34 results about "Post filtering" patented technology

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.

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 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.

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

Embodiments described herein relate to a post filter set configured as parallel post filter branches. Each post filter branch includes a post filter, an upstream multi-position valve, and a downstream multi-position valve. Each the upstream and the downstream multi-position valves are actuatable to at least two configurations to enable backwashing and filter to waste operations using fewer valve operations. For backwashing, a head pressure from the combined output of other post filters in the post filter set is leveraged such that backwashing a particular post filter can be performed as a pumpless operation.

Embodiments described herein relate to a post filter set configured as parallel post filter branches. Each post filter branch includes a post filter, an upstream multi-position valve, and a downstream multi-position valve. Each the upstream and the downstream multi-position valves are actuatable to at least two configurations to enable backwashing and filter to waste operations using fewer valve operations. For backwashing, a head pressure from the combined output of other post filters in the post filter set is leveraged such that backwashing a particular post filter can be performed as a pumpless operation.

The invention belongs to the technical field of image processing, and particularly relates to a honey water bath decrystallization filtering effect detection method based on image processing, and the method comprises the steps: obtaining a honey liquid level image, extracting a plurality of micro target points, and determining the maximum radial boundary and angle sampling total number of each micro target point to construct a polar coordinate light intensity matrix; calculating a global light intensity integral and a light intensity difference value of adjacent angular sampling points based on the polar coordinate light intensity matrix to obtain an angular light intensity coherence index; obtaining a radial attenuation contrast according to the calculated light intensity of the core condensation area and the light intensity of the edge total reflection area; calculating a solid state coefficient according to the angular light intensity coherence index and the radial attenuation contrast; based on the relation between the solid state coefficient and the set blocking limit, the possible crystal residue number is obtained, and whether the detection reaches the standard or not is judged. According to the invention, fluid microbubbles and real tiny crystals are effectively distinguished, and the reliability of automatic quality control detection of honey is obviously improved.

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 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 for energy saving in video coding. A supplemental enhancement information (SEI) message may include a first syntax element that indicates whether energy information related to a neural network post-processing filter (NNPF) is present in the SEI message. The SEI message may further include a second syntax element that indicates whether information related to a complexity or a property of the NNPF is present in the SEI message. The video data may be encoded or decoded based on the SEI message.

The embodiment of the invention discloses a video encoding and decoding method, a video bit stream storing method or a video bit stream sending method, electronic equipment and a storage medium. A method of decoding a video includes: receiving a bitstream of a portion of the video; decoding the bit stream to obtain a reconstructed portion of the video; obtaining a neural network filter (NNLF) identifier from the bitstream, and extracting a set of filter parameters associated with the NNLF from the bitstream when it is determined that the NNLF is to be applied to a reconstructed portion of the video according to the NNLF identifier; determining a combination mode of the NNLF and at least one other loop or post-filter; and applying the NNLF having the set of filter parameters and the at least one other loop or post-filter to the reconstructed portion of the video according to the combination to generate a filtered reconstructed portion of the video, where the neural network filter is a neural network loop filter or a neural network post-filter.