72 results about "Temporal filtering" patented technology

In various examples, the present disclosure relates to using temporal filters for automated real-time classification. The technology described herein improves the performance of a multiclass classifier that may be used to classify a temporal sequence of input signals—such as input signals representative of video frames. A performance improvement may be achieved, at least in part, by applying a temporal filter to an output of the multiclass classifier. For example, the temporal filter may leverage classifications associated with preceding input signals to improve the final classification given to a subsequent signal. In some embodiments, the temporal filter may also use data from a confusion matrix to correct for the probable occurrence of certain types of classification errors. The temporal filter may be a linear filter, a nonlinear filter, an adaptive filter, and / or a statistical filter.

The invention provides an infrared image flicker processing method, system and device and a medium. The method comprises the steps of generating a blocking piece mean value based on blocking piece image data of continuous N frames obtained during single-point correction; processing the histograms of the two-time single-point correction gap images according to the separation blade mean value to generate a statistical histogram of the images; performing first filtering processing on the statistical histogram to generate a first filtering result of the histogram; after the first filtering result is calculated in an accumulated mode, a gray mapping table is calculated, second filtering processing is carried out, and a second filtering result of the gray mapping table is generated; and performing time domain filtering processing on the second filtering result to realize flicker processing of the infrared image. According to the infrared image flicker processing method, the flicker phenomenon of the infrared image can be effectively reduced, and the stability and the visual effect of the image are improved.

Methods and apparatus for a lidar system having spatio-temporal filtering to reduce false alarms in image data. In embodiments, the probability of a lidar return being real and not a false alarm is calculated based on both the current and historical presence of other returns which are spatially adjacent to the return being calculated. The probability is used to filter false alarms through thresholding.

Systems and methods herein are for a video encoder to be associated with a temporal filter and a coding tree and that can perform a main pass for video encoding using individual video blocks towards prediction of at least one frame associated with the media stream, where the coding tree is associated with a lookahead pass, and where the temporal filter can enable denoising within the lookahead pass to reduce an effect of noise in one or more of motion estimation or mode selection of the video encoding.

In various embodiments, when reference picture resampling is applied to achieve better coding efficiency, methods and devices adapt temporal filtering of a noise-reduced input video prior to encoding according to a resolution ratio. According to one embodiment, temporal filtering strength values are fine-tuned at a pre-processing module according to the resolution ratio of the RPR mode. According to another embodiment, temporal filtering is deferred after rescaling when the RPR mode is enabled, and filtering strength values are fine-tuned according to the resolution ratio of the RPR mode. A third embodiment proposes to refine motion estimation in the encoder by setting the block size of motion estimation in temporal filtering according to the resolution ratio of the RPR mode.

Reduce signal bandwidth tilt. [Solution] The optical receiver 100 receives and processes the received optical signal received via the optical transmission path. The optical receiver 100 includes a DSP 105 that outputs information regarding the deviation of the amplitude characteristics of the received signal (intraband tilt), a TOF 101 that filters the received signal, and a control unit 106 that controls the settings of the TOF 101 based on the intraband tilt. For example, the control unit 106 reduces the intraband tilt by variably controlling the center frequency of the TOF.

This disclosure provides video encoding methods, apparatus, electronic devices, storage media, and programs. [Solution] The specific solution includes: obtaining a reference frame adjacent to the current frame and in which a hierarchical partitioning of the initial region of interest (ROI) has been established; reusing motion vectors generated during the motion-compensated time filtering process in the reference frame to determine the predicted ROI position of the current frame; extracting sensory feature points from the current frame and correcting the predicted ROI position based on the feature point spatial topology relationship in the initial ROI; assigning differentiated quantization parameters to the corrected primary face region, secondary face region, and background region, respectively; dynamically allocating the bitrate of the three layer regions based on real-time network bandwidth; and outputting the encoded frame of the current frame and associated ROI hierarchical metadata.

The application relates to a time filtering method, device, computer equipment, chip and medium, which comprises the following steps: acquiring a to-be-filtered signal corresponding to a current filtering number; determining target reference data corresponding to the current filtering number according to the current filtering number; determining a time filtering coefficient corresponding to the current filtering number according to the target reference data; and performing filtering processing on the to-be-filtered signal corresponding to the current filtering number according to the time filtering coefficient. The application can improve the filtering effect.

A system and method for identifying container numbers on front-mounted cranes are disclosed, relating to the field of container number identification on front-mounted cranes. To address the shortcomings of existing methods, such as inability to adapt to rainy or snowy weather and low-light conditions, poor container number identification performance, and poor anti-interference capabilities, this invention acquires video or images of containers on front-mounted cranes; extracts continuous frames from the video at a fixed frequency and performs grayscale processing on each frame to reduce computational complexity; applies temporal filtering to the preprocessed video / image; applies spatial filtering to the filtered video / image to remove isolated noise points; reduces high-frequency noise and smooths the image through weighted averaging; enhances image contrast by adjusting the grayscale distribution of the image, making the container number area clearer; and performs container number area detection and character recognition on the processed image to achieve automatic container number identification. This invention is mainly used for identifying container numbers on front-mounted cranes.

This invention provides a method and apparatus for superconducting motor quench detection based on sliding time filtering, relating to the field of superconducting motor quench detection technology. The method includes: differentially processing the terminal voltage signals of adjacent superconducting rotor magnets in the superconducting motor; conducting three trial runs of the superconducting motor before quench detection to obtain interference frequency data; establishing sliding time windows with both long and short time scales during the actual operation of the superconducting motor, and performing notch filtering on the differential voltage signals of adjacent superconducting rotor magnets; performing linear regression fitting on the filtered signals within the sliding time windows to extract effective quench signal feature values; and establishing a quench protection criterion based on the quench feature values. This invention solves the problem of achieving high reliability and rapid response in quench detection technology under the complex interference environment of superconducting motor rotation operation, a problem that is difficult to address in existing technologies.

The invention relates to a method for directional signal processing of signals of a microphone arrangement comprising a first microphone generating a first input signal from ambient sound and a second microphone generating a second input signal from ambient sound, wherein a reference signal is formed from the first input signal, wherein the reference signal is transformed into the frequency domain and a frequency space reference signal is generated, wherein the first and second input signal are each transformed into the frequency domain and a first frequency space directional signal is formed in the frequency domain from the so transformed first and second input signal, wherein a frequency-dependent first amplification factor is generated from a frequency-resolved comparison of the frequency space reference signal with the first frequency space directional signal or a signal derived from the first frequency space directional signal in the frequency domain, wherein a time filter is generated in the time domain from the first amplification factor, and wherein the reference signal is filtered by means of the time filter and an output signal is generated from the filtered reference signal.

This invention provides an automatic cleaning method and system for the hangar door side of polar shipborne helicopters. This invention belongs to the technical field of aviation ground support equipment and ship auxiliary machinery. The cleaning method includes: acquiring helicopter images, extracting key features of the fuselage, identifying the aircraft type and calculating the initial pose based on the PnP algorithm, and converting the preset cleaning path to the coordinate system of the cleaning device; generating a propeller cleaning sub-path, employing a master-slave control strategy to control two robotic arms to synchronously flush and clean the upper and lower surfaces of the propeller blades, and maintaining the balance of jet impact force through pressure closed-loop feedback; establishing a ship swaying dynamics model to estimate and predict the ship's motion state in real time, and combining the real-time feedback deviation vector obtained from laser ranging and visual acquisition to generate a corrected speed command; identifying the surface state category through temporal filtering and texture analysis, and adaptively adjusting according to the identification results.

The invention discloses a bare soil intelligent identification method and system of a high-resolution remote sensing image, and relates to the technical field of ecological environment remote sensing monitoring, high-resolution remote sensing image data of a to-be-identified area is acquired and preprocessed, and preprocessed high-resolution remote sensing image data is obtained; performing filtering optimization on the preprocessed high-resolution remote sensing image data by adopting a dynamic adaptive multi-temporal filtering optimization method to obtain an optimized high-resolution remote sensing image data image; cutting the optimized high-resolution remote sensing image data, extracting contour position coordinates of a mask image, and constructing a training set; and inputting the training set into a bare soil recognition model for training to obtain a trained bare soil recognition model, and recognizing the bare soil plaques of the to-be-recognized region based on the trained bare soil recognition model. The multi-scale bare soil plaques under a complex background are accurately and automatically identified under a relatively low computing resource demand, and the distinction degree between the bare soil and other ground features is enhanced.

This paper presents a method for fusing and reconstructing trajectory data from multiple sources in hybrid traffic flow, relating to the fields of multi-source sensor fusion localization and target tracking. The method acquires the 3D acceleration sequence and RGB video stream of the target object, extracting the geometric center coordinate sequence. Based on the frequency domain energy distribution of acceleration, the target's fundamental frequency parameters are obtained. Temporal filtering coefficients are constructed using the dynamic sampling rate of the video, and the geometric center coordinates are filtered to obtain a corrected center coordinate sequence, which is then mapped to a measurement vector. Kinematic state prediction is performed using acceleration to obtain prior inferred state variables, and then posterior updates are performed using the measurement vectors to obtain the optimal spatial position. The reconstructed trajectory sequence is generated by stitching the data together, and the sliding time window is updated based on feedback-optimized parameters. This method effectively eliminates spurious displacements caused by gait, fundamentally eliminating jagged oscillations in the trajectory, resulting in a smooth and stable fused trajectory.

The application relates to a high-precision positioning method based on angle information fusion estimation, and belongs to the technical field of wireless positioning algorithms, which comprises the following steps: establishing a benchmark antenna coordinate model; establishing an IQ data frame model according to a CTE protocol model; applying time filtering to the IQ data frame model in the time domain; constructing a mean reference phase difference and an angle phase difference matrix for the IQ data frame model after time filtering processing, and constructing a multi-phase difference composite signal model; constructing a signal covariance matrix by using the multi-phase difference composite signal model, applying spatial smoothing filtering to the signal covariance matrix; and fusing a dimension-reduced signal steering vector obtained by applying spatial smoothing filtering to the signal covariance matrix and a dimension-reduced noise subspace into angle estimation. The application starts from a two-dimensional antenna array spatial coordinate and an IQ data frame model, angle fusion estimation is carried out by using a hierarchical method, and the technical problem of low positioning precision of a two-dimensional antenna array in an indoor environment is solved.

The invention discloses a preset time adaptive control method and system for a high-order nonlinear MIMO system, and relates to the technical field of industrial control. The method comprises the following steps: establishing a dynamic model of a high-order nonlinear MIMO system, and approaching an unknown nonlinear function in the dynamic model by using a neural network; determining a tracking error based on the dynamic model; constructing a virtual control law based on the tracking error and defining a virtual error; constructing a preset time filter to process the virtual control law, and determining a filtering error; the parameter of the preset time filter is configured to enable the filtering error to converge in the preset time; under a backstepping recursion framework, combining a tracking error, a virtual error and a filtering error, and adopting an improved weighted integral technology to design an actual control law; and setting an event triggering mechanism based on a relative threshold value to modulate the actual control law and then output a control signal. The system stabilization time can be directly preset without being influenced by the initial state, and meanwhile the updating frequency of the controller is reduced.

A neural network-based medical image processing apparatus according to the present invention, which identifies a small intestine region from a medical image acquired by a capsule endoscope, comprises: a memory equipped with an organ identification algorithm for performing organ identification from the medical image; and a processor for applying the medical image to the organ identification algorithm such that the small intestine region is identified. The organ identification algorithm includes: a convolutional neural network algorithm for identifying an organ included in the medical image as the stomach, the small intestine, and the large intestine to identify the small intestine region therefrom; and a temporal filtering algorithm linked to the convolutional neural network algorithm to reduce images which may be misidentified by the convolutional neural network algorithm.

Embodiments described relate to adjusting one or more pixel values in a region corresponding to an image artifact based on one or more spatial characteristics and one or more temporal characteristics to reduce or eliminate the image artifact. An electronic device may employ spatio-temporal filtering circuitry that includes spatial adjustment circuitry, temporal adjustment circuitry, and / or fuse circuitry. The spatial adjustment circuitry may perform a spatial adjustment of image data in the region of the image frame. Moreover, the temporal adjustment circuitry may perform a temporal adjustment of the image data in the region of the image frame. The fuse circuitry may then merge the spatially adjusted image data and the temporally adjusted image data in the region of the image frame.

The invention provides an insulation defect identification method, system and device for power equipment and a medium, and the method comprises the steps: obtaining a partial discharge signal, and extracting a multi-resolution time-frequency feature of the partial discharge signal through a preset window width through Gabor transformation; inputting the multi-resolution time-frequency characteristics into a pre-trained insulation defect identification model, and obtaining an identification result of the insulation defect type of the power equipment based on the output of the insulation defect identification model; wherein the insulation defect identification model is configured with a frequency filter, a time filter and a texture filter, the frequency filter, the time filter and the texture filter respectively adopt convolution kernels of different sizes, and the frequency filter, the time filter and the texture filter are respectively used for processing time-frequency characteristics of different resolutions. According to the invention, the accuracy of insulation defect type identification can be improved.

The invention provides a bridge displacement monitoring method and system based on phase information, and the method comprises the steps: carrying out the pyramid decomposition of multi-scale direction decomposition on processed video data, carrying out the filtering of a phase spectrum in a time domain, extracting an interested frequency band, and amplifying the phase spectrum; obtaining a structure displacement signal according to the amplification signal and the center phase, and generating a pixel point displacement signal based on the structure displacement signal; establishing a physical coordinate system in each frame of image in the video data, converting the physical coordinate system into a modal coordinate system, mapping the pixel point displacement signal on the modal coordinate system, and taking the pixel point displacement signal on the modal coordinate system as an input signal; and constructing a modal analysis model, and identifying the modal response of the input signal based on the modal analysis model to obtain bridge monitoring information. According to the invention, the displacement information of the bridge can be accurately and comprehensively monitored.

The application discloses a kind of based on motion compensation time domain filtering method for image, comprising: using autoregressive moving average model to the obtained gyroscope error is modeled, the change rule of data is used to estimate model parameter, and gyroscope error model is established;Using the gyroscope data of removing error obtained by gyroscope error model, the rotation matrix of camera is calculated, and the rotation image is compensated in reverse using rotation matrix, and the de-rotation image is obtained.Through kalman filtering to image motion vector sequence, image random jitter is obtained, and the de-rotation image is compensated according to random jitter, and the stable image and the subjective motion vector of image are obtained;Using the motion target detection algorithm in difference map based on large map coordinate system to detect target in stable image.The application has high detection sensitivity, and can detect target and its trajectory quickly through a small amount of frame track correlation.

An electronic device includes memory and motion compensated temporal filtering (MCTF) circuitry communicatively coupled to the memory. The MCTF circuitry is configured to receive a plurality of motion vectors. The MCTF circuitry is also configured to retrieve a plurality of source pixel values and a plurality of reference pixel values from the memory. The plurality of source pixel values and the plurality of reference pixel values correspond to the plurality of motion vectors. The MCTF circuitry is further configured to determine motion vector edge statistics based on the plurality of motion vectors. The MCTF circuitry is further configured to generate a plurality of filtered pixel values by filtering the plurality of source pixel values based on the plurality of reference pixel values and the motion vector edge statistics.

The invention provides an image encoding method and an image encoding device. The image coding method comprises the steps that first quantization parameter information of a code rate control unit block in an image to be filtered is acquired, and the code rate control unit block represents a processing unit used for code rate distribution and image quality control; adjusting a filtering weight of a filtering block to be subjected to motion compensation time domain filtering in the bit rate control unit block based on the first quantization parameter information; performing motion compensation time domain filtering on the filtering block based on the adjusted filtering weight; and performing encoding based on the filtering result.

This invention discloses a method for constructing a real-time rendering engine for generative AI models and related equipment, relating to the field of human-computer interaction technology. The method includes acquiring multimodal semantic information from user input and converting it into latent vectors and constraint parameters; constructing a lightweight generative model and directly generating renderable intermediate representations using this model; building a rendering pipeline based on the generated intermediate representations to convert them into visualized images; capturing user operations in real-time and dynamically updating the constraints of the generative model to trigger incremental generation; optimizing system performance using model lightweighting, hardware acceleration, and hybrid rendering strategies; and ensuring temporal and spatial consistency of generated content through temporal filtering and spatial constraint techniques. This invention solves the problems of slow generation speed and low rendering efficiency in the fusion of generative AI models and real-time rendering engines, improving the efficiency and quality of visualized image generation and rendering.

Provided is a method for encoding a video, an electronic device and a storage medium, relating to the field of video encoding. The method includes: obtaining a reference frame that is adjacent to a current frame and has established hierarchical division of an initial ROI; reusing a motion vector generated by the reference frame in a motion compensated temporal filter process to determine an ROI position prediction value of the current frame; extracting facial feature points from the current frame, and correcting the ROI position prediction value based on a spatial topological relationship of feature points in the initial ROI; configuring differentiated quantization parameters for a main face region, a secondary face region and a background region after correction respectively; dynamically allocating a three-region bitrate according to a real-time network bandwidth; and outputting an encoded frame of the current frame and associated ROI-level metadata.

Methods, apparatus, and computer readable media for managing cross-link interference (CLI) are disclosed. In an embodiment, a method performed at a terminal device is provided. The method includes receiving a message from a base station regarding a CLI measurement configuration and a CLI reporting configuration for a sub-band non-overlapping full duplex (SBFD) mode of operation. The CLI measurement configuration indicates a measurement window duration, and the CLI reporting configuration indicates how to report first information about at least a portion of a time slot of the measurement window duration and second information about a value of the measured CLI in the at least a portion of the time slot of the measurement window duration. The method also includes performing a first CLI measurement per time slot within a measurement window duration without temporally filtering values of the measured CLI. The method further includes reporting a result of the first CLI measurement per slot to the base station based on the CLI reporting configuration.

The present disclosure relates generally to the field of video processing, and more particularly, to high dynamic range (HDR) image processing. In particular, the present disclosure relates to a method for determining a parameter set for a tone mapping curve. The method comprises obtaining a plurality of parameter sets, wherein each parameter set defines the tone mapping curve, and wherein each parameter set is derived based on one of a plurality of HDR video frames. Further, the method comprises temporally filtering the plurality of parameter sets to obtain a temporally filtered parameter set.

In various examples, updates to a dynamic seam placement and / or fitted 3D bowl may be at least partially concealed using spatial masking. A future time in which a predicted change in dynamic seam placement and / or fitted 3D bowl exceeds some threshold may be determined, and a predicted dynamic seam movement and / or fitted 3D bowl update may be spatially masked by triggering a viewport switch to coincide with (a) the predicted dynamic seam placement and / or fitted 3D bowl update and / or (b) a relaxation or disabling of temporal filtering. Additionally or alternatively to predicting that a future change will exceed a threshold, the determination of the change may occur based on a change between a current and previous frame. In some embodiments that employ viewport switching to spatially mask visualization updates, the switch may be to one of a plurality of candidate viewports for an applicable scene maintained in a scene catalog.