A video decoding method according to the present invention may comprise: a step for determining whether to divide a current block into a plurality of sub-blocks; a step for determining an intra prediction mode for the current block; and a step for performing intra prediction for each sub-block on the basis of the intra prediction mode, when the current block is divided into the plurality of sub-blocks.

A method, comprises monitoring a encoding process of a source video file performed by an encoder; obtaining an encoding decision parameter used to encode a picture of the source video file during the encoding process; comparing the encoding decision parameter to a threshold; based on the step of comparing, identifying the picture as a candidate picture for a visual defect or coding error; and storing a timestamp of the candidate picture.

An apparatus including a first module and a second module. The first module may be configured to generate one or more values based upon an analysis of one or more samples of a first frame. The second module may be configured to encode one or more samples of a second frame taking into account the one or more values generated by the first module. The one or more values generally represent a measure of an effect on the one or more samples of the first frame of encoding decisions made during encoding of the one or more samples of the second frame.

A method of processing a reconstructed picture can include generating a prediction block based on a prediction mode; generating a quantization block by inverse-scanning quantization coefficient information; generating a transform block by inverse-quantizing the quantization block using a quantization parameter; generating a residual block by inverse-transforming the transform block; generating a reconstructed picture by using the prediction block and the residual block; andapplying a deblocking filter on the reconstructed picture. Also, it is determined whether the deblocking filtering is applied between two adjecent blocks P and Q containing samples p0 and q0 respetively by using a boundary quantization parameter when a boundary strength is not zero, and the boundary quantization parameter is set to an average value of a quantization parameter of block P and a quantization parameter of block Q, and the quantization parameter is derived by adding a residual quantization parameter and a quantization parameter predictor.

A method of processing a reconstructed picture can include generating a prediction block based on a prediction mode; generating a quantization block by inverse-scanning quantization coefficient information; generating a transform block by inverse-quantizing the quantization block using a quantization parameter; generating a residual block by inverse-transforming the transform block; generating a reconstructed picture by using the prediction block and the residual block; andapplying a deblocking filter on the reconstructed picture. Also, it is determined whether the deblocking filtering is applied between two adjecent blocks P and Q containing samples p0 and q0 respetively by using a boundary quantization parameter when a boundary strength is not zero, and the boundary quantization parameter is set to an average value of a quantization parameter of block P and a quantization parameter of block Q, and the quantization parameter is derived by adding a residual quantization parameter and a quantization parameter predictor.

Disclosed here are methods, systems, and devices for measuring visual quality degradation of digital content caused by an encoding process. There is received first data for a digital content item, which is not encoded by the encoding process, and second data for the digital content item, which is encoded by the encoding process. For a given artefact type, the first data and the second data are processed to obtain a first quality metric measuring visual quality degradation in the digital content item attributable to the given artefact type caused by the encoding process. A stored mapping corresponding to the given artefact type is applied to the first quality metric to obtain a second quality metric which measures visual quality degradation in the digital content item attributable to the given artefact type caused by the encoding process and approximates subjective assessment of the digital content item by a human visual system.

Embodiments of the disclosure provide systems and methods for processing video content. The method can include: receiving raw video data of a video; determining a texture complexity for the video based on the raw video data; determining an encoding mode for the raw video data based on the texture complexity; and encoding the raw video data using the determined encoding mode.

The usual coding order according to which the reference view is coded prior to the dependent view, and within each view, a depth map is coded subsequent to the respective picture, may be maintained and does lead to a sacrifice of efficiency in performing inter-view redundancy removal by, for example, predicting motion data of the current picture of the dependent view from motion data of the current picture of the reference view. Rather, a depth map estimate of the current picture of the dependent view is obtained by warping the depth map of the current picture of the reference view into the dependent view, thereby enabling various methods of inter-view redundancy reduction more efficiently by bridging the gap between the views. According to another aspect, the following discovery is exploited: the overhead associated with an enlarged list of motion predictor candidates for a block of a picture of a dependent view is comparatively low compared to a gain in motion vector prediction quality resulting from an adding of a motion vector candidate which is determined from an, in disparity-compensated sense, co-located block of a reference view.

The usual coding order according to which the reference view is coded prior to the dependent view, and within each view, a depth map is coded subsequent to the respective picture, may be maintained and does lead to a sacrifice of efficiency in performing inter-view redundancy removal by, for example, predicting motion data of the current picture of the dependent view from motion data of the current picture of the reference view. Rather, a depth map estimate of the current picture of the dependent view is obtained by warping the depth map of the current picture of the reference view into the dependent view, thereby enabling various methods of inter-view redundancy reduction more efficiently by bridging the gap between the views. According to another aspect, the following discovery is exploited: the overhead associated with an enlarged list of motion predictor candidates for a block of a picture of a dependent view is comparatively low compared to a gain in motion vector prediction quality resulting from an adding of a motion vector candidate which is determined from an, in disparity-compensated sense, co-located block of a reference view.

A video fidelity measure is determined for a video sequence (1) by determining distorted and original difference pictures (30, 40) as pixel-wise differences between pixels (14, 24) in a distorted picture (10) and corresponding pixels (24) in an original picture (20) and between pixels in a preceding distorted picture (11) and corresponding pixels in a preceding original picture (21). First and second maps representing distortions in pixel values between the distorted and original pictures (10, 20) and between distorted and original difference pictures (30, 40) are determined. Third and sixth maps are determined as respective aggregations of local variabilities in pixels values in the distorted and original pictures (10, 20) and local variabilities in pixels values in the distorted and original difference pictures (30, 40), respectively. The video fidelity measure is then determined based on the first to third and sixth maps.