The method performed by an apparatus for encoding a current block, includes: generating a predicted block by predicting the current block; generating a residual block of the current block by subtracting the predicted block from the current block; partitioning the residual block into a plurality of subblocks having various sizes, and transforming each of the subblocks by using a transform unit of a size identical to each of the subblocks, to thereby generate transform blocks of the subblocks; quantizing the transform blocks; and encoding transform coefficients of each of the quantized transform blocks.

The method performed by an apparatus for encoding a current block, includes: generating a predicted block by predicting the current block; generating a residual block of the current block by subtracting the predicted block from the current block; partitioning the residual block into a plurality of subblocks having various sizes, and transforming each of the subblocks by using a transform unit of a size identical to each of the subblocks, to thereby generate transform blocks of the subblocks; quantizing the transform blocks; and encoding transform coefficients of each of the quantized transform blocks.

Super-transform coding may include identifying a plurality of sub-blocks for prediction coding a current block, determining whether to encode the current block using a super-transform, and super-prediction coding the current block. Super-prediction coding may include generating a super-prediction block for the current block by generating a prediction block for each unpartitioned sub-block of the current block, generating a super-prediction block for each partitioned sub-block of the current block by super-prediction coding the sub-block, and including the prediction blocks and super-prediction blocks for the sub-blocks in a super-prediction block for the current block. Including the prediction blocks and super-prediction blocks for the sub-blocks in a super-prediction block for the current block may include filtering at least a portion of each prediction block and each super-prediction block based on a spatially adjacent prediction block. Super-transform coding may include transforming the super-prediction block for the current block using a corresponding super-transform.

Super-transform coding may include identifying a plurality of sub-blocks for prediction coding a current block, determining whether to encode the current block using a super-transform, and super-prediction coding the current block. Super-prediction coding may include generating a super-prediction block for the current block by generating a prediction block for each unpartitioned sub-block of the current block, generating a super-prediction block for each partitioned sub-block of the current block by super-prediction coding the sub-block, and including the prediction blocks and super-prediction blocks for the sub-blocks in a super-prediction block for the current block. Including the prediction blocks and super-prediction blocks for the sub-blocks in a super-prediction block for the current block may include filtering at least a portion of each prediction block and each super-prediction block based on a spatially adjacent prediction block. Super-transform coding may include transforming the super-prediction block for the current block using a corresponding super-transform.

Wavelet transformation is performed on first image data and second image data until a decomposition level becomes a decomposition level based on synthesis control data or the like, and first wavelet coefficient data and second wavelet coefficient data are thereby generated. An ROI coefficient related to an ROI and a non-ROI coefficient in the first wavelet coefficient data are determined on the basis of mask data and the ROI coefficient in the first wavelet coefficient data and a wavelet coefficient in the second wavelet coefficient data are synthesized with each other, and synthesized coefficient data are thereby generated. Inverse wavelet transformation is performed on the synthesized coefficient data until a decomposition level becomes a predetermined end level, and synthetic image data are thereby generated.

An ROI coefficient and a non-ROI coefficient in first wavelet coefficient data corresponding to a first target image are determined on the basis of mask data which is developed for the first wavelet coefficient data. The ROI coefficient in the first wavelet coefficient data and a coefficient in second wavelet coefficient data corresponding to a second target image are synthesized. Synthesized coefficient data are thereby generated. Inverse wavelet transformation is performed on the synthesized coefficient data until a decomposition level becomes a predetermined end level. Synthetic image data are thereby generated.

An ROI coefficient and a non-ROI coefficient in first wavelet coefficient data corresponding to a first target image are determined on the basis of mask data which is developed for the first wavelet coefficient data. The ROI coefficient in the first wavelet coefficient data and a coefficient in second wavelet coefficient data corresponding to a second target image are synthesized. Synthesized coefficient data are thereby generated. Inverse wavelet transformation is performed on the synthesized coefficient data until a decomposition level becomes a predetermined end level. Synthetic image data are thereby generated.

An image encoding/decoding method and apparatus are provided. An image decoding method performed by an image decoding apparatus may include determining a prediction mode of a current block, generating a prediction block of the current block based on inter prediction mode information, based on the prediction mode of the current block being an inter prediction mode, generating a residual block of the current block based on a transform block of the current block, and reconstructing the current block based on the prediction block and the residual block of the current bloc.

The present invention relates to a method and device for sharing a candidate list. A method of generating a merging candidate list for a predictive block may include: producing, on the basis of a coding block including a predictive block on which a parallel merging process is performed, at least one of a spatial merging candidate and a temporal merging candidate of the predictive block; and generating a single merging candidate list for the coding block on the basis of the produced merging candidate. Thus, it is possible to increase processing speeds for coding and decoding by performing inter-picture prediction in parallel on a plurality of predictive blocks.

The present invention relates to a method and device for sharing a candidate list. A method of generating a merging candidate list for a predictive block may include: producing, on the basis of a coding block including a predictive block on which a parallel merging process is performed, at least one of a spatial merging candidate and a temporal merging candidate of the predictive block; and generating a single merging candidate list for the coding block on the basis of the produced merging candidate. Thus, it is possible to increase processing speeds for coding and decoding by performing inter-picture prediction in parallel on a plurality of predictive blocks.