16 results about "Temporal noise" patented technology

The invention discloses a multi-camera correction method and system and a medium, and the method comprises the steps: controlling a sampling condition, and analyzing the system gain of each camera; based on the ratio of the standard gain to the system gain, the correction coefficient of each camera is determined to correct each camera, so that the responsivity of each camera after correction is consistent; the method comprises the following steps of: extracting multiple frames of images acquired by the same camera, calculating a time domain noise value of each camera, determining a noise correction coefficient of each camera by adopting a ratio of a standard time domain noise value to the time domain noise value of each camera, and performing noise filtering on a gray value of each pixel point in the images acquired by the cameras according to the noise correction coefficient of each camera, therefore, the noise consistency adjustment of each camera is realized. According to the method, the effect that the noise level is consistent on the premise that the responsivity of the cameras is consistent is achieved, and the universality of the cameras of the same model or different models is improved.

The invention relates to the technical field of video generation, in particular to a space-time attention and optical flow constrained video generation method and system, and the system comprises a CLIP text encoder, a multi-frame potential noise initialization module, space-time attention U-Net, an optical flow prediction module, a dynamic path optimizer, a space-time noise scheduling module and a video frame decoder. By embedding physical constraints into a generation process, four-dimensional joint optimization of space, time, noise and semantics is realized, space-time attention U-Net is combined with 3D convolution and cross-frame attention modeling space-time dependence, and an optical flow prediction module optimizes a motion trail through residual compensation. The problems of inter-frame jitter and long-range motion breakage are effectively solved, the PSNR fluctuation is smaller than or equal to 0.5 dB, the Warping precision reaches 0.85, the video memory is reduced by 25%, the reasoning speed is increased by three times, 1080P and 30fps real-time generation is supported, and the video quality and the generation efficiency are improved.

Apparatuses, systems, and techniques to generate blue noise masks for real-time image rendering and enhancement. In at least one embodiment, a vector-valued noise mask is generated and applied to one or more images to generate one or more enhanced images for image processing (e.g., real-time image rendering). In at least one embodiment, the noise mask includes vector values per pixel and is able to handle the temporal domain (e.g., add time to the spatial domain) to improve image quality when rendering images over multiple frames.

Content transparency control implemented on a central processing unit, or a graphics processing unit to post-process live video content requires direct access to double data rate memory and can demand significant amounts of power. A solution addresses this issue by exploiting temporal noise reduction hardware and software already included in an image signal processor. The temporal noise reduction hardware and software are modified to support content transparency control in tandem with temporal noise reduction. Specifically, the feedback weight map and the output weight map used in temporal noise reduction to blend an input image and a retrieved reference image can be controlled based on a semantic map to effectuate content transparency control.

This invention proposes a high-precision method for measuring airflow thrust by extracting the Doppler frequency shift difference from the scanning absorption spectrum. A tunable laser performs forward and reverse scanning of the absorption spectrum. The laser wavenumber scanning waveform is symmetrical about the lowest wavenumber point. The laser beam is split into two beams, which cross the longitudinal section of the airflow center. The target gas absorption spectrum curve is obtained by measuring the laser intensity curve. The sum of the central wavenumbers of the absorption spectrum in both forward and reverse scans along the airflow path is calculated, as is the sum of the central wavenumbers in both forward and reverse scans against the airflow path. The Doppler frequency shift difference is extracted from the difference between the two sums of central wavenumbers, thus measuring the airflow velocity. The static temperature of the airflow is obtained using colorimetric thermometry, and the static pressure of the airflow is obtained using a nonlinear fitting method. The thrust is calculated by combining the airflow velocity, static temperature, and static pressure. This invention achieves airflow velocity measurement resistant to temporal noise interference and has significant application prospects in the field of integrated space-ground thrust measurement for engines.

A method of an optical navigation device to be coupled to a host device includes: providing a pixel array circuit to capture and generate an image frame; performing a bandpass filter operation upon the image frame to remove a low-frequency image noise and a high-frequency image noise from the image frame so as to generate a bandpass-filtered image frame; and performing a correlation operation upon the bandpass-filtered image frame and a reference image frame to generate a displacement result between the bandpass-filtered image frame and the reference image frame as a motion result of the optical navigation device; the displacement result is to be reported to the host device if the displacement result indicates a motion.

Example non-limiting technology herein provides several specific approaches for making CWTOF lidar more flexible and amendable to waveform controls. A first method examines how different mathematical wave models can be applied to the continuous wave approach to increase accuracy and reduce calibration burden. Second, an example is described of how carrier waveforms can be modulated with the continuous waveform and then demodulated prior to summation in order to improve noise rejection from both environmental and electronic sources. Third, an example is presented of how DCS frames can be updated with every sample rather than every 5th sample as commonly done (4 DCS frames and 1 ambient frame), which is especially advantageous for tracking faster objects. Fourth, an example of post-collection DCS frame signal processing is given that significantly reduces temporal noise. Fifth, a method is shown for using alternate frames at different integration times to significantly increase the dynamic range of the system. Sixth, an approach for integrating data from the CWTOF lidar with data from an amplitude map (e.g. B&W camera) can be used to form and track objects.

In a method of processing an image, a first composite frame image corresponding to an n-th input frame image is generated by performing a first temporal noise reduction operation based on the n-th input frame image and an (n−m)-th input frame image. The (n−m)-th input frame image is received prior to the n-th input frame image. A second composite frame image corresponding to the n-th input frame image is generated by performing a second temporal noise reduction operation based on the n-th input frame image and an (n+k)-th input frame image. The (n+k)-th input frame image is received subsequent to the n-th input frame image. The second composite frame image is provided as an n-th output frame image corresponding to the n-th input frame image.

This document describes various techniques for monitoring noise to assess sensor aging in systems and applications. The systems and methods described herein can monitor sensors—for example, at given time intervals and / or continuously—to generate information representing sensor noise. For instance, data (e.g., sensor data) received from a sensor are used to determine noise (e.g., temporal noise) associated with points (e.g., pixels) corresponding to the sensor. This noise is then used to generate representations—such as histograms—of noise distributions associated with the sensor. The systems and methods described herein can also monitor this noise information generated for the sensors to detect degradation in performance as the sensors age, such as specific components of the noise distributions.

The present disclosure relates to spatio-temporal noise masks and sampling using vectors for image processing and light transport simulation systems and applications, and in particular to apparatuses, systems, and techniques for generating blue noise masks for real-time image rendering and augmentation. In at least one embodiment, a vector-valued noise mask is generated and applied to one or more images to generate one or more augmented images for image processing (e.g., real-time image rendering). In at least one embodiment, the noise mask includes a vector value per pixel and is capable of handling the temporal domain (e.g., adding time to the spatial domain) to improve image quality when rendering images over multiple frames.

Disclosed are a data generation method and apparatus, a product, a device, and a medium. The method comprises: obtaining a feature set, and an input noise image of a diffusion network, the feature set comprising an image feature of a target image and indication features of N pieces of indication data, wherein the target image comprises a first object, and the N pieces of indication data are all used for indicating a target content on which the first object is to simulate language expression; calling the diffusion network to perform temporal noise prediction processing on the input noise image under the constraint of the feature set, so as to generate M noise prediction features; and performing transformation processing on the M noise prediction features on the basis of the input noise image, so as to generate a simulated video of the first object, wherein the simulated video is a video in which the first object simulates language expression on the target content, and each noise prediction feature is used to transform and generate one corresponding video picture frame in the simulated video. By means of using the present application, the generation effect of a simulated video of a first object can be improved.

Embodiments comprise a decoder for decoding a digital waveform signal, DWS, from a data stream using block-based transform decoding, wherein the decoder is configured to decode a spectrum for a current block of the DWS from the data stream, decode a mode signal from the data stream, which mutually exclusively indicates a selected mode out of a temporal noise shaping, TNS, mode and a noise synthesis, NS, mode. Furthermore, the decoder is configured to subject the spectrum to TNS filtering, in case of the selected mode being the TNS mode; and the decoder is configured to subject the spectrum to NS, in case of the selected mode being the NS mode. In addition, respective encoders, methods for decoding, methods for encoding computer programs and bitstreams are disclosed.

A method of an optical navigation device to be coupled to a host device includes: providing a pixel array circuit to capture and generate an image frame; performing a bandpass filter operation upon the image frame to remove a low-frequency image noise and a high-frequency image noise from the image frame so as to generate a bandpass-filtered image frame; and performing a correlation operation upon the bandpass-filtered image frame and a reference image frame to generate a displacement result between the bandpass-filtered image frame and the reference image frame as a motion result of the optical navigation device; the displacement result is to be reported to the host device if the displacement result indicates a motion.

This invention discloses an infrared spatiotemporal noise generation method based on hybrid neural representations. The method includes establishing an infrared denoising dataset containing paired indoor noise-clear video and unpaired outdoor noise-clear video; constructing an infrared spatiotemporal noise model based on hybrid neural representations and its training loss function; and building a spatiotemporal noise generator G and a spatiotemporal discriminator. This invention employs a divide-and-conquer approach, independently exploring the noise synthesis path from both spatial and temporal dimensions. By constructing a hybrid neural representation of noise, it deeply integrates the spatial and temporal embeddings of noise and implicitly models the complex spatiotemporal distribution of infrared noise through recurrent adversarial learning. This comprehensively and deeply characterizes the spatiotemporal properties of noise, providing new ideas and tools for noise modeling and analysis in the field of video processing.

This invention discloses a method for monitoring space debris, belonging to the field of space debris monitoring technology. This invention significantly improves the reliability of debris monitoring by low-Earth orbit satellites in maneuvering states through the deep integration of physical models and deep learning. A plume diffusion physical field model accurately characterizes the interference generation mechanism, a generative adversarial network (GAN) enables dynamic stripping of interference features, a multi-scale residual network enhances the micro-motion characteristics of debris, and optical flow alignment suppresses temporal noise. An online learning framework overcomes the bottleneck of satellite-ground collaboration, enabling autonomous evolution and updating of model parameters. This invention systematically solves the false alarm problem caused by plume interference without changing existing onboard hardware, while simultaneously improving the detection sensitivity for non-metallic debris and ensuring the autonomous monitoring capabilities of the satellite constellation.

The invention discloses an optical navigation device and a method thereof, and the method comprises the steps: providing a pixel array circuit, so as to capture and generate an image frame; performing band-pass filtering operation on the image frame by using an image band-pass filtering circuit to remove low-frequency image noise and high-frequency image noise in the image frame so as to generate an image frame after band-pass filtering; and performing correlation operation on the image frame after band-pass filtering and a reference image frame to generate a displacement result between the image frame after band-pass filtering and the reference image frame as a motion result of the optical navigation device, if the displacement result indicates motion, the displacement result is reported to the host device. According to the method, fixed pattern noise and time noise can be reduced, and quality reduction of correlation operation is avoided.