Image processing model generation method, processing method, storage medium, and terminal

A terminal comprising:

• a processor;
• and
• a memory storing a program that, when executed by the processor, causes the processor to:
• obtain a to-be-processed image captured by an under-screen camera;
• perform an image processing operation on the to-be-processed image by inputting the to-be-processed image into a corresponding image processing model to obtain a processed image, the image processing operation including at least ghost effect removal processing, wherein the image processing model corresponding to color deviation removal processing is a first image processing model, and the image processing model corresponding to the ghost effect removal processing is a second image processing model;
• and
• obtain an output image according to the processed image of the corresponding image processing model,
• wherein each image processing model is generated by:
• generating a generated image corresponding to a first image by a predetermined network model according to the first image of a training image set, the training image set including a plurality of training image groups, each training image group including the first image and a second image, wherein the first image is a color deviation image of the second image for the first image processing model, or the first image is a ghost effect image of the second image for the second image processing model;
• and
• correcting a model parameter by the predetermined network model according to the second image corresponding to the first image and the generated image corresponding to the first image, and continuing to generate an updated generated image corresponding to a next first image according to the next first image in a next training image group of the training image set until a training condition of the predetermined network model satisfies a predetermined condition,
• wherein the first image is generated based on an under-screen imaging system, and the second image describes a same content as the first image and is acquired without the under-screen imaging system
• wherein:
• the predetermined network model for generating the second image processing model corresponding to the ghost effect removal processing includes an encoder and a decoder;
• and
• generating the generated image corresponding to the first image by the predetermined network model according to the first image of the training image set includes:
• inputting the first image of the training image set into the encoder to obtain a feature image of the first image through the encoder, an image size of the feature image being smaller than an image size of the first image;
• and
• inputting the feature image into the decoder to output the generated image through the decoder, an image size of the generated image being equal to the image size of the first image.

A non-transitory computer readable storage medium storing one or more computer programs, the one or more computer programs, when executed by a processor, causing the processor to:

• obtain a to-be-processed image captured by an under-screen camera;
• perform an image processing operation on the to-be-processed image by inputting the to-be-processed image into a corresponding image processing model to obtain a processed image, the image processing operation including at least ghost effect removal processing, wherein the image processing model corresponding to color deviation removal processing is a first image processing model, and the image processing model corresponding to the ghost effect removal processing is a second image processing model;
• and
• obtain an output image according to the processed image of the corresponding image processing model,
• wherein each image processing model is generated by:
• generating a generated image corresponding to a first image by a predetermined network model according to the first image of a training image set, the training image set including a plurality of training image groups, each training image group including the first image and a second image, wherein the first image is a color deviation image of the second image for the first image processing model, or the first image is a ghost effect image of the second image for the second image processing model;
• and
• correcting a model parameter by the predetermined network model according to the second image corresponding to the first image and the generated image corresponding to the first image, and continuing to generate an updated generated image corresponding to a next first image according to the next first image in a next training image group of the training image set until a training condition of the predetermined network model satisfies a predetermined condition,
• wherein the first image is generated based on an under-screen imaging system, and the second image describes a same content as the first image and is acquired without the under-screen imaging system
• wherein:
• the predetermined network model for generating the second image processing model corresponding to the ghost effect removal processing includes an encoder and a decoder;
• and
• generating the generated image corresponding to the first image by the predetermined network model according to the first image of the training image set includes:
• inputting the first image of the training image set into the encoder to obtain a feature image of the first image through the encoder, an image size of the feature image being smaller than an image size of the first image;
• and
• inputting the feature image into the decoder to output the generated image through the decoder, an image size of the generated image being equal to the image size of the first image.