Image processing apparatus using neural network and image processing method using the same

An image encoding method comprising:

• outputting an initial search position from a student neural network by inputting a current frame and a reference frame of an image into the student neural network that has been trained through a knowledge distillation from a teacher neural network;
• and
• performing motion estimation based on the initial search position,
• wherein the outputting of the initial search position comprises:
• obtaining a first initial search position from the teacher neural network by inputting a first frame and a second frame, into the teacher neural network;
• obtaining a second initial search position from the student neural network by inputting the first frame and the second frame into the student neural network;
• and
• training the student neural network based on a loss function using a difference between the first initial search position and the second initial search position.

An image decoding apparatus comprising:

• an entropy decoder configured to receive a bitstream and parse the received bitstream to obtain information necessary for image reconstruction;
• an inverse quantizer configured to output a transform coefficient by inversely quantizing a quantized transform coefficient contained in the information;
• an inverse transformer configured to obtain a residual block by inversely transforming the transform coefficient;
• a predictor configured to generate a predicted block on the basis of information on prediction obtained from the entropy decoder;
• an adder configured to generate a reconstructed block by adding the residual block and the predicted block;
• and
• a filter configured to apply filtering to the reconstructed block,
• wherein the bitstream is an encoded image signal based on a motion vector obtained using an initial search position output by inputting a current frame and a reference frame into a student neural network trained through a knowledge distillation technique using a teacher neural network, and
• wherein the student neural network is trained by inputting a first frame and a second frame into the teacher neural network to obtain a first initial search position, inputting the first frame and the second frame into the student neural network to obtain a second initial search position, and training the student neural network based on a loss function using a difference between the first initial search position and the second initial search position.

An image decoding method comprising:

• receiving a bitstream and parsing the received bitstream to obtain information necessary for image reconstruction;
• outputting a transform coefficient by inversely quantizing a quantized transform coefficient contained in the information;
• obtaining a residual block by inversely transforming the transform coefficient;
• generating a predicted block on the basis of information on prediction obtained from an entropy decoder;
• generating a reconstructed block by adding the residual block and the predicted block;
• and
• applying filtering to the reconstructed block,
• wherein the bitstream is an encoded image signal based on a motion vector obtained using an initial search position output by inputting a current frame and a reference frame into a student neural network trained through a knowledge distillation technique using a teacher neural network, and
• wherein the student neural network is trained by inputting a first frame and a second frame into the teacher neural network to obtain a first initial search position, inputting the first frame and the second frame into the student neural network to obtain a second initial search position, and training the student neural network based on a loss function using a difference between the first initial search position and the second initial search position.

A non-transitory computer-readable storage medium storing a program that is executable by a processor to perform an image encoding method comprising:

• outputting an initial search position from a student neural network by inputting a current frame and a reference frame of an image into the student neural network that has been trained through a knowledge distillation from a teacher neural network;
• and
• performing motion estimation based on the initial search position,
• wherein the student neural network is trained by inputting a first frame and a second frame into the teacher neural network to obtain a first initial search position, inputting the first frame and the second frame into the student neural network to obtain a second initial search position, and training the student neural network based on a loss function using a difference between the first initial search position and the second initial search position.