47 results about "Ring Artifact" patented technology

The invention provides a method and system for removing ring artifacts of a CT image and a storage medium, and the method comprises the steps: obtaining original projection data corresponding to the CT image of which the ring artifacts are to be removed, classifying the original projection data according to scanning parameters during the scanning of CT equipment, and obtaining a plurality of projection classification data; calculating the mean projection of each piece of projection classification data; reconstructing the mean projection of each projection classification data to obtain the reconstructed mean reconstruction projection of each projection classification data; and removing ring artifacts according to the difference between the mean projection and the mean reconstruction projection of the projection classification data. According to the method, in order to accurately remove the ring artifacts, regression and strip artifact correction are respectively carried out on each classified mean value projection, so that the segmentation continuous attribute of the strip artifacts in the projection domain is fully utilized, the ring artifacts are removed, and the accuracy and efficiency of removing the ring artifacts are improved.

The invention discloses a generative adversarial network image enhancement method combined with frequency domain information, relates to the technical field of computer vision, and solves the problems of spectrum leakage, ringing artifacts, splicing strips and structural dislocation easily caused by the existing frequency domain image enhancement method. The specific scheme is as follows: receiving a degraded image and extracting multi-scale features and boundary section features; the method comprises the following steps of: performing overlapping partitioning and periodic continuation expansion on the basis of features, performing spectral analysis on an expansion block to generate a parameterized window function and performing windowing, then obtaining a preliminary reconstructed image through complex field correction and overlapping perception mixed inverse transformation, and finally performing optimization reconstruction under a generative adversarial framework through a multi-scale wavelet decomposition and sub-band fusion decoder to obtain a reconstructed image. According to the method, the consistency of space geometric precision and texture details can be kept while artifacts and seams are inhibited, and the applicability and stability of image enhancement in a complex scene are improved.

The invention provides a ring artifact correction method and electronic equipment, and relates to the technical field of medical treatment. According to the specific implementation scheme, the electronic equipment obtains a projection image, the projection image comprises a shadow area, and one shadow point in the shadow area corresponds to one annular artifact; the electronic equipment determines the position information of the annular artifact corresponding to the shadow point based on the position information of the shadow point in the shadow area; and the electronic equipment corrects the ring artifacts based on the position information of the ring artifacts corresponding to the shadow points. Thus, the position information of the ring artifact corresponding to the shadow point is determined, and correction of the ring artifact is performed in a targeted manner in combination with the position information of the ring artifact, so that the ring artifact can be removed more accurately, and the correction accuracy of the ring artifact is improved.

The present application belongs to the technical field of medical ultrasonic signal processing, and specifically relates to a spermatic vein ultrasonic imaging enhancement system and method based on double-wall filtering and adaptive Doppler signal processing. The system comprises a dynamic reconfigurable analog front end, a dual-channel heterogeneous data processing unit and a closed-loop feedback controller. The method extracts fluid dynamics characteristics in real time through an auxiliary path, intelligently identifies resting state and action mutation state. At the action mutation moment, the physical layer automatically switches the analog filtering parameters to prevent signal saturation, and the digital layer adaptively increases the FIR filter weight to eliminate the ringing artifact; in the resting state, the high-gain analog configuration is maintained and the IIR filter is dominated to capture weak signals. With the delay buffer mechanism, accurate timing alignment of control instructions and imaging data is realized. The present application effectively solves the contradiction between low flow rate detection sensitivity and strong tissue motion interference suppression, eliminates the flicker artifact generated by breath holding action, and significantly improves the diagnosis accuracy of weak reflux.

An apparatus and method for calibrating a photon-counting computed tomography (PCCT) apparatus, includes performing for each offset from a rotation center, a scan of a calibration phantom placed at the offset to obtain calibration data including measured count rate data. Location parameters of the calibration phantom are estimated for each of the plurality of offsets, based on the obtained calibration data. Thickness data of the calibration phantom is determined based on the estimated location parameters. A curve is estimated, by curve fitting using the measured count rate data and the determined thickness data, indicating a relationship between the energy bin count rate and phantom thickness, for each energy bin of each pixel of the plurality of pixels. A first look-up table is generated for pixel-to-pixel count rate variation correction, and the first look-up table is applied to acquired energy bin count data to reduce ring artifacts in an image reconstructed using the acquired energy bin count data. A second look-up table is generated for both pixel-to-pixel count rate variation correction and additional count-rate non-linearity correction, using water as the calibration material, and the second look-up table is applied to reduce both ring artifacts and cupping or doming artifacts in an image reconstructed using the acquired energy bin count data.

The application provides an image ring artifact removal method and device, electronic equipment and a storage medium, wherein the method comprises: performing normalization processing on an obtained original CT image to obtain a standard CT image; dividing the standard CT image into a plurality of standard sectors according to a target sector division mode, and dividing the original CT image into a plurality of original sectors according to the target sector division mode; determining a correction pixel value corresponding to each standard pixel in each standard sector; correcting an original pixel value of an original pixel in a main sector region in the original CT image according to the correction pixel value corresponding to each standard pixel in each standard sector, and performing linear transition on a pixel value of an original pixel in each boundary sector region in the original CT image according to two correction pixel values corresponding to each standard pixel in an overlapping region of each standard sector, so as to remove ring artifacts in the original CT image.

The present invention discloses a method, apparatus and imaging device for adaptively correcting ring artifacts in CT images while preserving the structure. The steps included in the invention are as follows: Step 1, obtaining the original CT projection image of the object to be measured; Step 2, performing multi-scale decomposition on the original CT projection image to obtain initial multi-scale images with different sizes; Step 3, performing boundary-preserving filtering on each initial multi-scale image and outputting the first multi-scale image; Step 4, removing the frequency information corresponding to the artifact information in the first multi-scale image through an artifact information correction method and outputting the second multi-scale image; Step 5, sequentially reconstructing and rebuilding the second multi-scale image to obtain a CT image with ring artifacts removed. The present invention can effectively correct ring artifacts in CT images only through software algorithms without the need for special hardware support.

The application discloses a medical image processing method and device and medical imaging equipment. When there is a ring artifact in an initial medical image sequence, the radius of the ring artifact in the initial medical image sequence is acquired, the artifact slice image sequence can be determined in a plurality of slice images included in the initial medical image sequence according to the radius of the ring artifact, the ring artifact is eliminated from a target slice image included in the artifact slice image sequence, and a target medical image sequence without the ring artifact is obtained. Through automatic identification of the artifact slice image sequence in the plurality of slice images included in the initial medical image sequence and elimination of the ring artifact from the artifact slice image sequence, automation of slice image ring artifact elimination is realized, and image quality and authenticity are improved. Further, through automatic identification of the artifact slice image sequence according to the radius of the ring artifact, the removal efficiency of the ring artifact can be improved.

The invention discloses a method for removing ring artifacts in CT imaging. The method comprises the following steps: correcting a projection sinogram of a central channel area of a projection domain detector based on a projection domain correction table; performing CT reconstruction on the corrected projection sinogram to obtain a reconstructed original CT image; extracting an image domain ring artifact of the original CT image; and subtracting the image domain ring artifact from the original CT image to obtain a ring-removed CT image. Therefore, by introducing the central channel selection window to carry out projection domain ring removal on the central channel area and carrying out integral ring removal in the image domain, the problem of black and white centers can be well inhibited under the condition that CT image distortion is not caused, the quality of the CT image, especially the photon counting CT image, is improved to a great extent, and the method can be widely applied to CT image processing.

According to the photon counting detector ring artifact correction method, the photon counting detector ring artifact correction device, the terminal and the medium provided by the invention, block correction and fitting error compensation are respectively performed on the photon counting detector through a high-order polynomial fitting method, so that accurate correction of the photon counting detector ring artifact is realized; meanwhile, complex modeling and time-consuming calculation are avoided, the real response laws between different detectors and the calibration plate can be accurately fitted only through a small amount of data, an accurate and reliable solution is provided for ring artifact correction, material decomposition and image reconstruction, and the method has remarkable application potential in clinical practice. The problems that a large number of annular artifacts appear after projection data reconstruction of the photon counting detector and the image quality is seriously reduced due to the fact that response laws of different detectors to spectrums are different are solved.

The present invention provides a method for eliminating ringing artifacts in single-pixel imaging, belonging to the field of image filtering technology. The present invention uses a Butterworth low-pass filter to automatically eliminate the ringing artifacts from a single-pixel imaging spectrum graph containing ringing artifacts and reconstruct a higher-quality image. The present invention solves the problem that ringing artifacts exist in the reconstructed target scene of SPI at low sampling rates. The present invention can automatically eliminate ringing artifacts using only a Butterworth low-pass filter, which is more efficient than existing methods and provides a method for achieving high-quality SPI at low sampling rates.

The invention belongs to the technical field of optical precision measurement, and particularly relates to an optical fiber three-dimensional refractive index measurement method based on differential interference optical tomography. The three-dimensional refractive index distribution of the optical fiber is reconstructed by extracting a differential phase field at a plurality of rotation angles. Compared with a traditional method, the method provided by the invention has the advantages that the natural weighted characteristic of the Hilbert transform of the differential phase field in the frequency domain is proposed, and the problem of over-dense sampling in a low-frequency region in the center of a frequency spectrum space is avoided; the method has the advantages that low-frequency oversampling is naturally suppressed, high-quality tomography can be performed on the optical fiber without manual frequency domain windowing filtering operation, three-dimensional refractive index distribution measurement is realized, Gibbs ringing artifacts are eliminated, and high-frequency details are reserved. According to the invention, isotropic micron / submicron resolution can be realized, and the method is suitable for accurate three-dimensional refractive index field measurement of optical fibers with complex structures.

The invention discloses an adaptive method for removing ringing artifacts in single-element endoscopic ultrasonic based on time-frequency analysis filtering. Steps: obtain original data of endoscopic single-element ultrasonic imaging, perform time-frequency spectrum analysis on adjacent frame signals; determine mutation of the time-frequency spectrum of the signal to be processed relative to reference signal by using an optical flow method; determine a threshold coefficient and spectral distribution factors to set parameters of a time-frequency filter; perform time-frequency filtering on the signal to be processed, and then perform time-domain recovery; calculate index of filtered and original data, and optimize and adjust threshold parameters based on whether index meets standard; perform time-frequency filtering, time-domain reconstruction, and ultrasonic endoscopic image reconstruction. The method nearly eliminates ringing artifacts, restores effective echo signals, and maintains structural integrity during close-range imaging.

The invention relates to the technical field of CT (Computed Tomography) artifact correction and image processing, in particular to a CT image ring artifact correction method based on detector jitter, which comprises the following steps of: controlling a detector to jitter according to a preset periodic jitter track and acquiring a projection image during scanning; returning the image to a non-jittering state according to the track; carrying out CT reconstruction on the returned image; and performing bilateral filtering on the reconstructed CT image to obtain a corrected image. The jitter trajectory follows a triangular wave function, bilinear interpolation is adopted for return, an FDK algorithm is adopted for reconstruction, and a Gaussian weighting mode combining space and a pixel value domain is adopted for bilateral filtering. According to the method, a ring artifact generation mechanism is broken through physical jitter, edge protective filtering is combined, the image definition is kept while the ring artifacts are effectively removed, and the method has the advantages of being independent of additional correction, free of a large amount of training data and easy and convenient to implement.

The invention provides an image processing method and device, electronic equipment and a storage medium, and relates to the technical field of image processing. A CT image containing the ring artifact under a rectangular coordinate system is converted into a first image under a polar coordinate system, and median filtering is performed on the first image in the radius direction, so that isolated extreme pixel values of the ring artifact in the radial direction can be effectively eliminated. Through difference operation between the first image and the filtered first image, ring artifact related information (linear artifacts) can be highlighted to obtain a difference image. Smooth filtering is carried out on the difference image in the angle direction, continuous pixel value fluctuation of the ring artifact in the angle direction can be restrained, the noise influence can be restrained, and after the ring artifact is converted back to the rectangular coordinate system to obtain the second image, the ring artifact can be accurately removed through difference operation between the original CT image and the second image. According to the method, the original texture details of the CT image can be reserved to the greatest extent, the interference of ring artifacts on the subsequent image processing process is avoided, and a more accurate image basis is provided for clinical diagnosis.

The present invention discloses an adaptive single-element endoscopic ultrasound ringing artifact removal method based on time-frequency analysis filtering. The method is as follows: Obtain the original data of endoscopic single-element ultrasound imaging, and perform time-frequency spectrum analysis on adjacent frame signals; Obtain the mutation situation of the time-frequency spectrum of the signal to be processed relative to the time-frequency spectrum of the reference signal according to the optical flow method; Determine the threshold coefficient and the spectrum distribution situation factor, and determine the parameters of the time-frequency filter through these two parameters; Perform time-frequency filtering on the signal to be processed by the initially calculated time-frequency filter and perform time-domain recovery; Calculate the indexes using the data after removing the artifacts by time-frequency filtering and the original data, and optimize and adjust the threshold parameters according to whether the indexes meet the standards; Use the time-frequency filter parameters with qualified indexes to perform time-frequency filtering, time-domain reconstruction, and ultrasound endoscopic image reconstruction on the data. This method can almost completely remove the ringing artifacts, restore the effective echo signals, and maintain the structural integrity during near-distance imaging.

This invention relates to the field of image processing technology, specifically providing a blind image restoration method based on the COS function and Wiener filtering. The method includes: acquiring a blurred image to be processed; constructing a blind deblurring model within a variational framework; the objective function of the blind deblurring model being used to simultaneously estimate a low-rank sharp image and a blur kernel; solving the objective function in a multi-scale Gaussian space using an alternating iterative optimization strategy to estimate and obtain the low-rank sharp image and blur kernel; using the obtained blur kernel to perform Wiener filtering on the blurred image to obtain an initial restored image; and then performing COS filtering on the initial restored image to obtain the final restored image. This invention combines Wiener filtering with a COS filter, utilizing the COS filter for smooth transitions, effectively solving the ringing artifact problem present in traditional Wiener filtering.

Provided in the invention is a method and a device of Correction of a ring artifact in a CT image and a computer program medium. The method of correction comprises: pre-processing original detection data; marking a bad detector according to data in the pre-processed original sinogram; acquiring a replacing detection value corresponding to the bad detector by means of a first averaging processing; and performing a CT image reconstruction using a sinogram data after the first averaging processing. The device comprises: a pre-processing unit configured to pre-process original detection data; a marking unit configured to mark a bad detector according to data in the pre-processed original sinogram; a first averaging processing unit configured to acquire a replacing detection value corresponding to the bad detector by means of a first averaging processing; and an image reconstruction unit. The invention is able to effectively eliminate the ring artifact in the CT image, and at the same time ensure that there is little loss of the spatial resolution of the CT image.

The invention provides a coding method and device for weakening a ringing effect, and the method comprises the steps: S1, comparing the RDCost of a current block in two modes of division and non-division, carrying out the pre-judgment of the division modes, and selecting a division scheme with the smaller RDCost; s2, judging whether the ringing effect does not exist in the current block by utilizing a quantization module of the video encoder, if so, ending ringing effect detection, and if not, further judging whether the ringing effect exists in the current block by utilizing a pixel change condition in an image block of the video encoder; s3, further judging the ringing effect of the current block, if the original pixels of the sub-block of the current block are flat, but the reconstructed pixels of the sub-block of the current block are not flat, judging that the ringing effect occurs in the block, forcibly selecting a division mode, and ending the ringing effect detection; and if all the sub-blocks are traversed and ringing effect detection is not quitted, the division scheme is kept unchanged. The method has the advantages that operation is simple, hardware implementation is facilitated, the overall compression ratio is not affected, and subjective quality can be effectively improved.

The application provides a circular artifact correction method, system, electronic equipment, storage medium and chip, the correction method comprises: determining an original image; coordinate conversion is carried out to the original image in the range of its circumscribed circle, and a polar coordinate image is determined; the polar coordinate image is circumferentially projected to obtain a projection curve, the first gradient of the pixel point on the projection curve is calculated, and the artifact where the pixel point is located is a thick ring if the first gradient is greater than a first threshold value; the polar coordinate image is filtered to remove the thick ring and obtain a first correction image; the second gradient of the pixel point on the first correction image is calculated, and the artifact where the pixel point is located is a thin ring if the second gradient is greater than a second threshold value and not greater than the first threshold value, and the first threshold value is greater than the second threshold value; the first correction image is filtered to remove the thin ring and obtain a second correction image; coordinate conversion is carried out to the second correction image in the range of its circumscribed circle, and a rectangular coordinate system image is obtained.

This invention, applicable to the field of computed tomography (CT) scanning, provides a wide-temperature correction method for CT detector modules and a CT system employing the method. By adding a corresponding temperature sensor to each detector module, the method collects detector sensitivity at different temperatures and establishes a temperature-sensitivity correction table. This correction table is then used to calibrate the projection data output during the actual imaging process, effectively eliminating ring artifacts in tomographic images and enhancing the imaging system's adaptability to various environments.

The present application relates to the technical field of image processing, and discloses a kind of polarization filtering and light field imaging's underwater alum flower identification method and system, solve the problem that prior art cannot realize the high-fidelity acquisition and accurate quantification of alum flower morphological characteristics under high turbidity, dynamic water quality working condition.The present application is through the collaborative optical design of polarization filtering and light field imaging, suppresses water backscattering and Mie scattering interference at the collection source, provides high-fidelity image basis for subsequent morphological quantification;Introduce double-domain Gaussian window spectrum shaping and truncated sinc interpolation kernel, improve the refocusing position accuracy without hardware modification, eliminate the ringing artifact and phase distortion caused by traditional linear interpolation;Multi-scale Retinex enhancement model accurately adapts to the low contrast and multi-scale texture characteristics of alum flower, retains the texture information required for fractal dimension calculation completely under the premise of avoiding noise amplification, and linear fitting is combined with box counting method, so that the fractal dimension estimation error is reduced.

Exemplary systems, methods and computer arrangement for decorrelating and removing noise, and / or for removing Gibbs ringing data from at least one image can be provided. In one example, there can be a procedure for receiving information related to the at least one image; a procedure for producing the at least one image based on the determination if the noise is decorrelated; a procedure to remove the noise from the at least one image; a procedure for detecting an oscillation pattern from at least one edge of a measured portion of k-space associated with the information; and a procedure for removing the Gibbs ringing artifact from the information based on the detected oscillation pattern.

The invention discloses an image noise removal method based on a linear array X-ray camera, which is suitable for a high-energy X-ray imaging system. The stripe noise in the pixel direction is eliminated through bright field correction, specifically, a bright field image matrix is obtained, the mean value in the pixel direction is calculated, then the image matrix to be processed is divided by the mean value line by line, and a pixel correction matrix is obtained. And then noise accumulated along with time is suppressed by using self-adaptive non-uniform correction, that is, preliminary noise reduction is adjusted through dynamic integral time, background noise corresponding to the integral time is deducted in real time, and then a neural network is accessed to correct residual high-frequency noise. For a three-dimensional image, a generative adversarial network is adopted to reduce ring artifacts in a reconstructed image, a generator of the generative adversarial network adopts a U-Net structure, and a discriminator fuses global and local discrimination. The method can effectively eliminate stripe noise in the pixel direction and the time direction, improve the quality of a two-dimensional image and reduce ring artifacts of a three-dimensional image, and is suitable for high-energy X-ray application scenes such as nondestructive testing of large metal workpieces, security inspection imaging and the like.

Provided is a self-adaptive single-array-element endoscopic ultrasonic ringing artifact removal method based on time-frequency analysis filtering. The method is as follows: acquiring endoscopic single-array-element ultrasonic imaging original data, and performing time-frequency spectrum analysis on adjacent frame signals; according to an optical flow method, obtaining a time-frequency spectrum mutation condition of a time-frequency spectrum of a signal to be processed relative to a reference signal; determining a threshold coefficient and a frequency spectrum distribution condition factor, and determining parameters of a time-frequency filter by means of the two parameters; performing time-frequency filtering on the signal to be processed by means of a time-frequency filter obtained by means of preliminary calculation and performing time domain recovery; performing index calculation on data after the artifact is filtered out by using time-frequency filtering and the original data, and optimizing and adjusting threshold parameters according to whether an index reaches a standard or not; and performing time-frequency filtering, time domain reconstruction, and ultrasonic endoscopic image reconstruction on the data by using a time-frequency filter parameter with the index reaching the standard. According to the method, the ringing artifact can be almost completely removed, an effective echo signal is recovered, and the structural integrity during short-distance imaging is maintained.

The invention relates to the technical field of image processing, discloses an underwater alumen ustum recognition method and system based on polarization filtering and light field imaging, and solves the problem that in the prior art, high-fidelity acquisition and accurate quantification of alumen ustum morphological characteristics cannot be realized under the working conditions of high turbidity and dynamic water quality. Through the collaborative optical design of polarization filtering and light field imaging, backscattering and Mie scattering interference of a water body is inhibited at an acquisition source, and a high-fidelity image basis is provided for subsequent form quantification; a double-domain Gaussian window frequency spectrum shaping and truncated sinc interpolation kernel is introduced, the precision of a refocusing position is improved under the condition that hardware does not need to be changed, and ringing artifacts and phase distortion caused by traditional linear interpolation are eliminated; the multi-scale Retinex enhancement model accurately adapts to the low-contrast and multi-scale texture characteristics of alumen ustum, texture information required by fractal dimension calculation is completely reserved on the premise of avoiding noise amplification, and the fractal dimension estimation error is reduced by combining linear fitting of a box counting method.

The invention relates to the technical field of image processing, and particularly provides an image blind restoration method based on a COS function and Wiener filtering, comprising: acquiring a blurred image to be processed, constructing a blind deblurring model under a variational framework, an objective function of the blind deblurring model being used for synchronously estimating a low-rank clear image and a blurring kernel; solving the target function in the multi-scale Gaussian space through an alternating iteration optimization strategy, and estimating to obtain a low-rank clear image and a blurring kernel; and performing Wiener filtering on the blurred image by using the solved blurred kernel to obtain an initial restored image, and performing COS filtering on the initial restored image to obtain a final restored image. Wiener filtering and the COS filter are combined, smooth transition is carried out through the COS filter, and the ringing artifact problem existing in traditional Wiener filtering is effectively solved.

The present invention discloses a defocused image deblurring method based on boundary neighborhood gradient difference, which belongs to the technical field of computer vision. In view of the fact that the existing defocused image deblurring method cannot accurately obtain the blur amount of the boundary position of the defocused image for static scenes with multiple depth layers, the present invention makes full use of the relationship between the boundary neighborhood gradient difference and the blur amount to accurately obtain the blur amount of the boundary position of the defocused image, thereby solving the problem of boundary ringing artifacts appearing in the deblurring result; in view of the problem that the ability of the non-blind deconvolution algorithm to retain image detail information is not strong enough, resulting in the loss of detail information in the deblurring result, the present invention combines the discrete blur amount selection strategy and the sparse prior to design a non-blind deconvolution algorithm to enhance the ability of the non-blind deconvolution algorithm to retain image detail information, solves the problem of the loss of detail information in the deblurring result, and can be used for defocused image deblurring processing in static scenes with multiple depth layers.

A method and wireless device with a counterpart presence detector is provided. The detector includes only memory and logic circuits to detect a change in a ringing artifact from the presence of a RF device. The memory stores template signals and threshold values. The template signals may be generated using a metal object positioned various distances from the RF device. The ringing artifact, also called an RF-off signal, is sampled. A difference between subsequent ringing artifact samples is taken to produce a ringing artifact difference. Also, a difference between subsequent samples of a template signal is taken to produce a template difference. A Euclidean distance between the ringing artifact difference and the template difference is determined. The distance is compared to a threshold value. A presence of another RF device within the RF field of the RF device is detected if the distance compares favorably to the threshold value.

The present invention relates to the field of medical image processing technology, and discloses a method, apparatus, computer device, and storage medium for removing artifacts from scanned images. The method comprises: obtaining a scanned image to be corrected that has ring artifacts; converting the ring artifacts in the scanned image to be corrected into strip artifacts to obtain a first image with strip artifacts; using a preset unsupervised network model to eliminate the strip artifacts in the first image to generate a second image; and performing artifact removal based on the first and second images to obtain a target scanned image. By implementing the technical solution of the present invention, the unsupervised network model in deep learning is fully utilized to solve the serious problem of ring artifacts in scanned images, thereby achieving effective removal of ring artifacts.