124 results about "Motion parameter estimation" patented technology

The invention discloses a human motion capture three dimensional playback system and a method thereof. The system is characterized in that the system comprises a human motion capture subsystem and a human motion playback subsystem; the human motion capture subsystem is composed of a microsensor motion measuring module and a motion parameter estimating module; the microsensor motion measuring module measures corresponding body motion data by a plurality of microsensor units attached to each limbs and trunk of human body respectively, and the motion parameter estimating module fuses microsensordata of different types of each microsensor unit and deduces the mass motion of human body; the human motion playback subsystem is used for receiving human mass motion parameters deduced by the humanmotion capture subsystem. The invention has the advantages of simple structure, high precision, low cost, small volume, low power consumption and convenient usage, has the characteristics of portability and real-time, has wide application in numerous fields and has comparatively strong practical value and application prospect.

The invention relates to a human motion capture device which comprises motion measuring units, a motion parameter estimation unit, an initialization unit, a display estimation unit and an overall integration unit; the motion measuring units are attached on all the limbs of a human body and are used for measuring the motion data and the environmental data of all the limbs; the motion parameter estimation unit deducts the motion parameters and the environmental parameters of all the limbs, and when in deduction, a self-adaptive anti-interference three-dimensional angle estimation method is adopted to deduct the three-dimensional angle values of all the limbs; the initialization unit is used for receiving and integrating the motion parameters and the environmental parameters of all the limbs, and deducting the initial operation parameters of the human body motion capture device; the displacement estimation unit is used for receiving and integrating the motion parameters and the environmental parameters of all the limbs as well as the initial operation parameters of the human body motion capture device, and deducing the displacement of the human body relative to the ground; and the parameters and the displacement of the human body relative to the ground are finally integrated together by the overall integration unit, so that the position and the gesture of the overall motion of the human body are worked out and output.

This invention relates to one visual frequency stable method based on property matching in the computer image visual frequency process technique field, which comprises the following steps: finding out each frame of visual SIFT property points; adopting simulation module as parameters estimation module for total estimation; adopting Gauss filter and curve matching method to process visual sequence process to fill unknown area.

The invention discloses a real-time camera tracking method for a dynamically-changed scene. According to the method, the camera pose can be tracked and solved stably in a scene changed dynamically and continually; at first, feature matching and camera parameter estimation are performed, and then, scene update is performed, and finally, when the method is actually applied, foreground and background mutil-thread coordinated operation is implemented, the foreground thread is used to perform feature point matching and camera motion parameter estimation on each frame, and the background thread is used to perform KD tree, key frame and three-dimensional point cloud maintenance and update continually, and optimize key frame camera motion parameters and three-dimensional point positions in a combined manner. When the scene is changed dynamically, the method of the invention still can be used to perform camera tracking on a real-time basis, the method of the invention is significantly better than existing camera tracking methods in tracking accuracy, stability, operating efficiency, etc.

The invention provides an image mosaic method, in particular a two-dimensional wide-scene ultrasonic image mosaic method, which is applied to a real-time acquired or stored ultrasonic video image sequence. The method comprises the following steps of: detecting key characteristic points in movable images by using a height relevance of two adjacent frames of images, namely a registration graph and a movable graph, and estimating a motion vector between the movable graph and the registration graph to finish motion matching and overall motion parameter estimation among the characteristic points of the adjacent images so as to obtain a rotating angle and a displacement and further finish a registration process of two images; mapping the current image to a coordinate system of the registration graph or the wide-scene image according to the obtained motion parameters so as to realize fusion between the current wide-scene image and the registered image; and if the wide-scene image exceeds the size of a current display equipment window, integrally moving the image backward with a plurality of pixel points till a new mosaic part of the wide-scene image is totally displayed; otherwise, processing the next image.

The invention discloses a panorama image stabilization method based on the iteration of global characteristic points. The method of the invention includes two parts of the estimation of image motion parameters based on the iteration of characteristic points and the compensation of image motion based on the wave filtering. The estimation of global motion parameters includes that a Harries characteristic point which is the most stable in the image is combined with a characteristic window; local characteristic points are gradually deleted through the identification of the distance consistency and the updating of the iteration of characteristic points so that the global characteristic point set converges rapidly and the global motion parameters can be accurately obtained. The compensation of the motion image includes that the global motion parameters are filtered to acquire dither parameters, and actual dither parameters are compensated and the normal scanning motion of an image pickup system is retained; simultaneously, the image fusion is combined with the compensation to realize the output of a panorama image. The method of the invention can effectively process the dithers such as translation, rotation and zooming, etc., of the image pick-up system and more complex local motion of the scene, and can be used for removing the influence on the video sequence by a motion carrier so as to output a stable video and improve the observation effect of the video monitoring or tracking.

The invention discloses self-adaptively selecting global motion estimation method for panoramic video coding, which comprises the following steps that: (1) an image is divided into a plurality of sub-image blocks, (2) zero vector block is decided, (3) multi-resolution motion is estimated, (4) translational motion model motion parameter is estimated, (5) six-parameter motion model motion parameter is estimated, (6) twelve-parameter motion model motion parameter is estimated, and (7) RDO optimizes an estimation model of self adaptively choosing global motion. The advantage is that the estimation model of self adaptively choosing global motion optimized by the RDO can well describe the camera motion flow characteristic of the current frame well so that the motion estimation is more accurate and the coding performance is higher. At the same time, aiming at the characteristics of the rich detail and the high resolution ratio of panoramic video motion, the invention takes the Lagrange parameter Lambada=0.85x2QP / 3+2QP / 6 and further obtains a good balance between compression code rate and image distortion degree.

The invention provides an image deblurring method based on camera motion detection. According to the image deblurring method based on the camera motion detection, motion parameters of a camera during exposure are firstly obtained through an inertial navigation device, and a rough movement locus of the camera is estimated according to the motion parameters; then a blurring core of an image during the exposure is obtained through the multi-look geometry according to the movement locus; finally, a sharp image which is deblurred is obtained according to the Wiener filtering algorithm. According to the image deblurring method based on the camera motion detection, the moving condition of the camera during the exposure can be accurately detected, the blurring core can be generated fast and accurately according to the movement locus, and finally the relatively sharp image can be obtained though inverse filtering.

The invention discloses a real time video image stabilization method based on simple fast global motion parameter estimation, which is simple to realize, has higher estimation prevision and provides a very effective method for real time video image stabilization under the environment of a low-speed embedded type platform. The real time video image stabilization method based on simple fast global motion parameter estimation comprises the following steps of: 1, carrying out block partition on a current frame; 2, obtaining a motion vector of each block based on a diamond search algorithm; 3, judging whether the motion is abnormal, and marking the block to be an effective block if the motion is not abnormal; 4, counting an average value of the translation invariants of all effective blocks to estimate a global translation invariant; 5, estimating rotation and zoom quantity of each effective block relative to a match block in a previous frame according to the global translation invariant; 6, counting all rotation and zoom qualities to estimate the global rotation and zoom quantity; 7, carrying out the motion filter process on the global translation invariant and the global rotation and zoom quantity; and 8, carrying out the motion compensation according to filter results.

[Problem]An object of the present invention is to provide an image registration processing apparatus that is capable of performing a robust and high-accuracy registration processing with respect to an entire image between images including multiple motions.[Means for Solving the Problem]The image registration processing apparatus according to the present invention comprises a feature point extraction processing unit that extracts feature points of a basis image and an input image that include multiple motions respectively, a feature point-based registration processing unit that performs a matching processing between basis image feature points and input image feature points and an initial motion parameter estimation processing after deleting outliers from matched feature points respectively, a single-motion region extraction processing unit that extracts a single-motion region based on an initial motion parameter and by using a similarity and a local displacement between images, a region-based registration processing unit that estimates a motion parameter with subpixel accuracy based on the initial motion parameter and the single-motion region, and a feature point deletion processing unit that deletes feature points included in the single-motion region from the basis image feature points and the input image feature points.

The invention discloses a full-frame electronic image stabilization method based on feature matching, which belongs to the technical field of digital image processing and aims at eliminating influences on a video sequence by jitter such as camera translation and rotation and generating stable full-frame video output. The method comprises steps: firstly, an ORB feature descriptor is adopted to extract feature points in each frame, a two-level matching strategy with minimum and second minimum Hamming distance ratio judgment in combination with coordinate and direction angle difference test is used for matching feature points in adjacent frames; then, a motion parameter estimation method with triangle area similarity test in combination with RANSAC is used for estimating and accumulating inter-frame affine transformation parameters; and finally, an image mosaic technique is used for acquiring a motion compensation mosaic image, subjective motion parameters of the camera are estimated through Kalman filtering, a display window with the same size as the video frame is set on the mosaic image sequentially, and complete motion compensation frame output is obtained. Translation and rotation jitter in the original video sequence are effectively removed, and the stable full-frame output is obtained.

The invention discloses a single-channel synthetic aperture radar moving target detection and positioning method based on two-view real image processing. The steps include: (1) calculating the azimuth spectrum; (2) separating sub-view images; (3) suppressing ground clutter ; (4) Using the constant false alarm detection method to detect moving targets; (5) Locating moving targets. The invention overcomes the disadvantages of multi-channel hardware system complexity, high cost and narrow application range by adopting the single-channel SAR-GMTI method, and has the advantages of simple hardware system, low cost and wide application range. Through adaptive amplitude filtering of the two-view real image and then suppressing the interference of static clutter, it overcomes the fact that there is still a large amount of static clutter left after the sub-view image cancellation of the existing single-channel system, and can only detect moving targets outside the main lobe of clutter The shortcomings of the signal have the advantages of high signal-to-noise ratio, the ability to detect moving target signals in the main lobe of clutter, low false alarm probability, and high accuracy of motion parameter estimation and positioning.

The invention proposes a target motion parameter estimation method for a random frequency hopping radar, and solves the problem that the existing speed measurement scheme has a long accumulation time,a large calculation amount and a poor anti-noise performance. The method comprises the main steps of: designing a waveform parameter for transmitting a random frequency hopping signal and receiving atarget echo; preprocessing digital signals; preprocessing the slow time sampling vector; constructing a difference frequency vector group; constructing a Doppler domain generalized Fourier transformmatrix group; carrying out the generalized Doppler transform and non-coherent processing; carrying out motion compensation processing; and carrying out the coherent integration of distance dimensionsand de-redundance processing to obtain a one-dimensional range profile with the correct target in the plurality of range gates. According to the target motion parameter estimation method for the random frequency hopping radar, a set of dimension decreasing difference frequency vectors are constructed from the target echoes, generalized Doppler processing is performed on each difference frequency vector, and an estimated value of the target radial velocity can be read in the generalized Doppler spectrum after non-coherent integration. The method is short in accumulation time, small in calculation amount and good in anti-noise performance, and is used for target detection and pulse accumulation of the random frequency hopping radar.

The invention discloses a real-time video image stabilizing method based on integral image characteristic block matching, which enhances the capability of preventing illumination and image noise shooting equipment, improves the robustness of global motion parameter estimation and further improves the video image stabilizing capability of the shooting equipment in a complex environment. The method comprises the following steps of: 1. carrying out block division on the current frame; 2. describing each block content by utilizing integral image characteristics; 3. carrying out block matching motion estimation on each block by using an integral image characteristic error minimum as a matching criterion; 4. calculating a motion vector of the block to obtain a global motion parameter of the current frame relative to the previous frame; 5. carrying out motion filter processing on the global motion parameter; and 6. carrying out motion compensation according to a filter result.

The invention relates to a partitioning processing-based SAR real-time imaging method and a system thereof. A distance echo pulse compression module is used for carrying out pulse compression on each received distance echo datum; an azimuth dimension partitioning processing module is used for carrying out range migration correction and Doppler parameter and kinematic parameter estimation on azimuth subaperture data; a full-aperture parameter estimation module is used for carrying out conjoint analysis and estimation on each azimuth subaperture parameter to obtain full-aperture Doppler parameters and kinematic errors; an envelope compensation module is used for carrying out envelop compensation on the azimuth subaperture data; and a distance dimension partitioning processing module is used for carrying out phase compensation, azimuth pulse compression, multi-look processing and quantization output on data which has undergone envelope compensation. Then, partitioning processing-based SAR real-time imaging processing is finished. The method has low requirements on system memory, can be adopted to effectively solve the problem that range variance leads to poor image quality, and is especially suitable for a SAR real-time imaging system which has high requirements on real-time performance.

The invention provides a motion parameter estimation method based on gray integral projection cross-correlation function characteristics. A horizontal moving motion model is adopted, and the method comprises the following steps that a target image is divided into N*N rectangular partitioning blocks with the equal size, gray integral projection is performed on each partitioning block, the variance of gray integral projection of each partitioning block is determined, R areas with the large variance can be selected as alternative areas, the cross-correlation operation is performed on gray integral projection of the alternative areas in two continuous frames of the target image, second derivatives of a cross-correlation function extreme point are calculated, weighted summation is performed on the variance of gray integral projection and the second derivatives of the cross-correlation function extreme point, good and poor factors of the alternative areas are obtained, the good and poor factors are arranged in a sort descending mode, the Q areas arranged in front are selected as the good-quality areas, local motion parameter estimation is performed on the obtained good-quality areas respectively, horizontal moving motion parameters in the direction of an axis X axis or an axis Y are obtained, and weighted summation is performed on the local motion parameters of the good-quality areas to obtain global motion parameters. According to the method, global motion parameters of an image with the low contrast ratio and the high resolution ratio can be effectively estimated.

The invention relates to the signal processing technology of an inverse synthetic aperture radar imaging, in particular to an ISAR (Inverse Synthetic Aperture Radar) imaging method for accumulating broadband directly acquired data based on ARP (Address Resolution Protocol) segmentation coherent. The method comprising: utilizing the coherence of the directly acquired data to estimate a target motion parameter according to a motion parameter estimation method, and performing a coarse compensation to a target motion using the parameter; then performing segmentation coherent accumulation on a compensated complex one-dimensional distance image based on ARP to improve the signal-to-noise ratio of an echo; and finally performing accurate processing of envelope alignment, phase compensation and ISAR imaging. The ISAR imaging method for accumulating broadband directly acquired data based on ARP segmentation coherent, fully utilizes the coherence of a broadband directly acquired echo, adopts a target translational parameter estimation method based on broadband echo translational phase fitting, and based on which, develops a frequency domain motion coarse compensation method; and for an application condition of low signal-to-noise ratio, adopts an ARP segmentation coherent accumulation method to improve the signal-to-noise ratio, and further adopts an accurate envelope alignment and phasecompensation method to obtain a target ISAR image with higher translational compensation precision and better focusing performance.

The invention discloses a motion compensation method of a starry sky background image. The method comprises the steps that: first, according to the gray scale and the motion feature of the starry sky background image, motion background compensation is carried out by utilizing two key processes of sample motion parameter estimation and integral motion parameter estimation. An abnormal point is directly removed in the sample motion vector estimation stage and the amount of calculating redundant information in the motion compensation method is reduced; and second, the method of the combination of block matching and centroid extraction is introduced in the sample motion parameter estimation stage. Due to the adoption of the block matching method, the operation speed of sample estimation is raised, the removal of the abnormal point furthermore reduces the amount of data information to be processed and the method based on the centroid extraction further improves the precision of a sample point estimation parameter. The motion compensation method adopts the method based on the combination of the block matching and the centroid extraction to achieve motion compensation in the starry sky background, therefore, calculation amount is lowered by 50 percent and the compensation precision is improved to 0.5 pixels from 1 pixel of the prior art.

The invention relates to a lane line detection method. The method comprises the following steps: collecting an image in real time; calibrating to obtain a homography matrix; computing a lane line graythreshold by adopting a local gray threshold method; extracting features according to gray value change of the pixel; clustering the feature points belonging to one lane line to fit the lane line through continuous matching and straight line constraint matching; orderly processing the feature points from bottom to top and from left to right so as to connect a form feature segment; inversely projecting the feature segment to a world coordinate system through the homography matrix, and computing the width, the length and the angle parameter of the lane mark line; selecting a seed feature segment, and searching the feature sequence input into the same lane line with the seed feature segment by serving the seed feature segment as the basis, and fitting a lane line equation; performing lane line tracking, and predicting the location of the detected lane line at the current frame on the basis of the lane line movement parameter estimation, and judging the effectiveness of the tracking target by serving the location at the input of the lane line tracking.

The invention belongs to the technical field of radar real-time imaging processing, and particularly relates to an SAR real-time imaging processing method based on an FPGA and multiple DSPs. The processing method includes the following steps that echo data are pre-processed by means of an FPGA chip, so that subaperture data are obtained; the subaperture data are sent to the first DSP sequentially by means of the FPGA chip and are alternately forwarded to the third DSP, the fourth DSP and the seventh DSP by means of the FPGA chip for Doppler center estimation, range migration correction, Doppler rate estimation and motion parameter estimation, and the processed data are forwarded to the eighth DSP sequentially through the first DSP; each subaperture datum is divided into three blocks in the range direction through the eighth DSP and the three blocks of each subaperture datum are sent to the second DSP, the fifth DSP and the sixth DSP respectively for motion parameter fitting, phase compensation, direction pulse pressure and multiview processing, so that corresponding blocked image data are obtained; the blocked image data are transmitted to the eighth DSP for image quantization and image splicing processing, and ultimately an SAP image is obtained.

The invention discloses a squint SAR ground moving target extracting method. The squint SAR ground moving target extracting method comprises the following steps that 1, echo signals of a stationary target and a moving target are computed; 2, range direction Fourier transformation is carried out; 3, consistent range walk correction is carried out on a range frequency domain and an orientation time domain; 4, range direction residual phase compensation is carried out; 5, variable parameter extension azimuth nonlinear CS is carried out; 6 the echo signals subjected to the extension azimuth nonlinear CS are multiplied by corresponding azimuth minus factors respectively and are transformed to the azimuth frequency domain; 7, the amplitudes of the two echoes are subtracted, the echo of the stationary target is removed, and stationary target clutter suppression is achieved; 8, amplitude detection and moving target extraction are carried out. The method solves the problems that the range and azimuth are coupled seriously in a ground moving target under the single-channel squint mode and moving target movement parameters are unknown, estimation of movement parameters is not needed, efficiency is higher, and the method can be widely used in the fields of clutter suppression, moving target extraction and the like.

The invention discloses a fast estimation method for a non-uniform rotating target motion parameter. The method comprises specific steps: an echo signal in a single distance unit is modeled into a QFMsignal; a correlation function is constructed, the QFM signal is converted to a time-chirp distribution plane, and minimum entropy criterion-based weighted least squares Radon transform is adopted toestimate secondary chirp; the estimation accuracy and the robustness of the algorithm in a low signal-to-noise ratio environment are improved effectively at the same time; TFD-based weighted least squares Radon transform is adopted to estimate linear chirp, and through filtering, cross-term interference is eliminated; and according to the geometric information in a distance-Doppler domain, the center frequency is directly estimated. The calculation amount of the target motion parameter estimation process can be significantly reduced, the influences of transmission errors on estimation of eachmotion parameter are effectively avoided, and the final target parameter estimation precision and the ISAR imaging quality are ensured.

The invention provides an estimation method of target motion parameters for a mine platform. A pseudo linear least square estimation method and the Kalman filtering algorithm are combined. The targetmotion parameters are initialized by adopting the pseudo linear least square estimation method to adaptively update target initial motion parameters. An optimal initial motion parameter is obtained asan iteration initial value of the Kalman filtering to solve the motion parameters of the target. The target motion parameter estimation method for the radar platform can increase the convergence speed and improve the estimation accuracy.

The invention relates to a method of estimating motion parameters of a linear global camera in multi-view reconstruction and belongs to the technical field of multi-view geometry and three-dimensionalreconstruction. The method comprises the steps of S1, inputting multiple images, and subjecting the multiple images in a fixed scene to pairwise matching; S2, using a theory based on multi-view geometry and a global optimization method to optimize all cameras in a same coordinate system; S3, calculating absolute rotation of each camera; S4, calculating absolute translation vector of each camera via the absolute rotation of the camera and point matching in accordance with polar geometric constraint relationship in multi-view geometry. The method has the advantages that reconstruction application of a big scene can be handled, noise influence is low, calculating is simple, other extra information is not required, and motion parameter precision is greatly improved.

The invention discloses a panoramic video coding-oriented quick global motion estimation method. The method comprises two steps of: 1, using a brightness residual threshold value model, which is based on the combination of statistic characteristics and mean of threshold values, to approximately divide a local motion area and a global motion area, and obtaining an approximate set of a global motion estimation area; and 2, adopting the motion vector residual grading threshold value technology to gradually detail the set of global motion pixels in a minimum iterative process of the energy residual function and finally separating the complete global motion area so as to achieve an aim of quick motion estimation. The method has the advantages of taking both accuracy and robustness of the global motion estimation into consideration, greatly saving cost of calculating the motion estimation under the condition of ensuring the quality of the re-constructed image does not decline, but is improved a little bit, and having effects of low algorithm complexity and accurate estimation of motion parameters on the global motion estimation of the panoramic video sequence.

The invention belongs to the field of radar imaging, and relates to an SA-ISAR imaging method for a target with a micro-motion component based on low-rank and sparse joint constraint. The method comprises the following steps: S1, carrying out modeling of a target one-dimensional range profile sequence after translation compensation of target with a micro-motion component; S2, carrying out modelingon a sparse aperture ISAR imaging problem of the target with a micro-motion component; and S3, solving the sparse aperture ISAR imaging problem of the target with the micro-motion component by adopting linear ADMM. The method has the following beneficial effects: sparse aperture ISAR imaging of a target with a micro-motion component can be realized; under sparse aperture conditions, the one-dimensional distance image sequence of the target main body part and the micro-motion part can be effectively separated; an m-D effect caused by the target micro-motion component is eliminated; sidelobe and grating lobe interference caused by the sparse aperture is eliminated, and thus the target main body part ISAR image with a good focusing effect is further obtained; and the method has an importantengineering application value for radar imaging of a target with a micro-motion component, micro-motion parameter estimation, feature extraction and target recognition under the condition of data limitation.

The invention belongs to the technical field of radar target detection, and specifically relates to a rapid detection and high-order motion parameter estimation method for radar maneuvering targets. According to the technical scheme, low, small and slow targets with complex motion are mainly detected through a radar, a method for solving distance movement and Doppler migration which occur when thetargets with the complex motion perform long-term coherent accumulation is provided, the parameter estimation performance is improved at the same time, the calculation amount is reduced, and therefore the purpose of rapidly detecting the targets is achieved.

The invention relates to a non-cooperative target relative navigation motion estimation method based on a sequence image. The implementation of non-cooperative target on-orbit tasks has high requirements for the relative speed, high precision and high reliability of relative navigation, especially when an active spacecraft does not rely on ground operations and independently completes relative navigation and guidance and control of non-cooperative targets. The method overcomes the deficiencies of the existing non-cooperative target relative navigation motion parameter estimation methods, and uses the sequence distance image as an input. The sequence distance image is used as input, the image is spatially discretized by a body unit, a non-cooperative target dynamic equation is used for Kalman filtering, which overcomes the limitations of a feature recognition method, improves the estimation accuracy and efficiency, and reduces the amount of data processing.

The invention relates to a hypersonic speed target detecting method for polynomial Radon-polynomial Fourier transform, and belongs to the technical field of radar signal processing and detecting. The method comprises the steps that N periodic signals to be accumulated are sampled, a slow time-fast time target observed value is extracted, and pulse compression is performed on the sampled signals separately; initialization parameters of polynomial Radon-polynomial Fourier transform are determined; search, compensation and accumulation are performed in a parameter space through polynomial Radon-polynomial Fourier transform to obtain a range-Doppler distribution diagram subjected to phase-coherent accumulation; constant false-alarm detection and target motion parameter estimation are performed on the range-Doppler distribution diagram. According to the method, model building is performed on target motion through polynomial, range walk and Doppler spread of the signals are compensated through parameter search of the polynomial, and therefore effective accumulation detection on a high-speed high-mobility target can be achieved under a low signal-to-noise ratio background; in addition, effective search on the multi-dimensional parameter space is achieved in a multi-resolution search mode, and therefore the search real-time performance is improved.

The invention provides a real-time motion compensation method for an ultra-wide band synthetic aperture radar (UWB SAR), which is characterized in that motion parameters output by a single-point global positioning system (GPS) are used for carrying out real-time motion compensation of the UWB SAR, the flight time is segmented according to Ta, when the current moment is a starting point of an imaging synthetic aperture, an imaging coordinate system is built, and if not, the next steps are carried out: step 1, eliminating the single-point GPS position jumping errors; step 2, calculating the transverse motion errors according to the single-point GPS positioning information; step 3, calculating the heading speed errors; and step 4, calculating the sight line direction motion errors and compensating the motion errors in the airborne UWB SAR sight line direction. In the method of the invention, the information processing is only carried out on the output data of a navigation system, the motion parameter evaluation does not need to be carried out, the storage space and the calculation quantity are saved, and the large-area imaging compensation precision is high. In addition, the cost is low, and the realization is easy.