Abstract:
Provided is a method of performing parallel entropy encoding and parallel entropy decoding by using a plurality of processors. The method includes: sequentially performing entropy encoding on a first row of blocks from among blocks that each have a predetermined size and are obtained by splitting and encoding an image, determining initial entropy coding probability information of a foremost block of a second row of blocks as entropy coding probability information updated by a block of a fixed position of the first row of blocks, sequentially performing entropy encoding on blocks of the second row of blocks which are serially arranged based on the initial entropy coding probability information, and after the entropy encoding is completed to a last block of the first row of blocks, initializing internal state information of an entropy encoded bit string of the first row of blocks.
Abstract:
A wearable device includes first and second electronic modules, a connection module configured to electrically connect the first electronic module to the second electronic module, and a length adjusting module of which length is adjustable to bring the connection module in contact with a user. The length adjusting module comprises first and second fastening units configured to be assembled and disassembled and configured to be locked together in a fastened position when assembled. When the first and second fastening units are assembled, the first fastening unit is electrically connected to the second fastening unit and a length of the length adjusting module is adjusted.
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:
An video decoding apparatus including a parser which obtains bit strings corresponding to current transformation coefficient level information by arithmetic decoding a bitstream based on a context model; a parameter determiner which determines a current binarization parameter by updating or maintaining a previous binarization parameter based on a comparison of a threshold and a size of a previous transformation coefficient; a syntax element restorer which obtains the current transformation coefficient level information by performing de-binarization of the bit strings using the determined current binarization parameter and generates a size of a current transformation coefficient using the current transformation coefficient level information, wherein the current binarization parameter has a value equal to or smaller than a predetermined value.
Abstract:
The present disclosure relates to signaling of sample adaptive offset (SAO) parameters determined to minimize an error between an original image and a reconstructed image in video encoding and decoding operations. An SAO decoding method includes obtaining context-encoded leftward SAO merge information and context-encoded upward SAO merge information from a bitstream of a largest coding unit (MCU); obtaining SAO on/off information context-encoded with respect to each color component, from the bitstream; if the SAO on/off information indicates to perform SAO operation, obtaining absolute offset value information for each SAO category bypass-encoded with respect to each color component, from the bitstream; and obtaining one of band position information and edge class information bypass-encoded with respect to each color component, from the bitstream.
Abstract:
Disclosed are methods for coding and decoding a multilayer video. The method for decoding a multilayer comprise: decoding a first layer picture and saving same to a decoded picture buffer (DPB); marking the first layer picture as a short-term reference picture; obtaining interlayer RPS information of a second layer picture which has a first POC identical to that of the first layer picture and which is interlayer-predicted by referencing the first layer picture; marking the first layer picture which has been marked as the short-term reference picture as a long-term reference picture, based on the interlayer RPS information; and performing interlayer prediction with respect to the second layer picture by referencing the first layer picture which has been marked as the long-term reference picture.
Abstract:
Methods and apparatuses for arithmetic encoding/decoding of video data. The arithmetic decoding method includes arithmetically decoding prefix bit strings representing a two-dimensional location of a last significant coefficient in a block sequentially by using a context model, arithmetically decoding suffix bit strings in a bypass mode, and performing inverse binarization on the arithmetically decoded prefix bit strings and suffix bit strings to acquire the location of the last significant coefficient in the block.