Abstract:
A method and apparatus for encoding video by using deblocking filtering, and a method and apparatus for decoding video by using deblocking filtering are provided. The method of encoding video includes: splitting a picture into a maximum coding unit; determining coding units of coded depths and encoding modes for the coding units of the maximum coding unit by prediction encoding the coding units of the maximum coding unit based on at least one prediction unit and transforming the coding units based on at least one transformation unit, wherein the maximum coding unit is hierarchically split into the coding units as a depth deepens, and the coded depths are depths where the maximum coding unit is encoded in the coding units; and performing deblocking filtering on video data being inversely transformed into a spatial domain in the coding units, in consideration of the encoding modes.
Abstract:
An image decoding method including determining coding units having a hierarchical structure for decoding an image using split information of a coding unit, determining at least one prediction unit for predicting a coding unit among the coding units using information about a partition type, determining at least one transformation unit for inversely transforming the coding unit using split information of the at least one transformation unit, wherein the split information of a coding unit, the information about a partition type and the information about a depth of the at least one transformation unit are parsed from a bitstream, parsing from the bitstream transformation coefficients generated by transformation according to the at least one transformation unit generated by dividing the coding unit, reconstructing residual of the at least one transformation unit by performing inverse quantization and inverse transformation on the parsed transformation coefficients, and performing intra prediction or inter prediction on the prediction unit to generate a predictor, and reconstructs the image based on the residual and the predictor.
Abstract:
Provided are scalable video encoding and decoding methods. The scalable video encoding method includes: obtaining a peripheral pixel of an enhancement block based on a peripheral pixel of a base layer block corresponding to the enhancement layer block to be prediction-encoded, and performing intra prediction on the enhancement layer block by using at least one of a peripheral pixel of the enhancement layer block that is encoded before the enhancement layer block and then restored and a peripheral pixel of the enhancement layer block that is obtained based on a peripheral pixel of the base layer block.
Abstract:
Provided are a method and apparatus for interpolating an image. The method includes: selecting a first filter, from among a plurality of different filters, for interpolating between pixel values of integer pixel units, according to an interpolation location; and generating at least one pixel value of at least one fractional pixel unit by interpolating between the pixel values of the integer pixel units by using the selected first filter.
Abstract:
Provided are a method and apparatus for estimating a motion vector using a plurality of motion vector predictors, an encoder, a decoder, and a decoding method. The method includes calculating spatial similarities between the current block and the plurality of neighboring partitions around the current block, selecting at least one of the neighboring partitions based on the calculated spatial similarities, and estimating a motion vector of the selected partition as the motion vector of the current block.
Abstract:
A method and apparatus for encoding and decoding an image by performing motion prediction and compensation on pictures in a group of pictures by selectively using a high-quality key picture that is previously encoded and restored, and a second picture that is previously encoded and restored. The method of encoding an image improves the prediction efficiency of an image by storing a key picture, which is encoded and restored to a high quality by reducing a loss caused by a quantization error using a small quantization coefficient, in a first storage unit and storing a previously encoded and restored second picture in a second storage unit, and then performing motion prediction and compensation by selectively using the key picture stored in the first storage unit and the second picture stored in the second storage unit while encoding a next picture in a group of pictures.
Abstract:
Provided are methods and apparatuses for encoding and decoding a motion vector. The method of encoding the motion vector includes: selecting, as a mode of encoding information about a motion vector predictor of the current block, a first mode in which information indicating the motion vector predictor from among at least one motion vector predictor is encoded or a second mode in which information indicating generation of the motion vector predictor based on blocks or pixels included in a previously encoded area adjacent to the current block is encoded; determining the motion vector predictor of the current block according to the selected mode and encoding the information about the motion vector predictor of the current block; and encoding a difference vector between the motion vector of the current block and the motion vector predictor of the current block.
Abstract:
An image processing apparatus for performing an image by using one or more neural networks may include a memory storing one or more instructions and at least one processor configured to execute the one or more instructions stored in the memory to obtain first feature information of a first image, generate an intermediate output image for the first image by performing first image processing on the first feature information, generate an attention map, based on the first image and the intermediate output image, obtain second feature information by performing second image processing on the first feature information, obtain fourth feature information by performing third image processing on third feature information extracted during the first image processing, and generate a second image having a higher quality than the first image, based on the attention map, the second feature information, and the fourth feature information.
Abstract:
An image processing apparatus, including a processor configured to execute instructions stored in a memory to: obtain characteristic information of a first image, divide the characteristic information into a plurality of groups, input each group into a respective layer of a plurality of layers included in a convolutional neural network and perform a convolution operation using one or more kernels to obtain a plurality of pieces of output information, generate an attention map including weight information corresponding to each pixel included in the first image, based on the plurality of pieces of output information, generate a spatially variant kernel including a kernel corresponding to the each pixel, based on the attention map and a spatial kernel including weight information according to a position relationship between the each pixel and a neighboring pixel, and generate a second image by applying the spatially variant kernel to the first image.
Abstract:
An image processing apparatus includes a memory storing at least one instruction; and a processor configured to execute the at least one instruction to use at least one neural network to: extract n pieces of first feature information from a first image, based on locations of pixels included in the first image, wherein n is a positive integer, generate n pieces of second feature information by performing a convolution operation between each of the n pieces of the first feature information and each of n kernels, and generate, based on the n pieces of the second feature information, a second image from which compression artifacts included in the first image are removed.