CN109118460B - Method and system for synchronously processing light-splitting polarization spectrum information - Google Patents

Method and system for synchronously processing light-splitting polarization spectrum information Download PDF

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CN109118460B
CN109118460B CN201810677743.0A CN201810677743A CN109118460B CN 109118460 B CN109118460 B CN 109118460B CN 201810677743 A CN201810677743 A CN 201810677743A CN 109118460 B CN109118460 B CN 109118460B
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polarization
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light intensity
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CN109118460A (en
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王慧斌
王敏敏
陈哲
沈洁
王建华
徐立中
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Hohai University HHU
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Abstract

The invention discloses a synchronous processing method and a system for light-splitting polarization spectrum information, wherein the system comprises a lower computer and an upper computer, wherein the lower computer is connected with three CMOS (complementary metal oxide semiconductors) through light splitting to obtain three polarization images in different directions under the same main optical axis in the same wave band; the upper computer is connected with the lower computer through a USB port, three polarization images in different directions obtained by the lower computer are stored, the three polarization images are corrected for displacement change by adopting a phase correlation method, the polarization parameters are calculated by adopting a linear tuning method to obtain four polarization parameter images, finally the polarization parameter images and the polarization degree images are fused based on a PCA method to obtain polarization characteristic images, and the polarization characteristic images and the synthesized light intensity images are fused and displayed based on a dual-channel PCNN. The invention can realize effective acquisition of polarization spectrum information and improve imaging quality.

Description

Method and system for synchronously processing light-splitting polarization spectrum information
Technical Field
The invention belongs to the technical field of image acquisition and processing, and particularly relates to a method and a system for synchronously processing light-splitting polarization spectrum information.
Background
The polarization imaging is a process of reconstructing and enhancing a target by using obtained information on the basis of acquiring target polarization information in real time, can provide target information with more dimensions, is a leading-edge technology with great application value, is particularly suitable for detection and identification of stealth, camouflage and false targets, and can improve the target detection and identification capability of photoelectric detection equipment in severe environments such as haze, smoke dust and the like.
Polarization is one of the fundamental properties of light, and any object exhibits polarization characteristics determined by its own characteristics and the basic law of optics during reflection and emission of electromagnetic radiation. Information of a scene in different polarization states is obtained through imaging, targets with polarization-light intensity differences and backgrounds can be effectively distinguished, and therefore detection and identification of weak targets in complex backgrounds are achieved. Therefore, in recent years, polarization imaging detection has received more and more attention in the scientific research of meteorological environment, the development and utilization of oceans, space detection, biomedicine, military application and the like.
There are three main types of polarization imaging detection devices currently in use: (1) time-sharing imaging mode. This approach obtains images of different polarization directions by rotating a polarizer and a wave plate mounted in front of the lens. The device has simple structure and easy realization, but is difficult to realize the polarized imaging of the moving target. (2) The manner of dividing the focal plane. The method adopts an imaging device manufactured by a special process, each pixel on the imaging device corresponds to different polarization directions respectively, and the imaging device is arranged according to a Bayer format similar to RGB distribution in a color image sensor. The mode can realize simultaneous polarization imaging, does not need an additional light splitting device, is easy to realize the miniaturization of an instrument, but has a complex manufacturing process of a focus splitting plane device and does not realize the commercialization. (3) The manner in which the channels are modulated. The method adopts three cameras to form a three-channel synchronous imaging system, respectively collects polarization images in different directions, and aligns pixels of overlapped areas of the polarization images in different directions by an image space registration algorithm. The method can realize real-time imaging, and has low hardware complexity and low cost; however, due to the difference between the distortion parameters of three channels and the shooting angle of view, if the distortion parameters and the shooting angle of view cannot be corrected reasonably, the polarization image has errors, and subsequent processing is affected. (4) Amplitude division. In the mode, incident light is divided into a plurality of paths by a light splitter, and each path of light enters a corresponding detector after passing through polaroids with different polarization directions. The mode realizes the synchronous acquisition of multi-direction polarization information, but the equipment is too large.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the problems in the prior art, the invention provides a method and a system for synchronously processing light-splitting polarization spectrum information.
The technical scheme is as follows: in order to achieve the purpose, the invention adopts the following technical scheme:
a method for synchronously processing light-splitting polarization spectrum information comprises the following steps:
(1) three polarization images of a target in a 0-degree direction, a 45-degree direction and a 90-degree direction, which are simultaneously acquired by three CMOS image sensors, are acquired and stored;
(2) performing displacement change correction on the three polarization images by adopting a phase correlation method, and performing polarization parameter calculation by adopting a linear tuning method to obtain four polarization parameter images;
(3) and fusing the polarization parameter image and the polarization degree image based on a PCA method to obtain a polarization characteristic image, and fusing and displaying the polarization characteristic image and the synthesized light intensity image based on the dual-channel PCNN.
Preferably, the method for calculating the polarization parameter in step (2) is as follows:
Sv＝k1I90°-k2I0°-cvI45°
Sh＝k3I0°-k4I90°-chI135°
Sd＝(k5+k6)*I45°-k6*(I0°+I90°)-cdI90°
Sr＝k7*(I0°+I90°)-(k7+k8)*I45°-crI0°
wherein Sv、Sh、Sd、SrPolarization parameters, k, in the vertical, horizontal, 45 and 135 directions, respectively1,k2……k8Is an interlayer opposition factor, satisfies kj|j＝1,3,5,7K > 1 and 0j|j＝2,4,6,8＜＝1，cv、ch、cd、crFor the outer layer rejection factor, I denotes the polarized light intensity, and the subscript denotes the corresponding polarization direction.
Preferably, the degree of polarization and the resultant light intensity in step (3) are calculated according to the following formula:
degree of polarization
Figure GDA0002530762860000021
Resultant light intensity
Figure GDA0002530762860000022
Preferably, the method for obtaining the polarization characteristic image by fusing the polarization parameter image and the polarization degree image based on the PCA method in the step (3) is as follows: forming a column vector by all element points in the polarization parameter image and the polarization degree image in four directions, and arranging the column vectors into a matrix X; the principal components of matrix X are retained as polarization signature images.
Preferably, the method for fusing the polarization characteristic image and the synthesized light intensity image based on the dual-channel PCNN in the step (3) includes:
(3.1) initializing neural network model parameters, and respectively taking the synthesized light intensity image and the polarization characteristic image as two inputs of a dual-channel PCNN
Figure GDA0002530762860000031
And
Figure GDA0002530762860000032
and according to
Figure GDA0002530762860000033
Respectively obtain the total stimulationFormula III βIAnd βDIs the coupling coefficient; n represents the number of iterations; the superscripts I and D are respectively used for marking a synthesized light intensity image and a polarization characteristic image, and the subscript j represents a pixel point in the image;
Figure GDA0002530762860000034
and
Figure GDA0002530762860000035
is the overall feedback of the neighborhood neurons;
(3.2) updating neural network model parameters based on
Figure GDA0002530762860000036
And
Figure GDA0002530762860000037
generating a pulse output in which
Figure GDA0002530762860000038
And
Figure GDA0002530762860000039
a threshold value of each channel at the current moment;
(3.3) according to
Figure GDA00025307628600000310
Updating the pulse generation times and making the iteration variable n equal to n +1, wherein
Figure GDA00025307628600000311
And
Figure GDA00025307628600000312
generating a total number of pulses for a previous time;
(3.4) if the iteration times are smaller than the maximum iteration times, returning to the step (3.2), otherwise, ending the iteration and turning to the step (3.5);
(3.5) obtaining each ignition matrix after iteration is finished
Figure GDA00025307628600000313
And
Figure GDA00025307628600000314
and fusion output is carried out through the mode of the maximum ignition times of different channels:
Figure GDA00025307628600000315
preferably, the coupling coefficient of the two-channel PCNN in the step (3) is a product of the joint local entropy E and the contrast σ of the image of the corresponding channel; wherein
Figure GDA00025307628600000316
Figure GDA0002530762860000041
H (i, j) represents the gray value at point (i, j), and N × M represents the size of the image.
A synchronous processing system of spectral polarization spectrum information for realizing the synchronous processing method of spectral polarization spectrum information comprises an upper computer and a lower computer; the lower computer comprises a filter plate, a beam splitting prism group, a polarizing plate and a CMOS image sensor and is used for acquiring three polarization images in different polarization directions under the same wave band;
the upper computer comprises an image storage unit, a polarization information processing unit and a fusion display unit;
the image storage unit is used for storing the polarization image collected by the lower computer and the image processed by the polarization information in the upper computer;
the polarization information processing unit is used for correcting the displacement change of the three polarization images by adopting a phase correlation method and calculating polarization parameters by adopting a linear tuning method to obtain four polarization parameter images;
the fusion display unit is used for fusing the polarization parameter image and the polarization degree image based on a PCA method to obtain a polarization characteristic image, and fusing and displaying the polarization characteristic image and the synthesized light intensity image based on a dual-channel PCNN.
Preferably, the lower computer and the upper computer perform data transmission through the USB port.
Preferably, the beam splitting prism group acquires three beams of light in the same wavelength band and the same main optical axis through a beam splitting structure, and obtains polarization images in three different directions through the polarizing plate and the CMOS.
Has the advantages that: compared with the prior art, the invention has the advantages that: the invention can synchronously acquire three polarization images with different polarization directions through the design of the upper computer and the lower computer, and designs the step of synchronously processing the polarization spectrum information. The lower computer designed by the method has a compact structure and a simple process, can image a moving target, obtains images quickly, obtains the largest polarization parameter information amount by performing polarization calculation in a linear tuning mode, and reduces the calculation amount and has more complete information by performing fusion in a grading mode.
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In order that the present disclosure may be more readily and clearly understood, reference is now made to the following detailed description of the present disclosure taken in conjunction with the accompanying drawings, in which:
FIG. 1 is a system framework diagram according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method according to an embodiment of the present invention;
FIG. 3 is a mathematical model diagram of a linear tuning polarization calculation according to an embodiment of the present invention.
Detailed Description
The invention is further described with reference to the accompanying drawings in which:
FIG. 1 is a system framework diagram according to an embodiment of the present invention. As shown in fig. 1, the system for synchronously processing the information of the light-splitting polarization spectrum disclosed in the embodiment of the present invention mainly includes an upper computer and a lower computer, and the upper computer and the lower computer communicate with each other through a USB port. The lower computer comprises a filter plate, a beam splitting prism group, a polarizing plate and a CMOS image sensor and is used for acquiring three polarization pictures in different polarization directions under the same wave band; the upper computer comprises an image storage unit, a polarization information processing unit and a fusion display unit; the image storage unit is used for storing the polarization image acquired by the lower computer and the image processed by the polarization information in the upper computer; the polarization information processing unit is internally provided with algorithms of displacement change and polarization calculation and is used for processing the image collected by the lower computer; and the fusion display is used for performing fusion display on the image subjected to the polarization information processing.
In the system of the embodiment, a black-and-white image sensor OV2710 of OmniVision company is used as an imaging device in the CMOS image sensor, the number of pixels of the sensor is 200 thousands, the optical format is 1/2.7 inch, and the effective resolution is 1920H × 1080V; complex camera functions including a snapshot technology, a line jump acquisition technology for zooming a sensor and a window interception technology of an interested area are combined on a chip, and parameters such as picture size, exposure time, gain and the like can be programmed and modified through two serial buses; the spectral response range is 450-1050nm, the imaging signal-to-noise ratio (39dB) and the dynamic range are respectively improved to 40dB and 69 dB; with a pixel size of 3 μm by 3 μm, a better response capability (2.0V/lux-sec) is possible; the frame rate of Full @30fps enables continuous image capture, and basically meets the detection requirement of a moving target.
The working waveband of the light splitting prism group is 425-1050 nm, and the working waveband of the polaroid is 400-1200 nm. The beam splitting prism group obtains three beams of light under the same main optical axis in the same wave band through a beam splitting structure, and obtains polarization images in three different directions through a polarizing film and a CMOS respectively.
Fig. 2 is a flowchart of processing spectroscopic polarization spectrum information according to an embodiment of the present invention, and as shown in fig. 2, a method for synchronously processing spectroscopic polarization spectrum information according to an embodiment of the present invention mainly includes the following steps:
the method comprises the following steps: three polarization images of a target in the directions of 0 degree, 45 degrees and 90 degrees, which are simultaneously acquired by the three CMOS image sensors, are acquired and stored. The method specifically comprises the following steps:
firstly, establishing connection between an upper computer and a lower computer through a USB;
secondly, after the confirmation, the upper computer can randomly select a CMOS in the lower computer and send control words of imaging parameters, including image resolution, exposure time and electronic gain;
and thirdly, the upper computer sends synchronous acquisition signals to simultaneously expose the three CMOS to obtain polarized images of the target in the directions of 0 degree, 45 degrees and 90 degrees.
And fourthly, the lower computer transmits the three polarized images to the upper computer and stores the three polarized images.
Step two: and performing displacement change correction on the three polarization images by adopting a phase correlation method, and performing polarization parameter calculation by adopting a linear tuning method to obtain four polarization parameter images. The method specifically comprises the following steps:
firstly, on an upper computer, three polarization images are subjected to displacement change correction based on a phase correlation method, namely, one polarization image is taken as a reference, and the other two polarization images are subjected to displacement change, and the method specifically comprises the following steps:
(1) selecting two images f1(x, y) and f2(x, y) with an amount of translation (Δ x, Δ y) between them, and f1(x, y) is a reference image, f2(x, y) is the image to be translated, i.e. f2(x,y)＝f1(x-Δx,y-Δy)；
(2) To f1(x, y) and f2(x, y) are separately fourier transformed: f2(u,v)＝F1(u,v)·exp[-j2π(uΔx+vΔy)]And F1(u,v)；
(3) Normalized power spectrum:
Figure GDA0002530762860000061
wherein F2 *(u, v) is F2(u, v) a conjugate function;
(4) performing inverse fourier transform on the normalized power spectrum: f (x, y) ═ x- Δ x, y- Δ y;
(5) calculating the peak point in the step (4) to obtain the translation parameters (delta x, delta y).
And secondly, carrying out polarization calculation based on a linear tuning mode to obtain 4 polarization parameter images.
FIG. 3 is a mathematical model diagram of a linear tuning polarization calculation according to an embodiment of the present invention. The linearly tuned polarization calculation as shown in fig. 3 is a linear calculation that can be expressed as:
Figure GDA0002530762860000062
in the formula (I), the compound is shown in the specification,
Figure GDA0002530762860000063
Iθis the intensity of polarized light in different polarization directions and satisfies theta1⊥θ2This ensures θ1And theta2Is a polarization sensitive pair; sv,h,d,rRepresenting a polarization sensitive parameter;
Figure GDA0002530762860000064
and
Figure GDA0002530762860000065
is a factor of opposition, and
Figure GDA0002530762860000066
and
Figure GDA0002530762860000067
cv,h,d,rIθrepresenting the total response of the set of neighboring photoreceptor cells to inhibition of the channel, cv,h,d,rBy altering the inhibition factor of the polarization sensitive pair of the adjacent photoreceptor cell group in the channel
Figure GDA0002530762860000068
And cv,h,d,rThe amplitude of the light beam is used for regulating and controlling the action of the polarized light intensity in different directions in the channel. The value of the tuning parameter will directly affect the quality of the obtained polarization parameter, and is calculated in the following way. The tuning factors are divided into interlayer opposition factor and outer layer inhibition factor cv,h,d,rAnd the interlayer opposition factor is further divided into an enhancement factor kj|j＝1,3,5,7And an inhibitor kj|j＝2,4,6,8. Because the effect of each tuning factor in the model is different, the set value range is also different. Let enhancement factor kj|j＝1,3,5,7Has a value range of [1,10 ]]Step size of 0.04, let suppression factor kj|j＝2,4,6,8The value range is [0.1,1 ]]Step size of 0.01, let suppression factor cv,h,d,rThe value range is [0.001,0.05 ]]Step size is 0.0002, then the information entropy of each polarization channel is calculated and compared with the information entropy under the previous tuning factor, if largeThe value of the tuning factor is updated if necessary until the information entropy is a maximum value, at which point the tuning factor is the best solution.
The step of calculating the polarization parameter by adopting a linear tuning method comprises the following steps:
① calculating the vertical polarization parameter Sv，Sv＝k1I90°-k2I0°-cvI45°。
② calculating the horizontal polarization parameter Sh，Sh＝k3I0°-k4I90°-chI135°。
③ calculating polarization parameter S of 45 degd，Sd＝(k5+k6)*I45°-k6*(I0°+I90°)-cdI90°。
④ calculating polarization parameter S of 135 degr，Sr＝k7*(I0°+I90°)-(k7+k8)*I45°-crI0°。
Based on the polarization parameters, the polarization degree image and the synthesized light intensity image are calculated according to the following formula:
degree of polarization
Figure GDA0002530762860000071
Resultant light intensity
Figure GDA0002530762860000072
Step three: and calculating the polarization degree image and the synthesized light intensity image on the upper computer, and fusing and displaying the four polarization parameter images, the polarization degree image and the synthesized light intensity image. The method comprises the following steps:
and (6) fusing the polarization parameter image and the polarization degree image based on a PCA method to obtain a polarization characteristic image.
② calculating joint local entropy
Figure GDA0002530762860000073
In the formula
Figure GDA0002530762860000074
H (i, j) represents the gray value at point (i, j).
③ calculating contrast
Figure GDA0002530762860000075
In the formula (I), the compound is shown in the specification,
Figure GDA0002530762860000076
n × M represents the size of the image, and H (i, j) represents the grayscale value at point (i, j).
And multiplying the local entropy and the contrast to obtain a coupling coefficient beta-E-sigma.
And fifthly, fusing the polarization characteristic image and the synthesized light intensity image based on the dual-channel PCNN, improving the image contrast and displaying.
The polarization characteristic image is obtained by carrying out primary fusion on the polarization parameter image and the polarization degree image by adopting PCA, and the method specifically comprises the following steps:
all element points in the polarization parameter image and the polarization degree image in four directions form a column vector, and the column vectors are arranged into a matrix X, namely
Figure GDA0002530762860000081
R∈Rn×nIs a correlation matrix of X, and R ═ RTObtaining R ═ E [ XX ]T]The eigenvalues and eigenvectors of (a):
Rqi＝λiqi,i＝1,2....n
in the formula qiIs a feature vector, λiFor eigenvalues, ordering the eigenvalues, λ1＞λ2......＞λn，
Let the characteristic value set D ═ lambda1,λ2......,λn]The corresponding feature vector set V ═ q1,q2......,qn]And then RV is VD.
Linear transformation for principal components:
Figure GDA0002530762860000082
order to
Figure GDA0002530762860000083
In the formula ciThe vector C formed is a projection in the X principal direction, and is a principal component, and is obtained: c ═ VTAnd (4) X. Since V is an orthogonal matrix, i.e. VT＝V-1Therefore, it is
Figure GDA0002530762860000084
Retain the first L principal components, i.e.
Figure GDA0002530762860000085
And X' is the polarization characteristic image.
The method for carrying out fusion based on the two-channel PCNN comprises the following specific steps:
(1) initializing each parameter in the neural network model, including coupling coefficient, iteration times, initial neuron feedback, pulse threshold and the like, and respectively taking the synthesized light intensity image and the polarization characteristic image as two inputs of a dual-channel PCNN
Figure GDA0002530762860000091
And
Figure GDA0002530762860000092
and according to
Figure GDA0002530762860000093
Respectively obtain total stimulation, wherein βIAnd βDIs the coupling coefficient; n represents the number of iterations; the superscripts I and D are respectively used for marking a synthesized light intensity image and a polarization characteristic image, and the subscript j represents a pixel point in the image;
Figure GDA0002530762860000094
and
Figure GDA0002530762860000095
is the overall feedback of the neighborhood neurons.
(2) Updating parameters of the neural network model in accordance with
Figure GDA0002530762860000096
And
Figure GDA0002530762860000097
generating a pulse output in which
Figure GDA0002530762860000098
And
Figure GDA0002530762860000099
is the threshold value of each channel at the current moment.
(3) According to
Figure GDA00025307628600000910
And updating the pulse generation times of the pixel point j, and enabling an iteration variable n to be n + 1.
(4) And (5) if the iteration times are less than the maximum iteration times, returning to the step (2), otherwise, ending the iteration and turning to the step (5).
(5) Obtaining the ignition matrix of each point after iteration
Figure GDA00025307628600000911
And
Figure GDA00025307628600000912
and fusion output is carried out through the mode of the maximum ignition times of different channels:
Figure GDA00025307628600000913
it should be understood that the above examples are only for clearly illustrating the present invention and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And such obvious variations or modifications which fall within the spirit of the invention are intended to be covered by the scope of the present invention.

Claims (8)

1. A method for synchronously processing light-splitting polarization spectrum information is characterized by comprising the following steps: the method comprises the following steps:
(1) three polarization images of a target in a 0-degree direction, a 45-degree direction and a 90-degree direction, which are simultaneously acquired by three CMOS image sensors, are acquired and stored;
(2) performing displacement change correction on the three polarization images by adopting a phase correlation method, and performing polarization parameter calculation by adopting a linear tuning method to obtain four polarization parameter images;
(3) fusing a polarization parameter image and a polarization degree image based on a PCA method to obtain a polarization characteristic image, and fusing and displaying the polarization characteristic image and a synthesized light intensity image based on a dual-channel PCNN;
the method for fusing the polarization characteristic image and synthesizing the light intensity image based on the dual-channel PCNN comprises the following steps:
(3.1) initializing neural network model parameters, and respectively taking the synthesized light intensity image and the polarization characteristic image as two inputs of a dual-channel PCNN
Figure FDA0002530762850000011
And
Figure FDA0002530762850000012
and according to
Figure FDA0002530762850000013
Respectively obtain total stimulation, wherein βIAnd βDIs the coupling coefficient; n represents the number of iterations; the superscripts I and D are respectively used for marking a synthesized light intensity image and a polarization characteristic image, and the subscript j represents a pixel point in the image;
Figure FDA0002530762850000014
and
Figure FDA0002530762850000015
is the overall feedback of the neighborhood neurons;
(3.2) updating neural network model parameters based on
Figure FDA0002530762850000016
And
Figure FDA0002530762850000017
generating a pulse output in which
Figure FDA0002530762850000018
And
Figure FDA0002530762850000019
a threshold value of each channel at the current moment;
(3.3) according to
Figure FDA00025307628500000110
Updating the pulse generation times and making the iteration variable n equal to n +1, wherein
Figure FDA00025307628500000111
And
Figure FDA00025307628500000112
generating a total number of pulses for a previous time;
(3.4) if the iteration times are smaller than the maximum iteration times, returning to the step (3.2), otherwise, ending the iteration and turning to the step (3.5);
(3.5) the iteration is ended to obtain
Figure FDA00025307628500000113
And
Figure FDA00025307628500000114
and fusion output is carried out by generating the maximum value of the pulse times through different channels:
Figure FDA00025307628500000115
2. the method for synchronously processing the spectroscopic polarization spectrum information according to claim 1, characterized in that: the method for calculating the polarization parameter in the step (2) comprises the following steps:
Sv＝k1I90°-k2I0°-cvI45°
Sh＝k3I0°-k4I90°-chI135°
Sd＝(k5+k6)*I45°-k6*(I0°+I90°)-cdI90°
Sr＝k7*(I0°+I90°)-(k7+k8)*I45°-crI0°
wherein Sv、Sh、Sd、SrPolarization parameters, k, in the vertical, horizontal, 45 and 135 directions, respectively1,k2……k8Is an interlayer opposition factor, satisfies kj|j＝1,3,5,7K > 1 and 0j|j＝2,4,6,8＜＝1，cv、ch、cd、crFor the outer layer rejection factor, I denotes the polarized light intensity, and the subscript denotes the corresponding polarization direction.
3. The synchronous processing method for the spectroscopic polarization spectrum information according to claim 2, characterized in that: the polarization degree and the synthesized light intensity in the step (3) are calculated according to the following formula:
degree of polarization
Figure FDA0002530762850000021
Resultant light intensity
Figure FDA0002530762850000022
4. The method for synchronously processing the spectroscopic polarization spectrum information according to claim 1, characterized in that: the method for fusing the polarization parameter image and the polarization degree image based on the PCA method in the step (3) to obtain the polarization characteristic image comprises the following steps: forming a column vector by all element points in the polarization parameter image and the polarization degree image in four directions, and arranging the column vectors into a matrix; the principal component of the matrix is retained as the polarization signature image.
5. The method for synchronously processing the spectroscopic polarization spectrum information according to claim 1, characterized in that: the coupling coefficient of the two channels PCNN in the step (3) is the product of the joint local entropy E and the contrast sigma of the image of the corresponding channel; wherein
Figure FDA0002530762850000023
Figure FDA0002530762850000024
H (i, j) represents the gray value at point (i, j), and N × M represents the size of the image.
6. A spectroscopic polarization spectrum information synchronous processing system for implementing the spectroscopic polarization spectrum information synchronous processing method according to any one of claims 1 to 5, characterized in that: comprises an upper computer and a lower computer; the lower computer comprises a filter plate, a beam splitting prism group, a polarizing plate and a CMOS image sensor and is used for acquiring three polarization images in different polarization directions under the same wave band;
the upper computer comprises an image storage unit, a polarization information processing unit and a fusion display unit;
the image storage unit is used for storing the polarization image collected by the lower computer and the image processed by the polarization information in the upper computer;
the polarization information processing unit is used for correcting the displacement change of the three polarization images by adopting a phase correlation method and calculating polarization parameters by adopting a linear tuning method to obtain four polarization parameter images;
the fusion display unit is used for fusing the polarization parameter image and the polarization degree image based on a PCA method to obtain a polarization characteristic image, and fusing and displaying the polarization characteristic image and the synthesized light intensity image based on a dual-channel PCNN.
7. The system for synchronously processing the spectroscopic polarization spectrum information according to claim 6, wherein: and the lower computer and the upper computer carry out data transmission through the USB port.
8. The system for synchronously processing the spectroscopic polarization spectrum information according to claim 6, wherein: the beam splitting prism group obtains three beams of light under the same main optical axis in the same wave band through a beam splitting structure, and obtains polarization images in three different directions through a polaroid and a CMOS respectively.
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