A method for image decoding, according to the present invention, includes the following steps: receiving image information including a plurality of filter coefficients; generating a restored block for a current block on the basis of the image information; and applying an adaptive loop filter to the restored block on the basis of the plurality of filter coefficients. According to the present invention, image encoding efficiency may be improved, and complexity may be reduced.

A decoder includes a memory and processing circuitry. The processing circuitry, in operation, changes values of pixels in a first block and a second block to filter a boundary therebetween, using clipping such that change amounts of the respective values are within respective clip widths. The clip widths for the pixels in the first block and the second block are selected based on block sizes of the first block and the second block. The pixels in the first block include a first pixel located at a first position, and the pixels in the second block include a second pixel located at a second position corresponding to the first position with respect to the boundary. The clip widths include a first clip width and a second clip width corresponding to the first pixel and the second pixel, respectively, and the first clip width is different from the second width.

In prediction, one of a first mode for deriving, using pixels in an image including a target block, predicted pixels in the target block, a second mode for deriving the predicted pixels in the target block using pixels in an image different from the image including the target block, a third mode for generating the predicted pixels in the target block using both the pixels in the image including the target block and pixels in the different image can be used. If the third mode is used in at least one of the first and second blocks, the intensity of deblocking filter to be performed for the boundary between the first and second blocks is set to the same intensity as in a case in which the first mode is used in at least one of the first and second blocks.

According to embodiments described herein, sub-pictures and/or virtual boundaries can be used for coding an image. For example, sub-pictures in the current picture can be used for predicting, reconstructing, and/or filtering the current picture. Virtual boundaries can be used for filtering reconstructed samples of the current picture. Through image coding based on the subpictures and/or virtual boundaries according to embodiments described herein, the subjective/objective quality of an image can be improved, and the consumption of hardware resources necessary for the coding can be reduced.

A method by which a decoding device decodes an image, according to the present document, comprises the steps of: obtaining image information from a bitstream; generating a reconstructed picture of the current picture; deriving deblocking filter parameter information related to deblocking filter parameters on the basis of the image information; and performing deblocking filtering on the reconstructed picture on the basis of the deblocking filter parameters so as to generate a modified reconstructed picture.

In an image decoding device 200 according to the present invention, a decoding unit 210 is configured to decode a flag indicating whether chroma-related syntax is included in a picture parameter set, and in a case where the flag indicates that chroma-related syntax is included in the picture parameter set, the decoding unit 210 is configured to decode syntax for controlling deblocking filter processing of a Cb signal and a Cr signal.

A device includes a memory and one or more processors. The memory is configured to store an image enhancement network of an image enhancer. The one or more processors are configured to predict an image compression quality of an image of a stream of images. The one or more processors are also configured to configure the image enhancer based on the image compression quality. The one or more processors are further configured to process, using the image enhancement network of the configured image enhancer, the image to generate an enhanced image.

A device includes a memory and one or more processors. The memory is configured to store an image enhancement network of an image enhancer. The one or more processors are configured to predict an image compression quality of an image of a stream of images. The one or more processors are also configured to configure the image enhancer based on the image compression quality. The one or more processors are further configured to process, using the image enhancement network of the configured image enhancer, the image to generate an enhanced image.

A method implemented by a video coding apparatus includes applying a neural network (NN) filter to an unfiltered sample of a video unit to generate a filtered sample, where the NN filter is based on a first NN filter model having a first depth, or a second NN filter model having a second depth, where the depth comprises a number of residual blocks of the respective NN filter model, and where the second depth is different than the first depth. The method also includes performing a conversion between a video media file and a bitstream based on the filtered sample.

A signal-processing apparatus includes an instruction-parallel processor, a first data-parallel processor, a second data-parallel processor, and a motion detection unit, a de-blocking filtering unit and a variable-length coding/decoding unit which are dedicated hardware. With this structure, during signal processing of an image compression and decompression algorithm needing a large amount of processing, the load is distributed between software and hardware, so that the signal-processing apparatus can realize high processing capability and flexibility.