Image signal processing method using neural network model and computing apparatus for performing the same

A computing apparatus for processing an image signal by using a neural network model, the computing apparatus comprising:

• a memory storing a program for processing an image signal;
• and
• at least one processor configured to execute the program to obtain an image captured via an image sensor, identify a shooting context of the image, select a neural network model included in at least one of an image reconstruction module or an image correction module according to the shooting context, and process the image by using the selected neural network model,
• wherein the selecting of the neural network model comprises selecting a detailed component of the image reconstruction module based on a shooting condition,
• wherein a neural network model included in the image correction module comprises a first neural network model and a second neural network model,
• the first neural network model is a model trained to minimize a difference between an inference image output when an input image and a correction parameter are fed into the first neural network model and a label image corresponding to the correction parameter,
• the label image corresponding to the correction parameter is an image obtained by correcting the input image by using at least one correction algorithm to which the correction parameter is applied,
• the correction parameter fed into the first neural network model is a correction parameter inferred when the input image is fed into the second neural network model, and
• the second neural network model is a model trained to minimize a difference between the correction parameter inferred by the second neural network model when the input image is fed thereinto and a correction parameter that causes the label image to have preset image characteristics.

A non-transitory computer-readable recording medium having recorded thereon a program for performing an image processing method comprising:

• obtaining an image captured via an image sensor;
• identifying a shooting context of the image;
• selecting a neural network model included in at least one of an image reconstruction module or an image correction module according to the shooting context;
• and
• processing the image by using the selected neural network model,
• wherein the selecting of the neural network model comprises selecting a detailed component of the image reconstruction module based on a shooting condition,
• wherein a neural network model included in the image correction module comprises a first neural network model and a second neural network model,
• the first neural network model is a model trained to minimize a difference between an inference image output when an input image and a correction parameter are fed into the first neural network model and a label image corresponding to the correction parameter,
• the label image corresponding to the correction parameter is an image obtained by correcting the input image by using at least one correction algorithm to which the correction parameter is applied,
• the correction parameter fed into the first neural network model is a correction parameter inferred when the input image is fed into the second neural network model, and
• the second neural network model is a model trained to minimize a difference between the correction parameter inferred by the second neural network model when the input image is fed thereinto and a correction parameter that causes the label image to have preset image characteristics.