CN101446483A - Photoelectric tracking macro-pixel iterative centroid method - Google Patents
Photoelectric tracking macro-pixel iterative centroid method Download PDFInfo
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- CN101446483A CN101446483A CNA2008102372959A CN200810237295A CN101446483A CN 101446483 A CN101446483 A CN 101446483A CN A2008102372959 A CNA2008102372959 A CN A2008102372959A CN 200810237295 A CN200810237295 A CN 200810237295A CN 101446483 A CN101446483 A CN 101446483A
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Abstract
During a photoelectric-tracking process, a photoelectronic tracking device adopts a photoelectric tracking macro-pixel iterative centroid method to process image data: spot images are obtained firstly, an objective macro-pixel and the centroid initial value of the objective macro-pixel are determined, and a rough estimation for the centroid is finished; after multiple iteration of the objective macro-pixel, the centroid of the objective macro-pixel is accurately obtained, and position error signals are obtained according to the centroid of an ideal image and the centroid of the objective macro-pixel; and the photoelectronic tracking device is adjusted according to the position error signals, and the tracking for light source is achieved. The invention has the advantages of less iteration steps, less calculated amount, quick positioning speed, strong anti-noise capability, high objective pixel coverage rate, high positioning accuracy and little errors, and is applicable to high accuracy positioning for asymmetric spot images with a low signal-to-noise ratio.
Description
Technical field
The invention belongs to the location algorithm field, specifically is a kind of high precision macro-pixel iterative centroid method that is applicable to photoelectric tracking.
Background technology
In fields such as automobile collision preventing warning system, intelligent robot, radar, communications, photoelectric tracking is a kind of very attractive technology.In photoelectric tracking, must accurately locate, obtain the error signal of degree of precision, finish photoelectric tracking according to error signal by controller and topworks then.Low noise resisting ability and acquisition speed are more greatly the subject matter of location algorithm in the present photoelectric tracking.
In the photoelectric tracking, generally adopt centroid method (or centroid method) location, this method is at first carried out filter preprocessing to laser image, then by formula
Obtain barycenter, wherein N is the total number of pixels of image, and I (k) is the gray-scale value of k pixel.Centroid algorithm is all done weighting to all pixels of entire image, can make full use of the gray-scale value of every bit in the image.But all pixels are obtained, influenced locating speed.Under the situation of circle Gauss light spot image, utilize centroid method can obtain bearing accuracy preferably; But for asymmetric hot spot image, when signal to noise ratio (S/N ratio) hour, the barycenter precision is relatively poor.So traditional centroid method also is not suitable for the location of the asymmetric target image of low signal-to-noise ratio.
Zeev Z has proposed the iterative center of mass algorithm, and this method is at first carried out guestimate to barycenter: (1) presses certain initial threshold with the view data thresholding; Obtain the initial value of barycenter with the way of seeking peak value; (2) the big or small M in target area (ROI) is set
1* M
1, obtain the barycenter in the ROI; (3) barycenter that obtains out by above-mentioned steps (2) upgrades ROI, obtains barycenter once more in new ROI; Obtain barycenter C (1) after repeating several times.
And then accurately obtain barycenter: (1) reduces initial threshold, behind the thresholding, is that size is 2 with the image division in the ROI
i* 2
iIndividual grand pixel (i is a number of iterations, i 〉=0) adopts formula C (i)=F (i) C (i)+[1-F (i)] C (i-1) to obtain C (i), and wherein C (i) is average grand pixel barycenter, and F (i) is the weights functions, and F (i) uses formula
Expression, wherein r (i) is a proportion function.(2) repeat (1), i<log
2M
1The barycenter iteration guarantees precision preferably by iteration.But use iteration to influence the speed of location too continually, and this method to be used in the asymmetric hot spot image of low signal-to-noise ratio bearing accuracy lower.
The shortcoming of existing location algorithm: calculated amount is big, and locating speed is slow, and a little less than the noise resisting ability, bearing accuracy is low, and error is big, is not suitable for the location of the asymmetric hot spot image of low signal-to-noise ratio.
Summary of the invention
The purpose of this invention is to provide that a kind of calculated amount is little, locating speed is fast, noise resisting ability is strong, bearing accuracy is high, error is little and be applicable to the high-precision locating method of the asymmetric hot spot image of low signal-to-noise ratio.
For achieving the above object, a kind of photoelectric tracking macro-pixel iterative centroid method of the present invention, its key is, carries out according to following steps:
Step 2 is determined the target macro pixel R of light spot image S, carries out according to following several steps:
The first step is determined initial threshold I
Th, its expression formula is: I
Th=(I
a-I
Min)/40, wherein, I
aBe the average gray value of described light spot image S, I
MinIt is the minimum gradation value of this light spot image S;
Second step is with described initial threshold I
ThTo described light spot image S thresholding, obtain thresholding light spot image S ';
Gray-scale value with the light spot image of grandfather tape noise deducts initial threshold I
Th, obtain the view data behind the thresholding; Thresholding can reduce ground unrest.
The 3rd step, divide described thresholding light spot image S ' step by step, obtain best grand pixel divide value M according to peak signal pixel coverage and less calculated amount principle
0* N
0, wherein said M
0Be the best grand pixel divide value of x direction, satisfy M
0=2
m-2, m is the positive integer greater than 1; Described N
0Be the best grand pixel divide value of y direction, satisfy N
0=2
n-2, n is the positive integer greater than 1;
The 4th step is according to the grand pixel divide value of described the best M
0* N
0Repartition described thresholding light spot image S ', obtain elementary grand pixel groups;
M according to the best
0And N
0Divide original image, can obtain the grand pixel of target coverage rate maximum, improve bearing accuracy; Select suitable M
0And N
0Can significantly reduce calculated amount; M
0Satisfy M
0=2
m-2, N
0Satisfy N
0=2
n-2 can be conveniently to the division of target macro pixel R, the acquisition time when reducing iteration.
The 5th step, the gray-scale value of each elementary grand pixel in the more described elementary grand pixel groups, the elementary grand pixel R of acquisition gray-scale value maximum
Max
The gray-scale value of grand pixel is the gray-scale value sum of pixel that this grand pixel comprises.
The 6th step is with the elementary grand pixel R of this gray-scale value maximum
MaxPixel size expand as M * N, be defined as described target macro pixel R, wherein x direction pixel M=M
0+ 2=2
m, y direction pixel N=N
0+ 2=2
n
For preventing that target from dropping on grand pixel rim, need to enlarge 1 pixel with around the elementary grand pixel, guaranteed the maximum coverage rate of object pixel, improved bearing accuracy.
Step 3 is obtained the x direction barycenter initial value C of described target macro pixel R
x(1), its expression formula is:
Wherein, I (k) is the gray-scale value of k pixel of x direction among this target macro pixel R;
Y direction barycenter initial value C
y(1) and described x direction barycenter initial value C
x(1) acquisition methods unanimity;
C
xWhat (1) obtained is the situation of target macro pixel R on the x direction, this formula can be expanded to be the situation of y direction; C
x(1) and C
y(1) is the guestimate to target macro pixel R barycenter, has only carried out obtaining of a target macro pixel R barycenter, has reduced the iteration link, has improved acquisition speed greatly.
Step 4 is determined the x direction barycenter C of described target macro pixel R
x, carry out according to following several steps:
The first step, the initial value i=0 of definition iterations i;
In second step, obtain i threshold value I
Thi, its expression formula is: I
Thi=I
Th-(i+1) (I
a-I
Min)/50;
The 3rd step is with described i threshold value I
ThiTo described target macro pixel R thresholding, obtain thresholding target macro pixel R
i
With less threshold value I
ThiCome thresholding can avoid when reducing ground unrest, reducing signal intensity.
The 4th step is with described thresholding target macro pixel R
iBe divided into 2
i* 2
iIndividual equal-sized secondary grand pixel T;
In the 5th step, obtain the pixel size Δ of secondary grand pixel T described in the i time iteration
i, its expression formula is:
Δ
i=M/2
i;
In the 6th step, obtain thresholding target macro pixel R described in the i time iteration
iAverage barycenter C (i), its expression formula is:
Wherein, I (p) is the gray-scale value of p pixel among j the described secondary grand pixel T;
The 7th step, obtain the i time iteration proportion function r (i), its expression formula is: r (i)=1+1/5
i
R (i) can effectively improve result's the precision and the ability of anti-noise.
The 8th step, obtain the i time iteration weighting function F (i), its expression formula is:
F(i)=r(i)[C(i-1)-C(i-1)]/[C(i)-C(i-1)];
F (i) is used for self-adaptation and regulates the average barycenter of grand pixel and the i-1 time iteration result.
The 9th step, obtain the i time iterative center of mass C (i), its expression formula is:
C(i)=F(i)C(i)+(1-C(i))C(i-1);
In the tenth step, judge that whether i is less than log
2M is if i is less than log
2M, then i adds 1, returns the described i threshold value I that obtains
ThiStep; If i is equal to or greater than log
2M, the x direction barycenter C of then described target macro pixel R
x=C (i);
The span of iterations i is 0≤i≤log
2M is limited in i in this scope, can guarantee to export result's precision, and shorten iteration cycle, reduces calculated amount.
To reducing step by step of threshold value, can guarantee that signal is fully used.
Y direction barycenter C
yWith described x direction barycenter C
xThe acquisition methods unanimity;
C
yWith C
xBe through iteration repeatedly, the result that obtains after regulating of self-adaptation repeatedly, the bearing accuracy height, it is more accurate to locate.
Determine x direction position error signal ε
x, carry out according to following several steps:
The first step is obtained described ideal image S with traditional centroid algorithm
0X direction barycenter C
X0
In second step, obtain described x direction position error signal ε
x, its expression formula is: ε
x=C
x-C
X0
Y direction position error signal ε
yWith described x direction position error signal ε
xThe acquisition methods unanimity;
Step 6 is according to described x direction position error signal ε
xWith y direction position error signal ε
yAdjust described photoelectronic tracking device, realize tracking light source.
ε according to the degree of precision that obtains
yAnd ε
xValue, controller and topworks by photoelectronic tracking device adjust tracing area, thereby can more accurate realization to the tracking of target light source.
In described step 4 the 8th goes on foot, when i=0, the initial value F (0)=0.5 of described the i time iteration weighting function F (i), this value helps improving precision, reduces calculated amount.
Described photoelectronic tracking device is made up of first computer PC1, quick titling mirror FSM, semiconductor laser LD, optical antenna, electro-optical imaging sensors CCD, digital signal processor DSP and second computer PC2;
The control signal output ends of wherein said first computer PC1 connects the control end of described quick titling mirror FSM, described semiconductor laser LD generates the collimated laser beam image projection on this quick titling mirror FSM, this quick titling mirror FSM reflexes to described optical antenna with laser beam image, the optical signalling output terminal of this optical antenna connects the optical signalling input end of described electro-optical imaging sensors CCD, the data output end of this electro-optical imaging sensors CCD connects the data input pin of described digital signal processor DSP, and the data output end of this digital signal processor DSP connects the data input pin of described second computer PC2.
First computer PC1 produces disturbing signal, and quick titling mirror FSM is applied sinusoidal signal on the x direction, and the rotational angle of control quick titling mirror FSM makes quick titling mirror FSM can receive the laser beam image of semiconductor laser LD projection more accurately; Laser beam image is after quick titling mirror FSM reflection, through long Distance Transmission, received by optical antenna, this optical antenna is imaged onto laser beam image on the described electro-optical imaging sensors CCD, electro-optical imaging sensors CCD exports to digital signal processor DSP with image information, this digital signal processor DSP is handled the view data that receives with macro-pixel iterative centroid method, and the result is exported to second computer PC2 demonstration.
Remarkable result of the present invention is: the iteration link is few, and calculated amount is little, and locating speed is fast, and noise resisting ability is strong, object pixel coverage rate height, and the bearing accuracy height, error is little, is applicable to the hi-Fix of the asymmetric hot spot image of low signal-to-noise ratio.
Description of drawings
Fig. 1 is the photoelectronic tracking device structural drawing;
Fig. 2 is a main flow chart of the present invention;
Fig. 3 is for determining the process flow diagram of target macro pixel;
Fig. 4 is for determining the process flow diagram of target macro pixel barycenter.
Embodiment
Below in conjunction with the drawings and specific embodiments the present invention is described in further detail.
As shown in Figure 1, photoelectric tracking macro-pixel iterative centroid method provided by the invention is applied in the photoelectronic tracking device, and this photoelectronic tracking device is made up of first computer PC1, quick titling mirror FSM, semiconductor laser LD, optical antenna 1, electro-optical imaging sensors CCD, digital signal processor DSP and second computer PC2.
Semiconductor laser LD generates the collimation laser beam images, and the wavelength of this laser beam is λ=1550nm.
PC1 produces the sinusoidal perturbation signal on the x direction, be applied on the quick titling mirror FSM, the rotational angle of control quick titling mirror FSM, like this, when laser beam image projected on the quick titling mirror FSM, the quick titling mirror FSM that has rotated proper angle can receive laser beam image more accurately.
Laser beam image reflects through quick titling mirror FSM, behind the transmission 3km, received by optical antenna 1, optical antenna 1 amplifies 20 times with laser beam image and is imaged onto on the electro-optical imaging sensors CCD, the pixel of this image information is 6.5 μ m * 6.5 μ m, and total pixel is 128 * 128pixels.Digital signal processor DSP takes out the every frame image information among the CCD, adopts photoelectric tracking macro-pixel iterative centroid method that view data is handled, and the result is exported to second computer PC2 demonstration.
Shown in Fig. 2,3,4, photoelectric tracking macro-pixel iterative centroid method provided by the invention, carry out according to following steps:
Utilize photoelectronic tracking device to obtain the ideal image S that noiseless does not have background
0With the light spot image S that has noise background, total pixel is 128 * 128pixels.
Obtain initial threshold I
Th=(I
a-I
Min)/40 deduct initial threshold I with the gray-scale value of grandfather tape noise light spot image
Th, obtain the thresholding light spot image S ' behind the thresholding.
Divide described thresholding light spot image S ' step by step, obtain best grand pixel divide value 30 * 30 according to peak signal pixel coverage and less calculated amount principle.
It is 30 * 30 elementary grand pixel groups that described thresholding light spot image S ' is divided into pixel size, and the gray-scale value of each elementary grand pixel in the more elementary grand pixel groups obtains the elementary grand pixel R of gray-scale value maximum
Max, with R
MaxEnlarge 1 pixel, i.e. R all around
MaxPixel size be 32 * 32.
According to formula
Obtain the x direction barycenter initial value C of described target macro pixel R
x(1), y direction barycenter initial value C
y(1) and C
xThe acquisition methods unanimity of (1).
Below be the x direction barycenter C that determines described target macro pixel R
xStep:
The initial value i=0 of definition iterations i.
Obtain the 0th threshold value I
Th0=I
Th-(0+1) (I
a-I
Min)/50 deduct I with the gray-scale value of target macro pixel R
Th0, obtain thresholding target macro pixel R
0
With described thresholding target macro pixel R
0Be divided into 2
0* 2
0Individual equal-sized secondary grand pixel T;
Obtain the pixel size Δ of secondary grand pixel T described in the 0th iteration
0, thresholding target macro pixel R
0Average barycenter C (0), proportion function r (0), weighting function F (0), according to formula
C (i)=F (i) C (i)+(1-C (i)) C (i-1) obtains the 0th iterative center of mass C (0).
I adds 1 then, returns and obtains the 1st threshold value I
Th1=I
Th-(1+1) (I
a-I
Min)/50 obtain the 1st iterative center of mass C (1) set by step, by that analogy, are equal to or greater than log up to i
232, the x direction barycenter C of the grand pixel R of export target
x=C (5); Y direction barycenter C
yWith C
xThe acquisition methods unanimity.
Below be to determine x direction position error signal ε
xStep: obtain ideal image S with traditional centroid algorithm
0X direction barycenter C
X0, obtain described x direction position error signal ε
x=C
x-C
X0Y direction position error signal ε
yWith ε
xThe acquisition methods unanimity.
At last according to x direction position error signal ε
xWith y direction position error signal ε
yAdjust photoelectronic tracking device, realize tracking light source.
Its working condition is as follows: in the photoelectronic tracking device, first computer PC1 control quick titling mirror FSM rotates and receives the laser beam image that semiconductor laser LD generates, laser beam image reflexes to optical antenna through quick titling mirror FSM, and imaging on electro-optical imaging sensors CCD, view data is admitted in the digital signal processor DSP, adopt photoelectric tracking macro-pixel iterative centroid method that view data is handled, and the result is exported to second computer PC2 demonstration.At first obtain light spot image and ideal image, determine the barycenter initial value of target macro pixel and target macro pixel, finish guestimate barycenter; Through the grand pixel of iterative target repeatedly, accurately obtain out the barycenter of target macro pixel, and obtain position error signal according to the barycenter of ideal image and the barycenter of target macro pixel; Adjust described photoelectronic tracking device according to position error signal, realize tracking light source.
Claims (3)
1, a kind of photoelectric tracking macro-pixel iterative centroid method is characterized in that, carries out according to following steps:
Step 1 utilizes photoelectronic tracking device to obtain the ideal image S of light spot image S and noiseless background
0
Step 2 is determined the target macro pixel R of light spot image S, carries out according to following several steps:
The first step is determined initial threshold I
Th, its expression formula is: I
Th=(I
a-I
Min)/40, wherein, I
aBe the average gray value of described light spot image S, I
MinIt is the minimum gradation value of this light spot image S;
Second step is with described initial threshold I
ThTo described light spot image S thresholding, obtain thresholding light spot image S ';
The 3rd step, divide described thresholding light spot image S ' step by step, obtain best grand pixel divide value M according to peak signal pixel coverage and less calculated amount principle
0* N
0, wherein said M
0Be the best grand pixel divide value of x direction, satisfy M
0=2
m-2, m is the positive integer greater than 1; Described N
0Be the best grand pixel divide value of y direction, satisfy N
0=2
n-2, n is the positive integer greater than 1;
The 4th step is according to the grand pixel divide value of described the best M
0* N
0Repartition described thresholding light spot image S ', obtain elementary grand pixel groups;
The 5th step, the gray-scale value of each elementary grand pixel in the more described elementary grand pixel groups, the elementary grand pixel R of acquisition gray-scale value maximum
Max
The 6th step is with the elementary grand pixel R of this gray-scale value maximum
MaxPixel size expand as M * N, be defined as described target macro pixel R, wherein x direction pixel M=M
0+ 2=2
m, y direction pixel N=N
0+ 2=2
n
Step 3 is obtained the x direction barycenter initial value C of described target macro pixel R
x(1), its expression formula is:
Wherein, I (k) is the gray-scale value of k pixel of x direction among this target macro pixel R;
Y direction barycenter initial value C
y(1) and described x direction barycenter initial value C
x(1) acquisition methods unanimity; Step 4 is determined the x direction barycenter C of described target macro pixel R
x, carry out according to following several steps:
The first step, the initial value i=0 of definition iterations i;
In second step, obtain i threshold value I
Thi, its expression formula is: I
Thi=I
Th-(i+1) (I
a-I
Min)/50;
The 3rd step is with described i threshold value I
ThiTo described target macro pixel R thresholding, obtain thresholding target macro pixel R
i
The 4th step is with described thresholding target macro pixel R
iBe divided into 2
iIndividual equal-sized secondary grand pixel T;
In the 5th step, obtain the pixel size Δ of secondary grand pixel T described in the i time iteration
i, its expression formula is:
Δ
i=M/2
i;
In the 6th step, obtain thresholding target macro pixel R described in the i time iteration
iAverage barycenter C (i), its expression formula is:
Wherein, I (p) is the gray-scale value of p pixel among j the described secondary grand pixel T;
The 7th step, obtain the i time iteration proportion function r (i), its expression formula is: r (i)=1+1/5
i
The 8th step, obtain the i time iteration weighting function F (i), its expression formula is:
F(i)=r(i)[C(i-1)-C(i-1)]/[C(i)-C(i-1)];
The 9th step, obtain the i time iterative center of mass C (i), its expression formula is:
C(i)=F(i)C(i)+(1-C(i))C(i-1);
In the tenth step, judge that whether i is less than log
2M is if i is less than log
2M, then i adds 1, returns the described i threshold value I that obtains
ThiStep; If i is equal to or greater than log
2M, the x direction barycenter C of then described target macro pixel R
x=C (i);
Y direction barycenter C
yWith described x direction barycenter C
xThe acquisition methods unanimity;
Step 5 is determined x direction position error signal ε
x, carry out according to following several steps:
The first step is obtained described ideal image S with traditional centroid algorithm
0X direction barycenter C
X0
In second step, obtain described x direction position error signal ε
x, its expression formula is: ε
x=C
x-C
X0
Y direction position error signal ε
yWith described x direction position error signal ε
xThe acquisition methods unanimity;
Step 6 is according to described x direction position error signal ε
xWith y direction position error signal ε
yAdjust described photoelectronic tracking device, realize tracking light source.
2, photoelectric tracking macro-pixel iterative centroid method according to claim 1 is characterized in that: in described step 4 the 8th goes on foot, and when i=0, the initial value F (0)=0.5 of described the i time iteration weighting function F (i).
3, photoelectric tracking macro-pixel iterative centroid method according to claim 1, it is characterized in that: described photoelectronic tracking device is by first computer PC1, quick titling mirror FSM, semiconductor laser LD, optical antenna (1), electro-optical imaging sensors CCD, digital signal processor DSP and second computer PC2 form, the control signal output ends of wherein said first computer PC1 connects the control end of described quick titling mirror FSM, described semiconductor laser LD generates the collimated laser beam image projection on this quick titling mirror FSM, this quick titling mirror FSM reflexes to described optical antenna (1) with laser beam image, the optical signalling output terminal of this optical antenna (1) connects the optical signalling input end of described electro-optical imaging sensors CCD, the data output end of this electro-optical imaging sensors CCD connects the data input pin of described digital signal processor DSP, and the data output end of this digital signal processor DSP connects the data input pin of described second computer PC2.
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CN103177237A (en) * | 2011-12-22 | 2013-06-26 | 中国移动通信集团河北有限公司 | Video monitoring method and device based on on-line lasers |
CN107726993A (en) * | 2017-10-30 | 2018-02-23 | 上海理工大学 | Particle depth measuring method based on the grand pixel greatest gradient region of light field image |
CN107726993B (en) * | 2017-10-30 | 2019-07-19 | 上海理工大学 | Particle depth measurement method based on light field image macro pixel greatest gradient region |
CN111699360A (en) * | 2017-11-03 | 2020-09-22 | 威力登激光雷达有限公司 | System and method for multi-layer centroid calculation |
CN111665747A (en) * | 2019-03-06 | 2020-09-15 | 罗伯特·博世有限公司 | Control of physical systems based on inferred states |
CN113074627A (en) * | 2021-03-12 | 2021-07-06 | 中国科学院生物物理研究所 | Imaging method and device of direct electronic detection camera and computer equipment |
CN113074627B (en) * | 2021-03-12 | 2022-06-10 | 中国科学院生物物理研究所 | Imaging method and device of direct electronic detection camera and computer equipment |
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