Image processing apparatus and image processing method thereof
AssigneesSamsung Electronics Co., Ltd., Korea Advanced Institute of Science and Technology
InventorsHyunseung LEE, MunChurl KIM, Yongwoo KIM, Jae Seok CHOI, Youngsu MOON, Cheon LEE
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Abstract
An image processing apparatus obtains a first output image by applying an image to a first training network model, obtains a second output image by applying the image to a second training network model, and obtains a reconstructed image based on the first output image and the second output image. The first training network model is a model that uses a fixed parameter obtained through training of a plurality of sample images, the second training network model is trained to minimize a difference between a target image corresponding to the image and the reconstructed image.
Claims20
An image processing apparatus, comprising:
- a memory configured to store at least one command;
- and
- a processor electrically connected to the memory,
- wherein the processor is further configured to:
- obtain a first output image output from a first training network model based on an input image input to the first training network model,
- obtain a second output image output from a second training network model based on the input image input to the second training network model, and
- obtain a reconstructed image based on the first output image and the second output image,
- wherein the first training network model is configured based on a fixed parameter obtained through training of a plurality of sample images, and
- wherein the second training network model is trained to minimize a difference between a target image corresponding to the input image and the reconstructed image.
An image processing method of an image processing apparatus, the method comprising:
- obtaining a first output image output from a first training network model based on an input image input to the first training network model;
- obtaining a second output image output from a second training network model based on the input image input to the second training network model;
- and
- obtaining a reconstructed image based on the first output image and the second output image,
- wherein the first training network model is configured based on a fixed parameter obtained through training of a plurality of sample images, and
- wherein the second training network model is trained to minimize a difference between a target image corresponding to the input image and the reconstructed image.
Dependencies are inferred from the claim text.