CN105046724A - Dual-image-point centroid extraction method in atmospheric coherent parameter test based on differential image motion - Google Patents

Dual-image-point centroid extraction method in atmospheric coherent parameter test based on differential image motion Download PDF

Info

Publication number
CN105046724A
CN105046724A CN201510447426.6A CN201510447426A CN105046724A CN 105046724 A CN105046724 A CN 105046724A CN 201510447426 A CN201510447426 A CN 201510447426A CN 105046724 A CN105046724 A CN 105046724A
Authority
CN
China
Prior art keywords
image
sigma
array
row
point
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201510447426.6A
Other languages
Chinese (zh)
Other versions
CN105046724B (en
Inventor
陈纯毅
杨华民
佟首峰
江伦
赵馨
张雷
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Henghui Photoelectric Measurement Technology Jilin Co ltd
Original Assignee
Changchun University of Science and Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Changchun University of Science and Technology filed Critical Changchun University of Science and Technology
Priority to CN201510447426.6A priority Critical patent/CN105046724B/en
Publication of CN105046724A publication Critical patent/CN105046724A/en
Application granted granted Critical
Publication of CN105046724B publication Critical patent/CN105046724B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30181—Earth observation
    • G06T2207/30192—Weather; Meteorology

Landscapes

  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Geometry (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Image Processing (AREA)
  • Image Analysis (AREA)

Abstract

The invention discloses a dual-image-point centroid extraction method in an atmospheric coherent parameter test based on differential image motion. The method can automatically divide a dual-image-point image into two single-image-point images without human assistance. For each single-image-point image, the method can automatically select a bounding box position of a single image point and eliminate the influence of pixels non-covered by the image point on centroid extraction to inhibit the reduction of the centroid extraction precision of the image point caused by output noise of an image sensor. According to the method, dual-light-spot centroid coordinates extracted in a test process are stored in a test record file in real time, so that a Fried parameter value can be calculated according to data in the test record file at any time after the test is finished.

Description

Double image point barycenter extracting method in the test of Differential Image motion air relevant parameters
Technical field
The invention belongs to atmospheric optics technical field of measurement and test, relate to the double image point barycenter extracting method in the test of a kind of Differential Image motion air relevant parameters.
Background technology
In the application such as optical communication, astronomical sight of star ground, often need the atmospheric turbulence intensity known on light transmission path.Usual atmospheric coherence length (i.e. Fried parameter) measures the turbulence intensity of whole atmosphere.At present, many documents are all mentioned, and measure the fluctuating of the difference of the light wave angle of arrival by the Differential Image method of movement, and then obtain Fried parameter value according to the theory relation between angle of arrival structure function and Fried parameter.The key measuring Fried parameter based on the Differential Image method of movement is, extract the barycenter of two picture points in the image of imageing sensor output.After the center-of-mass coordinate of two picture points obtaining a series of continuous print picture frame, can the direct basis theoretical model of having mercy in auspicious middle shown " Modern Atmospheric Optics ", calculate the difference of the angle of arrival corresponding to every two field picture at the component be parallel to and perpendicular to aperture center line direction with for a series of continuous print picture frame, can obtain a series of with value; A series of for this with value, calculate with mean value, just obtain the angle of arrival and to be parallel to and perpendicular to the structure function in aperture center line direction.For test at night, because starlight is fainter, cause the output signal-to-noise ratio of imageing sensor not high, the barycenter extraction accuracy impact of the various noises that imageing sensor exports on two picture points is very large.Carry out analysis to the double image dot image in the test of Differential Image motion air relevant parameters can find, not by those gray-scale values that picture point covers be greater than 0 image pixel in fact all affected by noise, if when extracting picture point barycenter, do not get rid of the impact of the image pixel that those are not covered by picture point, then when flicker causes picture point brightness very low, barycenter extracts error can be very large.The invention provides the double image point barycenter extracting method in the test of a kind of Differential Image motion air relevant parameters, when extracting picture point barycenter, automatically can get rid of the impact of most image pixel do not covered by picture point, barycenter extraction accuracy can be significantly improved.
Summary of the invention
The equipment that this method relates to comprises Differential Image method of movement measuring optical system, imageing sensor and computing machine; As shown in Figure 1, starlight incides in two input apertures of Differential Image method of movement measuring optical system after atmospheric envelope transmission, reentering after conversion is mapped on imageing sensor, the double image dot image that imageing sensor exports is transmitted to computing machine, completes the extraction of double image point center-of-mass coordinate on computers.As shown in Figure 2, the initial point of coordinate system is arranged on the lower left corner of double image dot image, the x-axis direction of coordinate system is set to the horizontal direction along double image dot image, the y-axis direction of coordinate system is set to the vertical direction along double image dot image; When installing Differential Image method of movement measuring optical system and imageing sensor, guarantee that the double image point barycenter line of the double image dot image exported without imageing sensor during Turbulent Flow Effects is parallel to the horizontal direction of double image dot image.
The performing step of this method:
Step001: start-up simulation machine, the double image dot image that continuous acquisition n frame sends from imageing sensor, n >=10; Utilize computer program, in the internal memory of computing machine, create one comprise total number of lines of pixels that M is capable, the two-dimensional array IMAG of N column element, M are double image dot image, N is total pixel columns of double image dot image; By all elements of array IMAG all assignment be 0; To I=1,2 ..., M, J=1,2 ..., N, calculates that the I of all n frame double image dot image collected is capable, the gray-scale value sum A001 of J row pixel, gray-scale value sum A001 is capable to the I of array IMAG divided by the result assignment of n, J column element;
Step002: utilize computer program, creates the one-dimension array HIST that comprises N number of element in the internal memory of computing machine; To J=1,2 ..., N, all elements value sum assignment that the J of array IMAG is arranged is to HIST J element:
Step003: divided by result assignment to variable X S, HIST(J) represent the value of J the element of array HIST; Order expression rounds up;
Step004: if receive stopping test command, go to step Step008, otherwise gather the new double image dot image A002 sent from imageing sensor of a frame; The gray-scale value of the pixel of the 1st of image A002 the capable to M, the 1st to Idx row is saved in one and comprises that M is capable, in the two-dimensional array A003 of Idx column element, namely to I=I, 2,, M, J=1,2,, Idx, capable to the I of array A003 for gray-scale value assignment that is capable for the I of image A002, J row pixel, J column element; The gray-scale value of the pixel that the 1st of image A002 the capable to M, Idx+1 to N are arranged is saved in one and comprises that M is capable, in the two-dimensional array A004 of N-Idx column element, namely to I=1,2,, M, J=Idx+1, Idx+2,, N, capable to the I of array A004 for gray-scale value assignment that is capable for the I of image A002, J row pixel, J-Idx column element;
Step005: the numbering MI of row and the numbering MJ of row that find out the maximum element place of the value of array A003, if the maximal value of the element in array A003 corresponds to multiple element simultaneously, then find out the numbering MI of row and the numbering MJ of row at any one maximal value element place wherein; Make i1=max (1, MI-W), i2=min (M, MI+W), j1=max (1, MJ-W), j2=min (Idx, MJ+W), max (X, Y) represents the maximal value of getting among X and Y, min (X, Y) represent the minimum value of getting among X and Y, W is integer, and W represents half length of side of picture point bounding box; Be calculated as follows expression formula: c li = Σ I = i 1 i 2 Σ J = j 1 j 2 I × A 003 ( I , J ) Σ I = i 1 i 2 Σ J = j 1 j 2 A 003 ( I , J ) With c lj = Σ I = i 1 i 2 Σ J = j 1 j 2 J × A 003 ( I , J ) Σ I = i 1 i 2 Σ J = j 1 j 2 A 003 ( I , J ) , Wherein A003 (I, J) represents that the I of array A003 is capable, the value of the element of J row;
Step006: the numbering MI of row and the numbering MJ of row that find out the maximum element place of the value of array A004, if the maximal value of the element in array A004 corresponds to multiple element simultaneously, then find out the numbering MI of row and the numbering MJ of row at any one maximal value element place wherein; Make i1=max (1, MI-W), i2=min (M, MI+W), j1=max (1, MJ-W), j2=min (N-Idx, MJ+W); Be calculated as follows expression formula:
c ri = Σ I = i 1 i 2 Σ J = j 1 j 2 I × A 004 ( I , J ) Σ I = i 1 i 2 Σ J = j 1 j 2 A 004 ( I , J ) With c rj = Σ I = i 1 i 2 Σ J = j 1 j 2 J × A 004 ( I , J ) Σ I = i 1 i 2 Σ J = j 1 j 2 A 004 ( I , J ) , Wherein A004 (I, J) represents that the I of array A004 is capable, the value of the element of J row;
Step007: utilize computer program to the center-of-mass coordinate of test record file output double image point, wherein the x coordinate of the barycenter of left picture point is (c lj-0.5) × w p, the y coordinate of the barycenter of left picture point is (c li-0.5) × h p, the x coordinate of the barycenter of right picture point is (c rj+ Idx-0.5) × w p, the y coordinate of the barycenter of right picture point is (c ri-0.5) × h p, w prepresent the width of the pixel of imageing sensor, h prepresent the height of the pixel of imageing sensor; Order go to step Step004;
Step008: stop double image point barycenter to extract operation.
Beneficial effect
The invention provides the double image point barycenter extracting method in the test of a kind of Differential Image motion air relevant parameters, in test process, this method can when without the need to being automatically divided into two single picture point images when human assistance by double image dot image, and automatically choose the bounding box position of single picture point, to get rid of the impact of the pixel that those are not covered by picture point, thus the output noise reducing imageing sensor is on the impact of picture point barycenter extraction accuracy.This method can be kept at the center-of-mass coordinate data of double image point in test record file in real time in test process.After test completes, Fried parameter value can be calculated according to the data in test record file at any time.
Accompanying drawing explanation
Fig. 1 is the hardware device composition schematic diagram that this method relates to.Fig. 2 is the relation of double image dot image and coordinate system.
Embodiment
In order to make the feature and advantage of this method clearly understand, below in conjunction with specific embodiment, this method is further described.In the present embodiment, make n=20, use the height of the pixel imageing sensor equal with width to detect double image dot image.
The equipment that this method relates to comprises Differential Image method of movement measuring optical system, imageing sensor and computing machine; As shown in Figure 1, starlight incides in two input apertures of Differential Image method of movement measuring optical system after atmospheric envelope transmission, reentering after conversion is mapped on imageing sensor, the double image dot image that imageing sensor exports is transmitted to computing machine, completes the extraction of double image point center-of-mass coordinate on computers.As shown in Figure 2, the initial point of coordinate system is arranged on the lower left corner of double image dot image, the x-axis direction of coordinate system is set to the horizontal direction along double image dot image, the y-axis direction of coordinate system is set to the vertical direction along double image dot image; When installing Differential Image method of movement measuring optical system and imageing sensor, guarantee that the double image point barycenter line of the double image dot image exported without imageing sensor during Turbulent Flow Effects is parallel to the horizontal direction of double image dot image.
The performing step of this method:
Step001: start-up simulation machine, the double image dot image that continuous acquisition n frame sends from imageing sensor, n >=10; Utilize computer program, in the internal memory of computing machine, create one comprise total number of lines of pixels that M is capable, the two-dimensional array IMAG of N column element, M are double image dot image, N is total pixel columns of double image dot image; By all elements of array IMAG all assignment be 0; To I=1,2 ..., M, J=1,2 ..., N, calculates that the I of all n frame double image dot image collected is capable, the gray-scale value sum A00I of J row pixel, gray-scale value sum A00I is capable to the I of array IMAG divided by the result assignment of n, J column element;
Step002: utilize computer program, creates the one-dimension array HIST that comprises N number of element in the internal memory of computing machine; To J=1,2 ..., N, all elements value sum assignment that the J of array IMAG is arranged is to HIST J element;
Step003: divided by result assignment represent the value of J the element of array HIST to variable X S, HIST (J); Order expression rounds up;
Step004: if receive stopping test command, go to step Step008, otherwise gather the new double image dot image A002 sent from imageing sensor of a frame; The gray-scale value of the pixel of the 1st of image A002 the capable to M, the 1st to Idx row is saved in one and comprises that M is capable, in the two-dimensional array A003 of Idx column element, namely to I=1,2,, M, J=1,2,, Idx, capable to the I of array A003 for gray-scale value assignment that is capable for the I of image A002, J row pixel, J column element; The gray-scale value of the pixel that the 1st of image A002 the capable to M, Idx+1 to N are arranged is saved in one and comprises that M is capable, in the two-dimensional array A004 of N-Idx column element, namely to I=1,2,, M, J=Idx+1, Idx+2,, N, capable to the I of array A004 for gray-scale value assignment that is capable for the I of image A002, J row pixel, J-Idx column element;
Step005: the numbering MI of row and the numbering MJ of row that find out the maximum element place of the value of array A003, if the maximal value of the element in array A003 corresponds to multiple element simultaneously, then find out the numbering MI of row and the numbering MJ of row at any one maximal value element place wherein; Make i1=max (1, MI-W), i2=min (M, MI+W), j1=max (1, MJ-W), j2=min (Idx, MJ+W), max (X, Y) represents the maximal value of getting among X and Y, min (X, Y) represent the minimum value of getting among x and Y, W is integer, and W represents half length of side of picture point bounding box; Be calculated as follows expression formula: c li = Σ I = i 1 i 2 Σ J = j 1 j 2 I × A 003 ( I , J ) Σ I = i 1 i 2 Σ J = j 1 j 2 A 003 ( I , J ) With c lj = Σ I = i 1 i 2 Σ J = j 1 j 2 J × A 003 ( I , J ) Σ I = i 1 i 2 Σ J = j 1 j 2 A 003 ( I , J ) , The wherein value of the element of the I of A003 (I, J) registration group A003 capable, J row;
Step006: the numbering MI of row and the numbering MJ of row that find out the maximum element place of the value of array A004, if the maximal value of the element in array A004 corresponds to multiple element simultaneously, then find out the numbering MI of row and the numbering MJ of row at any one maximal value element place wherein; Make i1=max (1, MI-W), i2=min (M, MI+W), j1=max (1, MJ-W), j2=min (N-Idx, MJ+W); Be calculated as follows expression formula:
c ri = Σ I = i 1 i 2 Σ J = j 1 j 2 I × A 004 ( I , J ) Σ I = i 1 i 2 Σ J = j 1 j 2 A 004 ( I , J ) With c rj = Σ I = i 1 i 2 Σ J = j 1 j 2 J × A 004 ( I , J ) Σ I = i 1 i 2 Σ J = j 1 j 2 A 004 ( I , J ) , Wherein A004 (I, J) represents that the I of array A004 is capable, the value of the element of J row;
Step007: utilize computer program to the center-of-mass coordinate of test record file output double image point, wherein the x coordinate of the barycenter of left picture point is (c lj-0.5) × w p, the y coordinate of the barycenter of left picture point is (c li-0.5) × h p, the x coordinate of the barycenter of right picture point is (c rj+ Idx-0.5) × w p, the y coordinate of the barycenter of right picture point is (c ri-0.5) × h p, w prepresent the width of the pixel of imageing sensor, h prepresent the height of the pixel of imageing sensor; Order go to step Step004;
Step008: stop double image point barycenter to extract operation.
The choosing method of the value of the parameter W in step Step005 and step Step006: before the test begins, use the double image dot image that computing machine continuous acquisition 80 two field picture sensor sends, use the image addition operation in Computer Image Processing, this 80 frame double image dot image is superimposed, obtain a new double image dot image B001, the image spot size in double image dot image B001 can be larger than the image spot size in the single frames double image dot image of computer acquisition; Double image dot image B001 draws a foursquare bounding box BBOX, the size arranging bounding box BBOX is minimum can surround the size that left picture point can surround again right picture point, as shown in Figure 2, the bounding box that in figure, left and right picture point is corresponding is two bounding boxes that the length of side is identical.The image pixel number NP that computation bound frame BBOX covers, order

Claims (1)

1. Differential Image motion air relevant parameters test in double image point barycenter extracting method, it is characterized in that, required equipment and performing step as follows:
The equipment that this method relates to comprises Differential Image method of movement measuring optical system, imageing sensor and computing machine; Starlight incides in two input apertures of Differential Image method of movement measuring optical system after atmospheric envelope transmission, reentering after conversion is mapped on imageing sensor, the double image dot image that imageing sensor exports is transmitted to computing machine, completes the extraction of double image point center-of-mass coordinate on computers; The initial point of coordinate system is arranged on the lower left corner of double image dot image, the x-axis direction of coordinate system is set to the horizontal direction along double image dot image, the y-axis direction of coordinate system is set to the vertical direction along double image dot image; When installing Differential Image method of movement measuring optical system and imageing sensor, guarantee that the double image point barycenter line of the double image dot image exported without imageing sensor during Turbulent Flow Effects is parallel to the horizontal direction of double image dot image;
The performing step of this method:
Step001: start-up simulation machine, the double image dot image that continuous acquisition n frame sends from imageing sensor, n >=10; Utilize computer program, in the internal memory of computing machine, create one comprise total number of lines of pixels that M is capable, the two-dimensional array IMAG of N column element, M are double image dot image, N is total pixel columns of double image dot image; By all elements of array IMAG all assignment be 0; To I=1,2 ..., M, J=1,2 ..., N, calculates that the I of all n frame double image dot image collected is capable, the gray-scale value sum A001 of J row pixel, gray-scale value sum A001 is capable to the I of array IMAG divided by the result assignment of n, J column element;
Step002: utilize computer program, creates the one-dimension array HIST that comprises N number of element in the internal memory of computing machine; To J=1,2 ..., N, all elements value sum assignment that the J of array IMAG is arranged is to HIST J element;
Step003: divided by result assignment represent the value of J the element of array HIST to variable X S, HIST (J); Order expression rounds up;
Step004: if receive stopping test command, go to step Step008, otherwise gather the new double image dot image A002 sent from imageing sensor of a frame; The gray-scale value of the pixel of the 1st of image A002 the capable to M, the 1st to 1dx row is saved in one and comprises that M is capable, in the two-dimensional array A003 of Idx column element, namely to I=1,2,, M, J=1,2,, Idx, capable to the I of array A003 for gray-scale value assignment that is capable for the I of image A002, J row pixel, J column element; The gray-scale value of the pixel that the 1st of image A002 the capable to M, 1dx+1 to N are arranged is saved in one and comprises that M is capable, in the two-dimensional array A004 of N-Idx column element, namely to I=1,2,, M, J=Idx+1, Idx+2,, N, capable to the I of array A004 for gray-scale value assignment that is capable for the I of image A002, J row pixel, J-Idx column element;
Step005: the numbering MI of row and the numbering MJ of row that find out the maximum element place of the value of array A003, if the maximal value of the element in array A003 corresponds to multiple element simultaneously, then find out the numbering MI of row and the numbering MJ of row at any one maximal value element place wherein; Make i1=max (1, MI-W), i2=min (M, MI+W), j1=max (1, MJ-W), j2=min (Idx, MJ+W), max (X, Y) represents the maximal value of getting among X and Y, min (X, Y) represent the minimum value of getting among X and Y, W is integer, and W represents half length of side of picture point bounding box; Be calculated as follows expression formula:
c li = Σ I = i 1 i 2 Σ J = j 1 j 2 I × A 003 ( I , J ) Σ I = i 1 i 2 Σ J = j 1 j 2 A 003 ( I , J ) With c lj = Σ I = i 1 i 2 Σ J = j 1 j 2 J × A 003 ( I , J ) Σ I = i 1 i 2 Σ J = j 1 j 2 A 003 ( I , J ) , Wherein A003 (I, J) represents that the I of array A003 is capable, the value of the element of J row;
Step006: the numbering MI of row and the numbering MJ of row that find out the maximum element place of the value of array A004, if the maximal value of the element in array A004 corresponds to multiple element simultaneously, then find out the numbering MI of row and the numbering MJ of row at any one maximal value element place wherein; Make i1=max (1, MI-W), i2=min (M, MI+W), j1=max (1, MJ-W), j2=min (N-Idx, MJ+W); Be calculated as follows expression formula:
c ri = Σ I = i 1 i 2 Σ J = j 1 j 2 I × A 004 ( I , J ) Σ I = i 1 i 2 Σ J = j 1 j 2 A 004 ( I , J ) With c rj = Σ I = i 1 i 2 Σ J = j 1 j 2 I × A 004 ( I , J ) Σ I = i 1 i 2 Σ J = j 1 j 2 A 004 ( I , J ) , Wherein A004 (I, J) represents that the I of array A004 is capable, the value of the element of J row;
Step007: utilize computer program to the center-of-mass coordinate of test record file output double image point, wherein the x coordinate of the barycenter of left picture point is (c lj-0.5) × w p, the y coordinate of the barycenter of left picture point is (c li-0.5) × h p, the x coordinate of the barycenter of right picture point is (c rj+ Idx-0.5) × w p, the y coordinate of the barycenter of right picture point is (c ri-0.5) × h p, w prepresent the width of the pixel of imageing sensor, h prepresent the height of the pixel of imageing sensor; Order go to step Step004;
Step008: stop double image point barycenter to extract operation.
CN201510447426.6A 2015-07-21 2015-07-21 Double image point barycenter extracting method in Differential Image motion air relevant parameters test Active CN105046724B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510447426.6A CN105046724B (en) 2015-07-21 2015-07-21 Double image point barycenter extracting method in Differential Image motion air relevant parameters test

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510447426.6A CN105046724B (en) 2015-07-21 2015-07-21 Double image point barycenter extracting method in Differential Image motion air relevant parameters test

Publications (2)

Publication Number Publication Date
CN105046724A true CN105046724A (en) 2015-11-11
CN105046724B CN105046724B (en) 2017-10-24

Family

ID=54453241

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510447426.6A Active CN105046724B (en) 2015-07-21 2015-07-21 Double image point barycenter extracting method in Differential Image motion air relevant parameters test

Country Status (1)

Country Link
CN (1) CN105046724B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107741280A (en) * 2017-11-22 2018-02-27 长春理工大学 Light beam forward direction turbulence transfer drift angle and reverse transfer angle of arrival coefficient correlation measuring method

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5537209A (en) * 1994-01-14 1996-07-16 Sparta, Inc. An interferometric measuring system having temperature compensation and improved optical configurations
CN102778300A (en) * 2012-07-27 2012-11-14 中国科学院长春光学精密机械与物理研究所 Method for stably measuring atmospheric coherence length
CN103578088A (en) * 2013-11-20 2014-02-12 中国人民解放军海军大连舰艇学院 Method for processing star image
CN104034353A (en) * 2014-06-06 2014-09-10 中国科学院长春光学精密机械与物理研究所 Computing method of digital sun sensor centroid based on detecting window

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5537209A (en) * 1994-01-14 1996-07-16 Sparta, Inc. An interferometric measuring system having temperature compensation and improved optical configurations
CN102778300A (en) * 2012-07-27 2012-11-14 中国科学院长春光学精密机械与物理研究所 Method for stably measuring atmospheric coherence length
CN103578088A (en) * 2013-11-20 2014-02-12 中国人民解放军海军大连舰艇学院 Method for processing star image
CN104034353A (en) * 2014-06-06 2014-09-10 中国科学院长春光学精密机械与物理研究所 Computing method of digital sun sensor centroid based on detecting window

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107741280A (en) * 2017-11-22 2018-02-27 长春理工大学 Light beam forward direction turbulence transfer drift angle and reverse transfer angle of arrival coefficient correlation measuring method

Also Published As

Publication number Publication date
CN105046724B (en) 2017-10-24

Similar Documents

Publication Publication Date Title
CN106796716B (en) For providing the device and method of super-resolution for low-resolution image
US10302420B2 (en) Method for reconstructing a surface using spatially structured light and a dynamic vision sensor
CN101465002B (en) Method for orientating secondary pixel edge of oval-shaped target
CN103702015B (en) Exposure control method for human face image acquisition system under near-infrared condition
CN104240264B (en) The height detection method and device of a kind of moving object
CN101650828B (en) Method for reducing random error of round object location in camera calibration
CN105678757B (en) A kind of ohject displacement measuring method
CN109472819A (en) A kind of binocular parallax estimation method based on cascade geometry context neural network
CN103871039B (en) Generation method for difference chart in SAR (Synthetic Aperture Radar) image change detection
CN109978786A (en) A kind of Kinect depth map restorative procedure based on convolutional neural networks
CN111043988A (en) Single stripe projection measurement method based on graphics and deep learning
CN103440648B (en) The method for automatic measurement of corps canopy regularity and device
CN104809724A (en) Automatic precise registration method for multiband remote sensing images
CN112116720A (en) Three-dimensional point cloud augmentation method and device, storage medium and computer equipment
CN101504770A (en) Structural light strip center extraction method
CN104835177A (en) Star point segmentation method under interference of moonlight and FPGA device of star point segmentation method
CN113628170B (en) Laser line extraction method and system based on deep learning
CN102982567B (en) The deformable body collision detection elimination method that a kind of Corpus--based Method is analyzed
CN107180310A (en) A kind of method for automatically determining job site safety sign board layout area
CN105046724A (en) Dual-image-point centroid extraction method in atmospheric coherent parameter test based on differential image motion
CN104502992B (en) Weak point target precisely positioning method and system based on space-time oversampling and scanning
CN104200460A (en) Image registration method based on images characteristics and mutual information
CN104867169B (en) A kind of infrared sensor physical effect real time imagery emulation mode based on GPU
CN104065853A (en) Infrared camera crosstalk eliminating method
Yang et al. Research on recognition for cotton spider mites’ damage level based on deep learning

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20211215

Address after: 130041 room 1618, building B, Sino Italian international, Changchun Economic Development Zone, Jilin Province

Patentee after: Jilin Henghui Photoelectric Technology Co.,Ltd.

Address before: 130022 No. 7089 Satellite Road, Jilin, Changchun

Patentee before: CHANGCHUN University OF SCIENCE AND TECHNOLOGY

TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20230605

Address after: Room 305 and 306, Dongfu Building, Zone 3, Entrepreneurship Service Center, No. 6666, Ecological Street, Jingyue Hi tech Industrial Development Zone, Changchun, 130000, Jilin

Patentee after: Henghui Photoelectric Measurement Technology (Jilin) Co.,Ltd.

Address before: 130041 room 1618, building B, Sino Italian international, Changchun Economic Development Zone, Jilin Province

Patentee before: Jilin Henghui Photoelectric Technology Co.,Ltd.

DD01 Delivery of document by public notice
DD01 Delivery of document by public notice

Addressee: Chang Rui

Document name: Notification of Qualified Procedures