47 results about "Post filtering" patented technology

This disclosure relates to a receiver device for pulse amplitude modulation (PAM) signals. The receiver device calculates a transmitter dispersion eye closure quaternary (TDECQ). The receiver device first obtains a signal, wherein the signal is based on a PAM signal sent by a transmitter device over a channel to the receiver device, and filters the obtained signal. Further, the transmitter device equalizes the filtered signal using a FFE with multiple taps, and filters the equalized signal output by the FFE using a 2-tap post filter, wherein high frequency noise caused by the FFE is compressed. The receiver device applies a Max-Log-Map (MLM) algorithm on the filtered signal output by the 2-tap post filter, reconstructs a signal constellation of the PAM signal based on the result of the MLM algorithm, and calculates a TDECQ based on the reconstructed signal constellation.

Syntax elements allow to enable applying film grain using a neural network post-processing filter. Syntax elements define parameters related to the film grain neural network post- processing filter. An encoded video bitstream carries such syntax elements from an encoding device to a decoding device, thus allowing the encoding device to specify how to apply film grain using a neural network post-processing filter and the decoding device to apply the film grain neural network post-processing filter when displaying the decoded video. Additional syntax elements specify parameters comprising a film grain style, a film grain intensity, a film grain purpose or a region of interest where to apply the film grain.

Software products that are installed on a computer are identified from application names of application programs on the computer. The application names are pre-filtered to discard those that do not meet initial product filtering criteria that were used to collect sample data from which training datasets for training encoder-only transformer models were selected. Application names that meet initial product filtering criteria are classified using the encoder-only transformer models. Application names that have been classified by the encoder-only transformer models as those of supported products are post-filtered to discard those that do not meet the initial product filtering criteria of corresponding supported products. Application names that have not been discarded by the post-filtering are deemed to be those of software products installed on the computer.

The present disclosure relates to picture encoding and decoding of image regions on tile-basis. In particular, multiple components of an input tensor including a first and second component in spatial dimensions is processed within multiple pipelines. The processing of the first component includes dividing the first component in the spatial dimensions into a first plurality of tiles. Likewise, the processing of the second component includes dividing the second component in the spatial dimensions into a second plurality of tiles. The respective first and second plurality of tiles are then processed each separately. Among the first and second plurality of tiles there are at least two respective collocated tiles differing in size. In case of compression, the processing of the first and / or second component includes picture encoding, rate distortion optimization quantization, and picture filtering. In case of decompression, the processing includes picture decoding and picture filtering.

Neural-network-based picture encoding and decoding of image regions may be performed on a tile-basis. An input tensor representing picture data is processed by the neural network, which includes at least a first and second subnetwork. The first subnetwork is applied to a first tensor where the first tensor is divided in a spatial dimensions into a first plurality of tiles. The first tiles are then further processed by the first subnetwork. After application of the first subnetwork, the second subnetwork is applied to a second tensor where the second tensor is divided in the spatial dimensions into a second plurality of tiles. The second tiles are then further processed by the second subnetwork. Among the first and second plurality of tiles there are at least two respective collocated tiles differing in size.

The utility model belongs to the technical field of spinning boxes, and discloses a spinning box filter which comprises a filter frame, an auxiliary mechanism is arranged in the filter frame, and the auxiliary mechanism extends to the outer side of the filter frame; the auxiliary mechanism comprises a connecting rod, when the filter screen plate needs to be replaced or cleaned due to long-term use, two electric push rods can be started, after the two electric push rods are separated from two positioning grooves correspondingly, the filter screen plate is in an unlimited state, then a worker can rotate the filter screen plate, at the moment, the connecting rod can support the filter screen plate, and the filter screen plate is prevented from being damaged. When the distance between the filter screen plate and the brush plate reaches a certain distance, the filter screen plate can be pulled upwards and then rotated, and when the filter screen plate rotates to a proper angle, the filter screen plate can be finally taken out from the interior of the filter frame, and through the structure, the filter screen plate can be quickly taken out from the interior of the filter frame, so that the filter efficiency is improved. And subsequent cleaning and replacing work is completed, and the situation that the blocking risk still exists is avoided.

Systems, methods, and instrumentalities are disclosed associated with neural network post filter for energy adaptation. Messages associated with energy adaptation operations may be signaled and / or used. The messages may be associated with neural network post-filter characteristics (NNPFC) and / or supplemental enhancement information (SEI). The message may be an NNPFC SEI message. Adaptation in terms of energy consumption of content (e.g., decoded content) may be performed, for example, based on a received NNPFC SEI message. An NNPFC SEI message may enable reduction of energy consumption of a content while used. An NNPFC SEI message may enable increase of energy consumption of a content, for example, if the increase in energy is associated with an increased quality of experience (QoE) associated with the content.

An apparatus for adaptive input picture selection in a post filter bank is disclosed herein. The apparatus includes circuitry configured to: receive an encoding of at least one picture; receiving signaling comprising information related to a group of at least one post-processing filter; and using information relating to the group of at least one post-processing filter to infer whether and how at least one post-processing filter of the group of at least one post-processing filter is used for at least one picture; wherein the information indicates at least one of whether and how to use at least one post-processing filter in the group when a previous post-processing filter in the cascade outputs a number of pictures different from a number of pictures serving as an input to a current post-processing filter in the cascade, or whether and how at least one post-processing filter is applied in a hierarchical manner.

This paper introduces procedures for estimating noise covariance across resource blocks with similar noise distributions. These procedures lead to more accurate estimates of noise occurring in a given channel because accuracy can be improved by increasing the number of resource blocks examined, while also identifying and filtering out those contaminated by interference. In summary, these procedures represent an automated method for detecting imbalances between noisy resource blocks and resource blocks that also contain interference, then forming clusters of resource blocks with similar characteristics to provide more samples that can be used to estimate the noise covariance.

Specific syntax elements define energy characteristics of a neural network post-processing filter (NNPF) used in a video coding system. An encoded video bitstream carries such syntax elements from an encoding device to a decoding device using an extension metadata of a NNPFC-SEI message, thus allowing the encoding device to provide energy consumption information related to the NNPF and allowing the decoding device to handle its energy consumption by deciding whether or not it should apply the NNPF. An encoding method, a decoding method, an encoding apparatus and a decoding apparatus are described.

Specific syntax elements define a neural-network post-filter characteristics (NNPFC) supplemental enhancement information (SEI) message carrying information related to a tone mapping operation that can be applied as a post filter to the decoded image. This NNPFC SEI message may comprise information representative of the colour volume resulting from the tone mapping operation, information representative of characteristics of a target display and information representative of adaptation parameters, related to the adaptation of the luminance level, quality level and the energy adaptation level that result from the tone mapping operation are provided. The information representative of the colour volume resulting from the tone mapping operation may also be carried using a second SEI message. An encoding method, a decoding method, an encoding apparatus and a decoding apparatus are described.

According to a method of decoding an image to perform a machine vision task of the present disclosure, the method comprising decoding the image; applying a post-filter to a decoded image; obtaining, based on an output of the post filter, a restored image for the machine vision task, wherein the post-filter is trained based on a differentiable neural network based codec difference from a codec used to decode the image.

A method of processing video data. The method includes determining that a supplemental enhancement information (SEI) message of a bitstream includes indicators specifying one or more neural network (NN) filter model candidates or selections for a video unit or samples within the video unit, and converting between a video media file comprising the video unit and the bitstream based on the indicators. A corresponding video coding apparatus and non-transitory computer readable medium are also disclosed.

This disclosure relates generally to video coding, and more particularly to in-loop filtering for video coding for machine tasks based on neural networks. For example, utilization of one or more neural network in-loop filter (NNLF) may be determined (either enabled or disabled) at various coding levels. Such determination may be based on output of one or more other VCM-codec-related processed. The usages of the NNLF may be signaled in the bitstream or may be implicitly derived from the output of the one or more other VCM-coded-related processes during decoding process in a decoder or during in-loop decoding process of an encoder. The signaling may be provided at a corresponding constructed syntax structure at one the various coding levels. The NNLF may be applied at various orders with one or more other in-loop or post filters.

Specific syntax elements define energy characteristics of a neural network post-processing filter (NNPF) used in a video coding system. An encoded video bitstream carries such syntax elements from an encoding device to a decoding device, thus allowing the encoding device to provide energy consumption information related to the NNPF and allowing the decoding device to handle its energy consumption by deciding whether or not it should apply the NNPF. An encoding method, a decoding method, an encoding apparatus and a decoding apparatus are described.

Specific syntax elements define energy characteristics of a neural network post-processing filter (NNPF) used in a video coding system. An encoded video bitstream carries such syntax elements from an encoding device to a decoding device using a NNPFC mode metadata of a NNPFC-SEI message, thus allowing the encoding device to provide energy consumption information related to the NNPF and allowing the decoding device to handle its energy consumption by deciding whether or not it should apply the NNPF. An encoding method, a decoding method, an encoding apparatus and a decoding apparatus are described.

Systems, methods, and instrumentalities are disclosed associated with neural network post filter for energy adaptation. Messages associated with energy adaptation operations may be signaled and / or used. The messages may be associated with neural network post-filter characteristics (NNPFC) and / or supplemental enhancement information (SEI). The message may be an NNPFC SEI message. Adaptation in terms of energy consumption of content (e.g., decoded content) may be performed, for example, based on a received NNPFC SEI message. An NNPFC SEI message may enable reduction of energy consumption of a content while used. An NNPFC SEI message may enable increase of energy consumption of a content, for example, if the increase in energy is associated with an increased quality of experience (QoE) associated with the content.

A mechanism for processing video data is disclosed. The mechanism includes determining that a plurality of neural network post-processing filters (NNPFs) or neural network post-processing filter banks (NNPFGs) defined in one or more supplemental enhancement information (SEI) messages share the same NNPF purpose. Conversion is performed between the visual media data and the bitstream based on the NNPF purpose.

Specific syntax elements define energy characteristics of a neural network post-processing filter (NNPF) used in a video coding system. An encoded video bitstream carries such syntax elements from an encoding device to a decoding device, thus allowing the encoding device to provide energy consumption information related to the NNPF and allowing the decoding device to handle its energy consumption by deciding whether or not it should apply the NNPF. An encoding method, a decoding method, an encoding apparatus and a decoding apparatus are described.

Various embodiments describe an apparatus, a method, and a computer program product. An example apparatus includes at least one processor; and at least one non-transitory memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to perform: storing the encoded video data in a video track of a file; obtaining a post neural network filter characteristic (NNPFC) supplemental enhancement information (SEI) message including a neural network representation (NNR) bitstream; storing the NNR bitstream as an item of the file; storing, in a file, an NNPFC SEI message that does not include the NNR bitstream; and associating, in the file, the item with an NNPFC SEI message that does not include the NNR bitstream.

The utility model belongs to the technical field of picrasma quassioides extract production, and discloses a picrasma quassioides post-extraction filtering device which comprises a box body assembly used for containing an extracting solution and evenly distributing the extracting solution, and a driving assembly used for driving rotary filtering is arranged in front of the box body assembly. The filter assembly is arranged behind the driving assembly and is used for circularly rotating and filtering the concave filter screen; a residue removal assembly for scraping and collecting filter residues is arranged on one side below the filter assembly; the filtering assembly comprises two driving rollers symmetrically arranged on the two sides, and two first corner rollers are symmetrically arranged on the opposite sides of the two driving rollers. According to the picrasma quassioides post-extraction filtering device disclosed by the utility model, the filter screens are continuously switched through the arrangement of circulating rotary filtering, so that the filter screens are prevented from being blocked to influence the filtering speed; through the arrangement of scraping and collecting filter residues, the filter residues are cleaned, and blockage caused by adhesion of the filter residues is avoided; and through the arrangement of the concave filter, the filtrate is prevented from leaking along with circulating rotation.

A device may be configured to perform filtering based on information included in a neural network post-filter characteristics message. In one example, the neural network post-filter characteristics message includes syntax elements specifying a height and width of a luma sample array of a picture resulting from applying a neural network post-filter.

Systems, methods, and instrumentalities are disclosed for defining and using offset-based post filters with adaptation parameter set (APS) types configured to store corresponding parameter sets. For example, a device may determine an offset-based post filter for a slice based on a reference to an adaptation parameter set (APS) ID list. The apparatus may decode each coding tree unit (CTU) of the slice based on the determined offset-based post filter and the APS ID list. The device may parse the APS of the slice and may decode one or more parameter sets of the APS.

A mechanism for processing video data is disclosed. The mechanism includes determining that a neural network post-processing filter characteristic (NNPFC) supplemental enhancement information (SEI) message having a particular neural network post-processing filter characteristic (NNPFC) identification (nnpfcid) value and an NNPFC base flag (nnpfcbaseflag) equal to 1 in a coding layer video sequence (CLVS) has the same SEI load content. A conversion between the visual media data and the bitstream is performed based on the determination.

The application provides a large model anti-learning method and system based on post-filtering and repeated thinking, and a medium. The method comprises the following steps: receiving a prompt word input by a user, prefix compiling and filling the prompt word input by the user; processing the prompt word based on a large model to generate preliminary response content; analyzing whether the prompt word processed by the large model and the preliminary response content trigger a repeated thinking process; if the repeated thinking process is triggered, optimizing the input prompt word based on the preliminary response content, generating new response content, and performing safety evaluation on the new response content; if the repeated thinking process is not triggered, directly outputting the preliminary response content; through prefix compiling and filling, the information processing capability of the large model is used to safely process the prompt word input by the user, a classifier module is used to safely evaluate the model output, the repeated thinking process is introduced, and when a fuzzy case is encountered, the repeated thinking is triggered for multiple rounds of verification, and the decision reliability is significantly improved.

A first flag in a frame header of a current frame indicates whether a post-reconstruction filtering process is performed for the current frame. When the process is performed, a second flag indicates whether a post-reconstruction filtering syntax for the post-reconstruction filtering process of a previously decoded frame is reused for the current frame. The post-reconstruction filtering syntax can be a frame-level syntax or a block-level syntax. When the second flag indicates that frame-level post-reconstruction filtering syntax of the previously decoded frame is reused for the current frame, a third flag may indicate whether the block-level post-reconstruction filtering syntax of a previously decoded frame is reused for the current frame. The post-reconstruction filtering syntax, whether the frame-level, the block-level, or both, is used for the post-reconstruction filtering process unless new syntax is coded for the current frame.

A neural network-based post-filter for video coding is described, and a method, apparatus, and medium for processing video data are provided. The method comprises: deriving, for an encoder and a decoder, one or more neural network (NN) filter model indices and / or availability of one or more NN filter models from supplemental enhancement information (SEI) messages of video units of a video media file in the same manner; and performing a conversion between the video media file and the bitstream based on the one or more NN filter model indices and / or the availability of the one or more NN filter models.

In some embodiments, a pitch filter for filtering a preliminary audio signal generated from an audio bitstream is disclosed. The pitch filter has an operating mode selected from one of either: (i) an active mode where the preliminary audio signal is filtered using filtering information to obtain a filtered audio signal, and (ii) an inactive mode where the pitch filter is disabled. The preliminary audio signal is generated in an audio encoder or audio decoder having a coding mode selected from at least two distinct coding modes, and the pitch filter is capable of being selectively operated in either the active mode or the inactive mode while operating in the coding mode based on control information.

A constant pressure and constant liquid level control method for a glass utility water pump house, belonging to the technical field of float glass manufacturing, solves the problem of how to design a constant pressure and constant liquid level control method with a short adjustment time and good dynamic performance; the pressure and liquid level signals of the water pump house fed back by an external transmitter are filtered for high-order harmonics in the signal after passing through an advanced low-pass filtering link, and then the differential judgment link is used to collect the pressure and liquid level data, find the difference and divide by the interval time to obtain the change rate, and finally the constant pressure and constant liquid level control signal of the water pump house is output through an improved incremental PID link; the advanced low-pass filtering link of the present invention eliminates high-order harmonics in the signal after signal acquisition, optimizing the input signal; the differential judgment link is added to dynamically balance and improve the execution efficiency of the change algorithm, greatly shortening the adjustment time; the improved incremental PID link dynamically adjusts the proportional gain to avoid generating an integral saturation area, making its dynamic performance better.

A mechanism for processing video data is disclosed. The mechanism includes determining a supplemental enhancement information (SEI) message contains a non-binary syntax element indicating usage of a neural-network post-filter (NNPF). A conversion can then be performed between a visual media data and a bitstream based on the NNPF and the non-binary syntax element.