Abstract: A method for decoding a 360-degree image includes: receiving a bitstream obtained by encoding a 360-degree image; generating a prediction image by making reference to syntax information obtained from the received bitstream; combining the generated prediction image with a residual image obtained by dequantizing and inverse-transforming the bitstream, so as to obtain a decoded image; and reconstructing the decoded image into a 360-degree image according to a projection format. Here, generating the prediction image includes: checking, from the syntax information, prediction mode accuracy for a current block to be decoded; determining whether the checked prediction mode accuracy corresponds to most probable mode (MPM) information obtained from the syntax information; and when the checked prediction mode accuracy does not correspond to the MPM information, reconfiguring the MPM information according to the prediction mode accuracy for the current block.

Abstract: An image prediction encoding device includes a prediction signal generator that produces a prediction signal with respect to a target pixel signal of a target region that is among regions divided by a block division unit, a motion estimator that searches for a motion vector required for the production of the prediction signal from an already reproduced signal, and a subtractor that produces a residual signal indicating a difference between the prediction signal and the target pixel signal. The prediction signal generator determines a search region that is a partial region of the already reproduced signal based on the motion vector and produces one or more type 2 candidate prediction signals. The prediction signal generator includes a candidate prediction signal combining unit that produces the prediction signal by processing the type 2 candidate prediction signals and a type 1 candidate prediction signal produced based on the motion vector.

Abstract: Local motion estimation is described herein. Each picture of a video is partitioned into blocks for the local motion estimation. An extended-block FFT is calculated for each block, where the extended-block denotes that a certain area around the block is also included for applying FFT. Extending the block for FFT helps to account for the motion of objects that are moving into or out of the block. Phase correlation is applied to attain a set of Motion Vector (MV) candidates for the blocks, and a cost function is evaluated for each MV. If no MV candidate produces a cost function below a pre-defined threshold, a hierarchical variable block matching search is applied and the process is repeated with blocks for finer resolution. Also, predictive MV candidates are used during the block matching search along with temporal constraints tracking to select an MV that yields the minimum cost function.

Abstract: A method of filtering an image includes receiving target image data and applying a multiple stage filter to the target image data. Each stage of the filtering includes generating a motion vector sampling pattern, using the target image data and the motion vector sampling pattern to generate a temporal prediction of the target image data, and using the temporal prediction of the target image data to generate a spatial-temporal transformation of the target image data.