H04N19/50

Method and system for picture segmentation using columns

Described is picture segmentation through columns and slices in video encoding and decoding. A video picture is divided into a plurality of columns, each column covering only a part of the video picture in a horizontal dimension. All coded tree blocks (“CTBs”) belonging to a slice may belong to one or more columns. The columns may be used to break the same or different prediction or in-loop filtering mechanisms of the video coding, and the CTB scan order used for encoding and/or decoding may be local to a column. Column widths may be indicated in a parameter set and/or may be adjusted at the slice level. At the decoder, column width may be parsed from the bitstream, and slice decoding may occur in one or more columns.

Method and system for picture segmentation using columns

Described is picture segmentation through columns and slices in video encoding and decoding. A video picture is divided into a plurality of columns, each column covering only a part of the video picture in a horizontal dimension. All coded tree blocks (“CTBs”) belonging to a slice may belong to one or more columns. The columns may be used to break the same or different prediction or in-loop filtering mechanisms of the video coding, and the CTB scan order used for encoding and/or decoding may be local to a column. Column widths may be indicated in a parameter set and/or may be adjusted at the slice level. At the decoder, column width may be parsed from the bitstream, and slice decoding may occur in one or more columns.

Transferring data from autonomous vehicles
11580687 · 2023-02-14 · ·

A system includes at least one imaging sensor and a processor. The processor is configured to acquire, using the imaging sensor, detected data describing an environment of an autonomous vehicle. The processor is further configured to derive reference data, which describe the environment, from a predefined map, to compute difference data representing a difference between the detected data and the reference data, and to transfer the difference data. Other embodiments are also described.

IMAGE DECODING METHOD AND DEVICE USING DEBLOCKING FILTERING
20230045656 · 2023-02-09 ·

An image decoding method according to the present disclosure presents indication information related to whether deblocking parameters for a deblocking filtering procedure exist in a picture header or a slice header.

IMAGE DECODING METHOD AND DEVICE USING DEBLOCKING FILTERING
20230045656 · 2023-02-09 ·

An image decoding method according to the present disclosure presents indication information related to whether deblocking parameters for a deblocking filtering procedure exist in a picture header or a slice header.

Super-resolution loop restoration
11558631 · 2023-01-17 · ·

A super-resolution coding mode is described. Encoded image can be decoded by decoding, from an encoded bitstream, a flag indicating whether an image was encoded using the super-resolution mode. The image is encoded at a first resolution. Responsive to the flag indicating that the image was encoded using the super-resolution mode, bits indicating an amount of scaling of the image are decoded. The image is decoded from the encoded bitstream to obtain a reconstructed image at the first resolution, and the reconstructed image is upscaled to a second resolution using the amount of scaling to obtain an upscaled reconstructed image. The second resolution is higher than the first resolution. Loop restoration filtering is applied to the upscaled reconstructed image using loop restoration parameters to obtain a loop restored image at the second resolution.

Super-resolution loop restoration
11558631 · 2023-01-17 · ·

A super-resolution coding mode is described. Encoded image can be decoded by decoding, from an encoded bitstream, a flag indicating whether an image was encoded using the super-resolution mode. The image is encoded at a first resolution. Responsive to the flag indicating that the image was encoded using the super-resolution mode, bits indicating an amount of scaling of the image are decoded. The image is decoded from the encoded bitstream to obtain a reconstructed image at the first resolution, and the reconstructed image is upscaled to a second resolution using the amount of scaling to obtain an upscaled reconstructed image. The second resolution is higher than the first resolution. Loop restoration filtering is applied to the upscaled reconstructed image using loop restoration parameters to obtain a loop restored image at the second resolution.

Vector Quantization for Prediction Residual Coding
20230011893 · 2023-01-12 ·

Residual coding using vector quantization (VQ) is described. A flag indicating whether a residual block for the current block is encoded using VQ. In response to the flag indicating that the residual block is encoded using VQ, a parameter indicating an entry in a codebook is decoded, and the residual block is decoded using the entry. In response to the flag indicating that the residual block is not encoded using VQ, the residual block is decoded based on a skip flag indicating whether the current block is encoded using transform skip. The current block is reconstructed using the residual block.

ARTIFICIAL INTELLIGENCE-BASED IMAGE ENCODING APPARATUS AND METHOD AND DECODING APPARATUS AND METHOD

A method of decoding an image based on cross-channel prediction using artificial intelligence (AI) includes obtaining cross-channel prediction information by applying feature data for cross-channel prediction to a neural-network-based cross-channel decoder, obtaining a predicted image of a chroma image by performing cross-channel prediction based on a reconstructed luma image and the cross-channel prediction information, obtaining a residual image of the chroma image by applying feature data of the chroma image to a neural-network-based chroma residual decoder, and reconstructing the chroma image based on the predicted image and the residual image.

ARTIFICIAL INTELLIGENCE-BASED IMAGE ENCODING APPARATUS AND METHOD AND DECODING APPARATUS AND METHOD

A method of decoding an image based on cross-channel prediction using artificial intelligence (AI) includes obtaining cross-channel prediction information by applying feature data for cross-channel prediction to a neural-network-based cross-channel decoder, obtaining a predicted image of a chroma image by performing cross-channel prediction based on a reconstructed luma image and the cross-channel prediction information, obtaining a residual image of the chroma image by applying feature data of the chroma image to a neural-network-based chroma residual decoder, and reconstructing the chroma image based on the predicted image and the residual image.