Abstract:
Provided are an inter prediction method and a motion compensation method. The inter prediction method includes: performing inter prediction on a current image by using a long-term reference image stored in a decoded picture buffer; determining residual data and a motion vector of the current image generated via the inter prediction; and determining least significant bit (LSB) information as a long-term reference index indicating the long-term reference image by dividing picture order count (POC) information of the long-term reference image into most significant bit (MSB) information and the LSB information.
Abstract:
Provided are a method and apparatus for encoding or decoding a 360-degree image. An image decoding method and apparatus according to an embodiment include: obtaining image data from a bitstream; decoding a first region of a projection image corresponding to a non-clipping region of a 360-degree image from the image data; obtaining information about a clipping region of the 360-degree image from the bitstream; determining a second region of the projection image, based on the information about the clipping region; and converting the projection image including the first region and the second region into the 360-degree image.
Abstract:
Provided is in-loop filtering technology using a trained deep neural network (DNN) filter model. An image decoding method according to an embodiment includes receiving a bitstream of an encoded image, generating reconstructed data by reconstructing the encoded image, obtaining information about a content type of the encoded image from the bitstream, determining a deep neural network (DNN) filter model trained to perform in-loop filtering by using at least one computer, based on the information about the content type, and performing the in-loop filtering by applying the reconstructed data to the determined DNN filter model.
Abstract:
Provided is a method of encoding an image, the method including: determining a subjective quality of the image when the image is compressed; determining at least one degree of compression that changes the subjective quality and is from among degrees of compression indicating how much the image is compressed; and encoding the image by compressing a residual signal of the image, based on compression information according to the determined degree of compression, wherein the subjective quality is determined for each frame by using a Deep Neural Network (DNN). Provided are an image decoding method and an image decoding apparatus for performing the image decoding method for decoding an image by using information encoded according to an image encoding method.
Abstract:
Provided is an image processing method including: acquiring images captured in at least two directions; generating a projection image by projecting the images onto a polyhedron; moving a location of at least one pixel among pixels in the projection image to reshape the projection image into a rectangular image; and processing the rectangular image.
Abstract:
Provided is a video processing device and method capable of enhancing security of content included in a video, the video processing device including: a loader configured to load an original video; an encoder configured to generate an encoded video including a header and a payload by encoding the loaded original video; and a security information inserter configured to insert security information comprising information about a reproduction right of the video into the header or the payload.
Abstract:
Provided are an inter prediction method and a motion compensation method. The inter prediction method includes: performing inter prediction on a current image by using a long-term reference image stored in a decoded picture buffer; determining residual data and a motion vector of the current image generated via the inter prediction; and determining least significant bit (LSB) information as a long-term reference index indicating the long-term reference image by dividing picture order count (POC) information of the long-term reference image into most significant bit (MSB) information and the LSB information.
Abstract:
Provided are methods and apparatuses for encoding and decoding an image. The method of encoding includes: determining a maximum size of a buffer to decode each image frame by a decoder, a number of image frames to be reordered, and latency information of an image frame having a largest difference between an encoding order and a display order from among image frames that form an image sequence, based on an encoding order the image frames that form the image sequence, an encoding order of reference frames referred to by the image frames, a display order of the image frames, and a display order of the reference frames; and adding, to a mandatory sequence parameter set, a first syntax indicating the maximum size of the buffer, a second syntax indicating the number of image frames to be reordered, and a third syntax indicating the latency information.
Abstract:
Provided are an inter prediction method and a motion compensation method. The inter prediction method includes: performing inter prediction on a current image by using a long-term reference image stored in a decoded picture buffer; determining residual data and a motion vector of the current image generated via the inter prediction; and determining least significant bit (LSB) information as a long-term reference index indicating the long-term reference image by dividing picture order count (POC) information of the long-term reference image into most significant bit (MSB) information and the LSB information.
Abstract:
Encoding an image using a non-encoding region of the image, a block-based encoding region of the image, and a pixel-based encoding region of the image.