Image processing method and apparatus based on image processing model, electronic device, storage medium, and computer program product

An electronic device, comprising:

• one or more processors;
• and
• memory storing one or more programs, the one or more programs comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
• acquiring a standard image matched with an image processing model;
• determining light field variation parameters corresponding to a use environment of the image processing model based on the standard image;
• determining an image training sample set matched with the use environment of the image processing model based on the light field variation parameters, the image training sample set comprising images of different light field backgrounds;
• training a correction network of the image processing model through the image training sample set to obtain a model updating parameter adapted to the correction network, and generating a trained image processing model based on the model updating parameter;
• acquiring a single image in the use environment, and performing prediction processing on the single image through the trained image processing model to obtain light field information corresponding to the single image;
• and
• correcting a light field of the single image based on the light field information.

A non-transitory computer-readable storage medium, storing a computer program, the computer program, when executed by one or more processors of an electronic device, cause the one or more processors to perform operations comprising:

• acquiring a standard image matched with an image processing model;
• determining light field variation parameters corresponding to a use environment of the image processing model based on the standard image;
• determining an image training sample set matched with the use environment of the image processing model based on the light field variation parameters, the image training sample set comprising images of different light field backgrounds;
• training a correction network of the image processing model through the image training sample set to obtain a model updating parameter adapted to the correction network, and generating a trained image processing model based on the model updating parameter;
• acquiring a single image in the use environment, and performing prediction processing on the single image through the trained image processing model to obtain light field information corresponding to the single image;
• and
• correcting a light field of the single image based on the light field information