1. A method of enhancing a source image using an image enhancement machine learning model comprising:
capturing a source image using a digital imager component of a communication device;
processing the source image using an image enhancement machine learning model on the communication device, wherein the image enhancement machine learning model is trained by:
using at least one processor to perform:
accessing a set of target images, wherein the target images represent a target output of the image enhancement machine learning model;
generating a set of input images, wherein the set of input images correspond to one or more target images in the set of target images and represents content in at least one target image modified to simulate being captured under less ideal lighting conditions than in the at least one target image based on determining one or more potential dark pixel values associated with pixels in the at least one target image;
selecting a first reference pixel, based on a reference image, in response to determining that the first reference pixel is a closest match to the one or more potential dark pixel values; and
training the image enhancement machine learning model using a training dataset,
wherein the training dataset comprises the set of target images and the generated set of input images corresponding to the one or more target images to obtain a trained image enhancement learning model; and
outputting the processed source image.
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