12 results about "Line Spread Function" patented technology

The invention discloses an SAR (Synthetic Aperture Radar) image MTF (Modulation Transfer Function) quality evaluation method and system based on a natural scene edge, and the method comprises the steps: building a selection standard system for automatic edge screening of a natural scene SAR image, and determining a high-contrast linear edge according to the standard system; automatically detecting a high-contrast linear edge in the natural scene, and intercepting a region of interest for subsequent calculation based on the position of the linear edge; gray level distribution is extracted in the normal direction of the linear edge, and an edge spread function is constructed and used for describing gray level transition response of the imaging system in the edge area; carrying out normalization and smoothing processing on the edge spread function, and carrying out spatial domain first-order differential calculation to obtain a line spread function; and performing fast Fourier transform on the line spread function to obtain a modulation degree transfer function curve, and representing the detail transfer capability of the system under different spatial frequencies. According to the method, the imaging quality of the SAR image of the natural scene can be automatically, accurately and quantitatively evaluated under the condition that manual field arrangement is not needed.

The invention relates to a geometric parameter calculation and performance evaluation algorithm based on an integrated motif, which is applied to the integrated motif comprising a geometric parameter calculation module, a spatial resolution module, a contrast module, a uniformity module and a spatial accuracy module. Comprising the following steps: calculating geometric parameters of a CBCT system by using position information of a metal ball in a geometric parameter calculation module and known information; acquiring a line spread function of the metal wire by using position information and known information of the metal wire in the spatial resolution module, and then calculating the spatial resolution; sampling by using position information and known information of an annular insertion block in the contrast module; automatically selecting a center area and a peripheral area of a uniformity module to carry out gray value average value calculation to obtain uniformity information of the image; and the distance and the included angle between the positioning small holes are calculated by using the position information of the positioning small holes in the space accuracy module and known information. According to the invention, high-frequency, high-precision and low-cost performance evaluation requirements in the research and development process can be met.

The invention relates to the technical field of interference spectrum data simulation, in particular to an interference spectrum data simulation generation method based on a DFDI system, and the method comprises the steps: extracting an absorption line characteristic parameter from a standard fixed star spectrum database, combining an interferometer fixed optical path difference parameter, and generating interference fringe distribution by using an equal thickness interference principle; carrying out convolution modulation by adopting a spectrograph line spread function to obtain a continuous interference spectrum image, and carrying out discretization sampling to generate a digital data matrix; generating a diversified data set through parameterization adjustment, and adding Poisson distribution noise to simulate a real observation environment; and formatting the noise data into a dual-channel image, and finally realizing the inversion of the radial velocity through the training of the convolutional neural network. According to the method, the problem of insufficient training samples caused by scarcity of real DFDI data is solved, and the phase feature extraction precision of the interference fringes and the inversion reliability of the radial velocity are improved.

This invention discloses a method and system for restoring defocused images based on estimating the point spread function from a spot image. The method includes: 1) reading the original spot image and the defocused blurred image; 2) cropping the area where the spot is located; 3) projecting the cropped spot image into grayscale along the vertical axis to obtain the original line spread function curve; 4) performing Gaussian fitting on the original line spread function curve to obtain a smooth line spread function curve; and then calculating the standard deviation of the Gaussian function; 5) calculating the blur coefficient of the Gaussian defocus model using the standard deviation; 6) substituting the blur coefficient into the Gaussian defocus model to obtain the point spread function; 7) performing Wiener filtering on the defocused blurred image in the frequency domain to obtain the initial restored image in the frequency domain; 8) performing a second Wiener filtering on the initial restored image to obtain the final restored image in the frequency domain; and 9) performing an inverse Fourier transform to obtain the restored image. This invention effectively reduces the blurriness of defocused images and solves the problem of computational complexity.

This application provides a dynamic star point localization method, apparatus, and device based on an effective line spread function, relating to the field of optical imaging measurement technology. The method includes: estimating the trailing parameters of a star point image based on the coarsely estimated coordinate position changes of the star point image on adjacent frames of starscape images; the coarsely estimated coordinate position characterizing the center position coordinates of the star point image obtained by calculating the centroid of the star point image using the threshold centroid method; establishing an effective line spread function under the current motion conditions based on an effective point spread function pre-established under static imaging conditions, and combining the trailing parameters; the effective line spread function characterizing the energy distribution pattern of the trailing star point image obtained by integrating the effective point spread function along the trailing trajectory; and using the effective line spread function to perform localization calculations on the imaging data of the trailing star point image to obtain a finely estimated coordinate of the star point image.

The invention discloses a method for high-precision measurement of a modulation transfer function (MTF) of an optical system, and relates to the field of optical measurement. The method comprises the following steps of: acquiring a digital image of a slit target, and obtaining an accurate centroid position of a slit in each pixel row through a centroid positioning algorithm of an iterative adaptive window function for each pixel row intersected with the slit in the image. The method comprises the following steps: carrying out linear fitting on an accurate mass center position, calculating an accurate inclination angle of a slit relative to an image sensor pixel array, determining a super-sampling interval by using a geometrical relationship, constructing a super-sampling line spread function (SSLSF), and finally carrying out correction by using a joint correction model through Fourier transform to obtain an accurate MTF (Modulation Transform Function). According to the method, the problem of inaccurate MTF measurement caused by image noise and detector sampling frequency limitation in the prior art is solved, and the MTF measurement precision and the anti-noise capability are remarkably improved.

The embodiment of the application provides an MTF testing method and device for an AR projection light machine, comprising: acquiring a projection test target, wherein the projection test target is a cross slit bright line; collecting a test projection image corresponding to the projection test target; based on the test projection image, scanning along the direction perpendicular to the extension direction of each bright line in the cross slit bright line respectively, and determining the brightness data of each corresponding scanning position; performing brightness feature extraction on the brightness data of each corresponding scanning position to obtain an effective brightness data sequence; based on the effective brightness data sequence, constructing a line spread function; and based on the line spread function, determining a test result. Through the cross slit bright line test target combined with directional scanning, brightness feature extraction and line spread function construction, the imaging quality of the AR projection light machine is accurately tested, and the reliability and applicability of the test result are improved.

This invention discloses a method and system for improving the stability of a coherent dispersive spectrometer based on cross-cancellation, belonging to the field of spectral imaging technology. It includes acquiring two interference spectra with a phase difference of π in an asymmetric coherent dispersive system; separating the local spectrum and interference spectrum through addition and subtraction; performing Fourier transform on both to obtain the local spectrum and interference spectrum in the frequency domain; determining the optical path difference based on the grating line spread function and signal-to-noise ratio condition; and dividing the interference spectrum into a first component region and a second component region; determining the weights using a phase residual optimization method within the frequency range from zero to the optical path difference; and performing a weighted summation of the spectral components of the local spectrum and the first component region to obtain the mixed spectrum after cross-cancellation. This invention further improves spectral resolution through high-frequency stitching and suppresses ringing effects through equalization processing. This invention significantly improves system stability and spectral resolution without increasing system size and complexity.

The present application relates to a kind of image restoration methods of fitting PSF, including S1, extract actual image LSF, actual image LSF is converted into the linear combination of Gaussian second derivative;S2, according to the linear combination of Gaussian second derivative, actual line spread function is fitted and corrected;S3, using actual line spread function after fitting and correction, generate restoration image.The method of the present application extracts actual image line spread function, and it is modeled into the form of linear combination of a series of Gaussian second derivative;Then, based on the Gaussian second derivative model established, the LSF extracted from blurred image is fitted and corrected;Finally, blurred image is restored using PSF after fitting and correction, and finally clear image is obtained.Compared with the prior art image restoration method, the method of the present application can produce clearer restoration image when facing high blur degree original image.

The invention discloses a semi-automatic ground resolution distance measurement method for an in-orbit medium-resolution remote sensing image. The method comprises the following steps: S1, selecting natural targets and constructing a target library; s2, extracting target sub-pixels and generating a profile coordinate set; s3, extracting a gray value sequence of a normalized image from the obtained coordinate set of the section, constructing a section matrix and averaging according to rows to obtain an average edge spread function, performing first-order difference operation on the edge spread function to obtain a line spread function, and further performing normalization processing on the line spread function; s4, extracting a peak value of the normalized line spread function curve and a corresponding half peak value position, determining a distance between half peak points on the left side and the right side through linear interpolation, taking the distance as a width metric value, and multiplying the width metric value by a ground sampling distance of the satellite image to obtain a ground resolution distance value; and S5, summarizing and outputting results. The method is applied to the technical field of remote sensing image measurement or surveying and mapping geographic information services.

The invention belongs to the technical field of image quality online detection, and particularly relates to a camera modulation transfer function estimation method and system based on a pulse neural network, and the method comprises the steps: obtaining a test image collected by a camera, and selecting a region of interest from the test image; performing gray scale differential coding on the ROI image in the continuous time window to generate a sparse pulse sequence; the pulse sequence is input into a pulse neural network, and the pulse neural network is constructed based on a leakage integration distribution model and is used for carrying out feature extraction and dynamic contrast reconstruction on the pulse sequence and outputting a corresponding pulse response; gaussian smoothing and deconvolution are carried out on the impulse response, and a high-precision line spread function is reconstructed; carrying out fast Fourier transform on the modulation transfer function curve to obtain a complete modulation transfer function curve; by using an event-driven mechanism and sparse calculation characteristics of the spiking neural network, ultralow-power-consumption and ultralow-delay MTF estimation at the embedded front end is realized, and the requirement of online full inspection of a high-speed production line is met.

The application discloses a kind of semi-automatic ground resolution distance measurement methods of on-orbit medium resolution remote sensing image.The present application includes the following steps: step S1.natural target selection and target database construction;Step S2.target subpixel extraction and profile coordinate set generation;Step S3.the coordinate set of obtained profile extracts the gray value sequence of normalized image, constructs profile matrix and averages by row, obtains average edge spread function, carries out first-order difference operation to edge spread function, obtains line spread function, further carries out normalization processing to line spread function;Step S4.extract the peak value of normalized line spread function curve and its corresponding half-peak position, determine the distance between left and right half-peak points by linear interpolation, as the measure of width, multiply the measure of width with the ground sampling distance of satellite image, obtain ground resolution distance value;Step S5: result summary output.The present application is applied to the technical field of remote sensing image measurement or surveying and mapping geographic information service.