CN116380076A - Underwater positioning method and system based on polarization characteristics and sky image restoration - Google Patents
Underwater positioning method and system based on polarization characteristics and sky image restoration Download PDFInfo
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Abstract
The invention discloses an underwater positioning method and an underwater positioning system based on polarization characteristics and sky image restoration. Firstly, acquiring underwater sky images in a plurality of polarization directions, denoising the images by adopting wiener filtering and combining with a BRDF model, then estimating the underwater transmittance, the underwater background light intensity at infinity and backward scattered light in an underwater physical imaging model by adopting a dark channel priori principle and polarization characteristics, realizing underwater image restoration, designing a polarization perception model to calculate an underwater polarization mode, extracting the position of a solar meridian according to the underwater polarization mode, and calculating underwater azimuth information by combining a solar azimuth angle. According to the invention, the accuracy of polarization information can be improved through denoising and restoration of the polarization image under a complex water environment, so that the underwater vehicle can stably and reliably perform a passive navigation positioning task.
Description
Technical Field
The invention belongs to the field of underwater positioning navigation, and relates to an underwater positioning method and an underwater positioning system based on polarization characteristics and sky image restoration, in particular to an underwater polarization mode obtained by adopting a polarization perception model based on dark channel priori and polarization characteristics restoration after image denoising and azimuth information obtained by utilizing solar meridian position information in the underwater polarization mode.
Background
The navigation system is a key technology for an autonomous underwater vehicle to autonomously complete an underwater detection task. The navigation system plays an important role in research on the aspects of ocean resource detection, target identification, positioning, communication and the like, and has the characteristics of high precision, good stability, good persistence, low risk and the like along with the continuous increase of the navigation range because of the special task requirements of the navigation system. The current underwater navigation system comprises an inertial navigation system, a satellite navigation system, a radio navigation system, an astronomical navigation system, a geomagnetic navigation system and the like. The inertial navigation has the advantages of high update rate, short-term precision and good stability, and the defects of accumulation of positioning errors along with time and longer initial alignment time before each use. Satellite navigation works by radio waves, is vulnerable to attack in war time, and has inferior dynamic characteristics as an inertial navigation system. The astronomical navigation is not interfered by electromagnetic fields, electromagnetic waves are not radiated outwards, the concealment is good, the orientation and positioning accuracy is high, but the astronomical navigation is limited by cloud layers and meteorological conditions, and the astronomical navigation is difficult to be used for application in realistic scenes. In recent years, the polarization navigation technology becomes a research hot spot gradually, only depends on polarization information in the environment, has the advantages of being not easy to be interfered by the outside, small in size, high in integration level, low in cost, free from error accumulation with time and the like, and provides a new thought for underwater navigation and positioning.
Because the polarized light source in the natural underwater environment mainly comes from skylight, the polarization characteristic of the underwater light has close relation with the polarization characteristic of the skylight, and the polarized light source contains position information which can be used for navigation and positioning. Therefore, by researching the distribution mode of the polarized light under water, the bionic polarized navigation sensor has feasibility to be applied to the water.
Disclosure of Invention
The invention aims to: aiming at the problems existing in the prior art, the invention aims to provide the underwater positioning method and the underwater positioning system based on the polarization characteristics and sky image restoration, which can effectively finish the positioning application of the autonomous underwater vehicle only by relying on polarized light information in the environment, have the advantages of being not easy to be interfered by the outside, good in concealment, low in calculation cost, free from accumulation of errors with time and the like, and can solve a plurality of problems existing at present by combining with other navigation modes.
The technical scheme is as follows: in order to achieve the aim of the invention, the invention adopts the following technical scheme:
an underwater positioning method based on polarization characteristics and sky image restoration mainly comprises the following steps:
(1) Acquiring sky images of a plurality of polarization directions under water, denoising the sky polarized images by using wiener filtering and combining with a BRDF model, and improving the quality of the underwater polarized images;
(2) Estimating the transmissivity, the underwater background light intensity at infinity and the back scattered light in the underwater imaging model by taking the underwater physical imaging model as a background and adopting a dark channel priori principle and polarization characteristics, so as to realize the recovery of the underwater polarized image;
(3) For the restored polarized image, acquiring polarization information based on a polarization opposite perception model, and calculating an underwater polarization mode, wherein the polarization opposite perception model adopts a weight factor to regulate and control the information entropy of the underwater polarization mode so as to acquire an optimal underwater polarization mode;
(4) And extracting the solar meridian position in the underwater polarization mode, and solving the azimuth information of the underwater vehicle by combining the solar azimuth angle.
Preferably, in the step (1), denoising the sky polarized image by using wiener filtering in combination with a BRDF model includes: processing blurring and noise of an image by wiener filtering, describing the blurring process of the image by a point diffusion (PSF) function and analyzing texture characteristics and frequency domain properties by a Power Spectral Density (PSD) function to remove image noise and restore detail information of an original image; and estimating the propagation process of light in the underwater environment by using a Bidirectional Reflectance Distribution Function (BRDF) model, calculating the scattering condition of the light in the underwater environment, and correcting the underwater image by using the calculated scattering information in the wiener filtering process so as to eliminate image blurring noise caused by underwater scattering.
Preferably, in the step (2), the transmissivity, the background light intensity under infinity and the back scattered light in the underwater imaging model are estimated by adopting the dark channel prior principle and the polarization characteristic, so as to realize the recovery of the underwater polarized image, and the method comprises the following steps:
(2.1) estimating the transmissivity and the background light intensity under infinity in an underwater imaging physical model according to a dark channel priori principle, carrying out dark channel processing on the image by using a 3x3 window, and searching for a darkest pixel in a local area of a current pixel to obtain a dark channel image; selecting the brightest first 1% of pixel point positions in the dark channel image, and taking the light intensity of the original image corresponding to the average pixel value of the maximum window of the brightest pixel point positions as the light intensity of the underwater background at infinity; and estimating the minimum transmittance in the window where the current pixel is positioned according to the dark channel principle by using the estimated background light intensity under the infinity and the total light intensity of the image, and calculating the global transmittance of the image.
(2.2) estimating the backscattered light of each pixel point based on the polarization information. The light intensity information has a large influence on the polarization degree, in order to restrain the influence of transmitted light on the polarization information, a polarization angle is selected as parameter estimation, the polarization angle with the largest probability of occurrence is selected from a polarization angle diagram, the polarization degree corresponding to the pixel position of the polarization angle is screened out, the maximum value is selected as the polarization degree of back scattered light, and then the back scattered light of an image is solved;
and (2.3) obtaining a restored polarized image by combining the underwater physical imaging model according to the estimated underwater transmissivity, the underwater background light intensity at infinity and the backward scattered light.
Preferably, the formula of underwater polarized image restoration is:
wherein (x, y) represents the image pixel coordinates, L(x, y) represents the restored image, I (x, y) represents the total light intensity of the image to be restored, t (x, y) represents the underwater transmittance, A ∞ Represents the underwater background light at infinity, I s (x, y) represents the scattered light component of the image, and its formula is I s (x，y)＝A ∞ (1-t(x，y))。
Preferably, the calculating the underwater polarization mode based on the polarization opposite perception model in the step (3) includes the following steps:
(3.1) designing a polarization perception model, and respectively acquiring sky images (I) with four polarization directions (0 DEG, 45 DEG, 90 DEG and 135 DEG) 0° ，I 45° ，I 90° ，I 135° ) Polarized light between mutually perpendicular angles forms a group of polarized channels, and weight factors are added in front of each polarized channel for enhancing and inhibiting the polarized channels so as to solve the polarized information of the underwater sky image, namely the underwater polarized mode;
and (3.2) solving the optimal weight factor in a self-adaptive optimization mode to solve the optimal information entropy of the underwater polarization mode diagram, firstly setting an initial weight factor and the information entropy of the underwater polarization mode diagram, then calculating the information entropy according to the current weight factor, then updating the weight factor, if the image information entropy of the current state is larger than the image information entropy of the previous state, updating the weight factor, otherwise, increasing the weight factor in a fixed step length until the weight factor corresponding to the optimal information entropy is selected, and obtaining the underwater polarization mode with the optimal information entropy.
Preferably, the step (4) extracts the position of the solar meridian according to the underwater polarization mode, and performs underwater positioning calculation by combining the solar azimuth angle, and the method comprises the following steps:
(4.1) extracting a solar meridian according to the underwater polarization mode to obtain an included angle between the solar meridian and a body axis;
(4.2) calculating the solar azimuth through solar calendar;
and (4.3) establishing a relation model of the underwater space coordinate system and the solar meridian, and calculating the azimuth information of the underwater carrier according to the extracted solar meridian position and the solar azimuth information.
Based on the same inventive concept, the invention provides an underwater positioning system based on polarization characteristics and sky image restoration, comprising: the polarized image detection processing module is used for acquiring sky images in a plurality of polarization directions under water, denoising the sky polarized images by using wiener filtering and a BRDF model, taking an underwater physical imaging model as a background, estimating the transmissivity, the underwater background light intensity at infinity and the backward scattered light in the underwater imaging model by adopting a dark channel priori principle and polarization characteristics, and realizing the restoration of the underwater polarized images; the polarization information processing module is used for acquiring polarization information from the restored polarized image based on a polarization opposite perception model and calculating an underwater polarization mode, and the polarization opposite perception model adopts a weight factor to regulate and control the information entropy of the underwater polarization mode so as to acquire an optimal underwater polarization mode; and the positioning module is used for extracting the solar meridian in the underwater polarization mode and calculating the azimuth information of the underwater vehicle by combining the solar azimuth angle.
Based on the same inventive concept, the invention provides a computer system, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the computer program realizes the steps of the underwater positioning method based on polarization characteristics and sky image restoration when being loaded to the processor.
The beneficial effects are that: the underwater positioning method based on the polarization characteristics mainly realizes underwater navigation positioning through an underwater polarization mode. Firstly, detecting sky polarized light by adopting an imaging type polarization sensor, denoising an image by using wiener filtering and combining with a BRDF model to improve image details, then estimating underwater transmissivity, infinity underwater background light and backward scattered light parameters in the model by adopting a dark channel priori principle and polarization characteristics based on an underwater physical imaging model to obtain an image restoration result after scattering removal, then providing a polarization perception model to calculate to obtain an underwater polarization mode, optimizing according to a weight factor to obtain an underwater polarization mode of optimal information entropy, finally extracting the space position of a solar meridian according to the underwater polarization mode, and determining heading information by combining a solar azimuth angle. Compared with the existing autonomous underwater vehicle navigation mode using satellite, inertia, geomagnetism and terrain matching, the autonomous underwater vehicle navigation method is inspired by the capability of insects such as mantis shrimps and the like to distinguish the azimuth by using polarized light in the environment, accurately predicts sky polarization characteristic distribution under the natural water surface, and performs carrier positioning according to an underwater polarization mode. According to the invention, the underwater polarization mode is optimized, so that the mode obtains the highest information entropy, the solar meridian is more accurately obtained, and the orientation accuracy by utilizing polarized light in a complex underwater environment in cloudy weather can be comprehensively improved.
Drawings
FIG. 1 is a flow chart of a method of an embodiment of the present invention.
Fig. 2 is a schematic view of an underwater space coordinate system.
Fig. 3 is an azimuth resolution schematic.
Fig. 4 is a diagram of an experimental apparatus.
Fig. 5 is a schematic illustration of solar meridian extraction. Wherein (a) row is a polarization angle distribution pattern obtained by detecting polarization information at different times and calculating, (b) row is a polarization degree distribution pattern obtained by detecting polarization information at different times and calculating, (c) row is a spatial position feature point diagram extracted by threshold values at different times, and (d) row is a solar meridian diagram extracted at different times.
Fig. 6 is a comparison of errors.
Detailed Description
For clarity and to highlight the objects and advantages of the invention, the invention will be further described with reference to the drawings in the examples of the invention.
As shown in fig. 1, the implementation process of the underwater positioning method based on polarization characteristics and sky image restoration disclosed in the embodiment of the invention mainly comprises the following steps:
step one: and denoising and recovering the underwater sky image. Firstly, sky images in a plurality of polarization directions under water are acquired, the sky polarized images are denoised by combining wiener filtering with a BRDF model, then, the underwater physical imaging model is used as a background, the prior principle of a dark channel and the polarization characteristics are adopted to estimate the transmissivity, the underwater background light intensity at infinity and the backward scattered light in the model, and finally, the underwater polarized image restoration is realized.
An underwater polarized light acquisition system is built to acquire an original sky image in four underwater polarization directions, and the quality of the original polarized image is improved through a denoising and restoration algorithm. In this embodiment, denoising the sky polarized image by using wiener filtering in combination with a BRDF model includes: processing blurring and noise of an image by wiener filtering, describing the blurring process of the image by a point diffusion (PSF) function and analyzing texture characteristics and frequency domain properties by a Power Spectral Density (PSD) function to remove image noise and restore detail information of an original image; estimating the propagation process of light in an underwater environment by using a Bidirectional Reflectance Distribution Function (BRDF) model, calculating the scattering condition of the light in the underwater environment, and correcting an underwater image in a wiener filtering process by using the calculated scattering information to eliminate image blurring noise caused by underwater scattering, wherein the image denoising process is specifically as follows:
collecting sky images with different polarization directions, i.e. I 0° ，I 45° ，I 90° I 135° In the image acquisition process, due to image degradation caused by factors such as shooting or environment, each polarized image is denoised according to a wiener filtering mode, and a degraded image model is as follows:
g(x，y)＝h(x，y)*f(x，y)+n(x，y)
where g (x, y) is a noisy degraded image, f (x, y) is a restored image, n (x, y) is an additive noise model, h (x, y) represents a system function (degradation function) integrating degradation factors, if both the degradation function and noise are considered, a general inverse filtering effect becomes very poor due to the presence of noise, wiener filtering can be performed on the basis of estimating the frequency response of the image to reduce the influence of noise and improve the image quality, and its expression in the frequency domain is:
wherein G (u, v) is a degraded image, F (u, v) is a restored image, |H (u, v)| 2 Power Spectral Density (PSD) representing an image degradation function H (u, v), which refers to the energy distribution in the frequency domain, |H (u, v) | 2 ＝H * (u，v)H(u，v)，H * (u, v) is the complex conjugate of H (u, v), H (u, v) is the image degradation function, and can be calculated by the Point Spread Function (PSF), wherein the PSF describes the distribution condition of an ideal point light source on an imaging plane after passing through an optical system, and the spatial expression is as follows:
where a is a parameter for measuring the PSF scale, x and y are space coordinates, and H (x, y) is converted into a frequency domain and then becomes H (u, v).
where N (u, v) is the scattering noise, F (u, v) is the undegraded image, N (u, v)/F (u, v) is the noise-to-signal ratio, and since the value of F (u, v) is to be solved, the true noise-to-signal ratio can be obtained by measuring the scattering coefficient. The Bidirectional Reflectance Distribution Function (BRDF) model can describe underwater scattering conditions as follows:
where d is the differential sign, ω i And omega r Solid angles respectively representing the incident direction and the observation direction include
θ and->
Representing the angle of incidence and azimuth of a beam of light, L r (ω r ) Indicating the direction of observation ω r Intensity of radiation at L i (ω i ) Indicating the direction of incidence omega i Intensity of radiation f r (ω i ，ω r ) Indicating the direction of light in the viewing direction omega r And the incident direction omega i The ratio of the light intensity on the surface is solved to obtain a scattering coefficient 1-f r (ω i ，ω r ) As a noise-to-signal ratio.
The image restoration method based on the underwater physical imaging model is based on denoising and degradation of the image, and a restoration result is obtained by inverting the imaging model through estimation of parameters. Specifically, the transmissivity and the underwater background light intensity at infinity in the underwater imaging physical model are estimated according to the dark channel prior principle, the backward scattered light of each pixel point is estimated based on polarization information, and a restored polarized image is obtained by combining the underwater physical imaging model according to the estimated underwater transmissivity, the underwater background light intensity at infinity and the backward scattered light.
In this embodiment, the sky image I is obtained according to the four polarization directions after denoising 0° ，I 45° ，I 90° ，I 135° And performing restoration processing on the obtained product. The total light intensity of an image is typically composed of transmitted light and backscattered light, expressed as:
I(x，y)＝I t (x，y)+I s (x，y)
wherein (x, y) represents the pixel coordinates of the image, I (x, y) is the total light intensity of the image, I s (x, y) is back-scattered light, I t (x, y) is light transmitted by the underwater target, and the expression is:
I t (x，y)＝L(x，y)t(x，y)
t(x，y)＝e -βz
wherein L (x, y) is an image to be restored, t (x, y) is the transmittance under water, z represents the distance between the optical imaging system and the target, beta is the attenuation coefficient of light, and the attenuation function of the absorption and scattering effects of the water body on the light is represented.
I s (x, y) is back-scattered lightIndicating that part of the light enters the camera after passing through the scattering particles, resulting in a reduction in imaging quality, the expression is:
I s (x，y)＝A ∞ (1-t(x，y))
in which A ∞ And represents the underwater background light intensity value at infinity, and t (x, y) is the underwater transmittance. The total expression of the underwater physical imaging model is as follows:
I(x，y)＝L(x，y)t(x，y)+A ∞ (1-t(x，y))
namely:
from the above equation, it can be seen that by solving for t (x, y) and A ∞ The parameters can restore the original image L (x, y). According to I t (x, y) and I s T (x, y) common to (x, y) can be given by:
the underwater restoration image L (x, y) is obtainable from the above:
as can be seen from the above, A is obtained ∞ And I s (x, y) a restored image L (x, y) can be obtained.
Specifically, the background light intensity A of the underwater infinity is estimated according to the dark channel prior principle ∞ And transmittance t (x, y). The dark channel expression is:
wherein J C (x, y) is each channel of the color image, Ω (x, y) is represented as a pixel (x, y) -centered window, and a window of size 3*3 is selectedSearching for the darkest pixel in the local area of the current pixel to obtain a dark channel image J dark (x, y), then selecting the pixel point position with 1% high brightness in the dark channel, selecting the maximum value of the average light intensity of 3*3 window of the pixel as the light intensity A of the underwater background at infinity ∞ I.e.
In the middle of
High pixel value for the first 1% of the dark channel of the image, < >>
Representing the search for the maximum average pixel value of the (x, y) centered 3*3 window,/for>
Representing the light intensity value corresponding to the window where the highest pixel is selected, namely the light intensity A of the underwater background at infinity ∞ 。
According to the light intensity A of the underwater background at infinity ∞ The transmittance t (x, y) can be further solved. According to the total expression of the underwater physical imaging model, the method is converted into:
where t (x, y) is regarded as a constant
And obtaining the minimum value of the two sides twice:
according to the dark primary prior principle, no scattering image is formedAt least one pixel is present in the sky area and has a value of approximately 0, i.e. J dark (x, y) →0, can be obtained
Transmittance +.>
The method comprises the following steps:
in order to obtain a more natural restored image, a correction factor omega with a value of 0.95 is introduced, and the correction formula is as follows:
wherein ω is a correction factor, A ∞ Is the background light intensity under the water at infinity, and I (x, y) is the total light intensity of the image.
Determination of backscattered light I s (x, y). In order to restrain the influence of transmitted light on polarization information, a polarization angle is selected as parameter estimation, a polarization angle with the largest probability of occurrence is selected from a polarization angle diagram, the polarization degree corresponding to the pixel position of the polarization angle is screened out, the maximum value is selected as the polarization degree of back scattered light, and then the back scattered light of an image is solved, and the specific steps are as follows:
(1) calculating a polarization angle image and a polarization degree image through Stokes vector parameters;
from sky image I 0° (x，y)，I 45° (x，y)，I 90° (x，y)，I 135° (x, y) calculating corresponding Stokes vector parameters, namely:
wherein I represents the total light intensity of polarized light, Q represents the light intensity difference between the horizontal polarized component and the vertical polarized component, U represents the light intensity difference between the polarized component in the 45 ° direction and the polarized component in the 135 ° direction, V represents the light intensity difference between the right-handed polarized component and the left-handed polarized component of light, and the polarization degree DOP and polarization angle AOP distribution map is calculated from Stokes vector parameters.
(2) Carrying out distribution statistics on a polarization angle diagram of the sky area, and selecting a polarization angle ψ with the largest occurrence probability s ；
(3) Screening out the polarization angle ψ s The maximum polarization value is selected as the polarization degree P of the back scattered light s 。
According to polarized light imaging theory, the image can be decomposed into a pair of mutually orthogonal polarized images, the light intensity value of the image transmitted by polarized light is I/2, the transmitted light intensity is I (1-p)/2, the polarized image consists of the transmitted light and a polarized part of the light intensity, and the polarized part of the polarized image acquired in the 0-degree direction has the light intensity I according to Malus' law SP (x, y) is:
wherein I (0 °) represents the light intensity in the polarization direction of 0 °, p is the degree of polarization, and I is the total light intensity. Psi s Is the polarization angle with the highest occurrence probability. According to the definition of the polarization degree, namely the ratio of the light intensity of the polarized part to the total light intensity, the scattered light intensity I of each pixel can be obtained s The method comprises the following steps:
a according to the solution ∞ And t (x, y) or A ∞ And I s (x, y) obtaining restored images based on the underwater physical imaging model as follows:
thus, the denoising and restoration processing of the underwater image is completed.
Step two: and designing a polarization opposite perception model for the restored polarized image to acquire polarization information, and calculating an underwater polarization mode. Calculating an underwater polarization mode according to the polarization opposite perception model, wherein the method specifically comprises the following steps of:
(1) From the processed polarized image I 0° ，I 45° ，I 90° ，I 135° The polarization parameters of each channel are calculated, and the expression is as follows:
S 1 ＝k 1 I 90° -k 2 I 0° -c 1 I 45°
S 2 ＝k 3 I 0° -k 4 I 90° -c 2 I 135°
S 3 ＝k 5 I 45° -k 6 I 135° -c 3 I 90°
S 4 ＝k 7 I 135° -k 8 I 45° -C 4 I 0°
wherein the polarization parameter S represents the difference of polarized light intensity after being enhanced or suppressed between the angles, k represents the enhancement or suppression factor in each polarization channel, and c represents the suppression factor of the polarized light intensity of the adjacent group.
(2) And optimizing the weight factors. The information entropy of the polarization parameter is used as a reference index, and the expression is as follows:
wherein L represents the gray value of the image, p (i) is the ratio of the number of pixels with the gray value of i to the total number of pixels, the larger the information entropy E is, the more the information quantity of the representing image is, and when E reaches the maximum value, the weight factor is the optimal solution. The invention adopts a self-adaptive optimization method to solve the weight factors, and the weight factors in the opposite perception model are mainly divided into: enhancement factor k of interlayer photoreceptor cells i (i=1, 3,5, 7), inhibitor k i (i=2, 4,6, 8) and inhibition factor C of photoreceptor cells of adjacent group i (i=1, 2,3, 4), the weight factor is optimized using an exhaustive search, the main steps of which are as follows:
(2.1) initializing a weight factor. Setting k 1 =1 and the value range is 1-10, k 1 =0.1 and the value range is 0 to 1, c 1 The value range of the initial information entropy of the polarization sensitive parameter image is 0.001-0.05, which is 0.001 =0.001
N 0 Representing an initial state;
and (2.2) calculating the entropy of the polarization sensitive image information. Calculating a current information entropy according to the current weight factor;
(2.3) updating the weight factor. If the entropy of the current state is higher than that of the previous state, i.e
N i And N i-1 And updating the current weight factor when the current state and the previous state are represented, otherwise, increasing the weight factor by a fixed step length until the maximum information entropy value of the polarization sensitive image is found, and simultaneously recording the corresponding optimal weight factor value.
(3) Calculating an underwater polarization mode, namely a polarization degree DOP distribution diagram and a polarization angle AOP distribution diagram according to a polarization perception model, wherein the formula is as follows:
thus, the acquisition of the underwater polarization mode is completed.
Step three: finally, extracting a solar meridian according to the underwater polarization mode, and calculating the included angle between the body axis direction and the geographic north direction by combining the solar azimuth angle
Firstly, extracting a solar meridian according to an underwater polarization mode to obtain an included angle between the solar meridian and a body axis; and then calculating the solar azimuth through solar calendar, finally establishing a relation model of the underwater space coordinate system and the solar meridian, and calculating the azimuth information of the underwater carrier according to the extracted solar meridian position and the solar azimuth information.
Specifically, the method for extracting the solar meridian position in the underwater polarization mode is as follows: preliminarily setting a threshold T α The distribution characteristics of the characteristic points of the solar meridian position meet 90-T α AOP < 90 DEG and-90 DEG AOP < T α -90 ° the solar meridian location feature points are segmented out of the background region by thresholding. The position of the solar meridian, namely the clamping angle of the solar meridian and the body axis, is proposed by adopting a straight line fitting method
Fig. 2 is a view of a space coordinate system of underwater polarization positioning, which describes the process of light entering the observation position of the carrier from the atmosphere, and is converted into a two-dimensional geographical plane coordinate system for more intuitively describing the process of resolving underwater azimuth information, as shown in fig. 3.
θ s ＝arcsin(sinδsinβ+cosδcosβcost)
wherein beta represents the geographical latitude of the observation point, t is the solar time angle, and is calculated from the true solar time, and delta is the solar declination angle.
and establishing a spatial relationship between the underwater spatial coordinate system and the solar meridian, taking the underwater observation position as an origin, establishing a northeast coordinate system, and determining the solar meridian as a reference standard for underwater positioning. According to the calculated solar azimuth angle
The angle between the extracted solar meridian and the body axis is +.>
Thereby calculating the angle between the carrier direction and the geographic north>
Azimuth angle->
The solution formula is:
the calculation of the azimuth angle of the carrier is completed, and the application of underwater positioning by utilizing the polarization characteristics and sky image restoration is completed.
Based on the same inventive concept, the invention provides an underwater positioning system based on polarization characteristics and sky image restoration, which is disclosed by the embodiment of the invention, and comprises: the polarized image detection processing module is used for acquiring sky images in a plurality of polarization directions under water, denoising the sky polarized images by using wiener filtering and a BRDF model, taking an underwater physical imaging model as a background, estimating the transmissivity, the underwater background light intensity at infinity and the backward scattered light in the underwater imaging model by adopting a dark channel priori principle and polarization characteristics, and realizing the restoration of the underwater polarized images; the polarization information processing module is used for acquiring polarization information from the restored polarized image based on a polarization opposite perception model and calculating an underwater polarization mode, and the polarization opposite perception model adopts a weight factor to regulate and control the information entropy of the underwater polarization mode so as to acquire an optimal underwater polarization mode; and the positioning module is used for extracting the solar meridian in the underwater polarization mode and calculating the azimuth information of the underwater vehicle by combining the solar azimuth angle.
Based on the same inventive concept, the invention provides a computer system disclosed in an embodiment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the computer program realizes the steps of the underwater positioning method based on polarization characteristics and sky image restoration when being loaded into the processor.
In order to verify the effect of the underwater positioning method and the system using the polarization characteristics and sky image restoration, an experimental device is built for experiment. During experiments, a camera is used for shooting zenith, and the axis direction of the camera is consistent with the axis direction of the body. The experimental setup is shown in fig. 4.
In order to verify the effectiveness of the invention, the underwater polarization positioning performance at different times was experimentally tested. The experimental result takes the course angle error as an evaluation standard. The experimental result is shown in fig. 5, wherein (a) is a sky polarization angle distribution diagram; (b) is a sky polarization profile; (c) a fusion map of location feature points; (d) solar meridian extraction results.
The experiment is carried out from eight in the morning to five in the afternoon, the actual azimuth is kept to be in the forward south direction, the test is carried out every one hour, and the experiment records the time of each hour and the sun altitude angle and the sun azimuth angle, the underwater polarization mode information entropy, the azimuth angle and the azimuth error corresponding to the longitude and latitude of the test place. E is shown in the following table 1 And E is 2 Respectively Stokes vector parameters, and information entropy and theta of the underwater polarization mode diagram obtained by the invention 1 And theta 2 Respectively Stokes vector parameters, azimuth information calculated under the underwater polarization mode acquired by the invention, delta 1 And delta 2 Respectively Stokes vector parameters and azimuth errors under the underwater polarization mode obtained by the method.
Table 1 table of experimental data
According to the analysis of the data results in the table 1 and the table 6, sky is easily affected by cloud layers, water mist and the like, so that polarization azimuth information is blurred, in sky polarization mode diagrams obtained through testing under the weather conditions, solar meridian areas are more blurred, the influence degree of noise on the traditional method is high, and the method and the system provided by the invention have better robustness and stability and have important significance on underwater polarization positioning.
Claims (10)
1. An underwater positioning method based on polarization characteristics and sky image restoration is characterized by comprising the following steps:
(1) Acquiring sky images of a plurality of polarization directions under water, and denoising the sky polarized images by using wiener filtering and combining with a BRDF model;
(2) Estimating the transmissivity, the underwater background light intensity at infinity and the back scattered light in the underwater imaging model by taking the underwater physical imaging model as a background and adopting a dark channel priori principle and polarization characteristics, so as to realize the recovery of the underwater polarized image;
(3) For the restored polarized image, acquiring polarization information based on a polarization opposite perception model, and calculating an underwater polarization mode, wherein the polarization opposite perception model adopts a weight factor to regulate and control the information entropy of the underwater polarization mode so as to acquire an optimal underwater polarization mode;
(4) And extracting the solar meridian position in the underwater polarization mode, and solving the azimuth information of the underwater vehicle by combining the solar azimuth angle.
2. The underwater positioning method based on polarization characteristics and sky image restoration according to claim 1, wherein the denoising processing of the sky polarization image in the step (1) by combining wiener filtering with a BRDF model comprises: processing blurring and noise of an image by wiener filtering, describing the blurring process of the image by a point diffusion (PSF) function and analyzing texture characteristics and frequency domain properties by a Power Spectral Density (PSD) function to remove image noise and restore detail information of an original image; and estimating the propagation process of light in the underwater environment by using a Bidirectional Reflectance Distribution Function (BRDF) model, calculating the scattering condition of the light in the underwater environment, and correcting the underwater image by using the calculated scattering information in the wiener filtering process so as to eliminate image blurring noise caused by underwater scattering.
3. The underwater positioning method based on polarization characteristics and sky image restoration according to claim 1, wherein the step (2) adopts a dark channel prior principle and polarization characteristics to estimate the transmittance, the underwater background light intensity at infinity and the backward scattered light in an underwater imaging model, so as to realize underwater polarization image restoration, and the method comprises the following steps:
(2.1) estimating the transmissivity and the background light intensity under infinity in an underwater imaging physical model according to a dark channel priori principle, carrying out dark channel processing on the image by using a 3x3 window, and searching for a darkest pixel in a local area of a current pixel to obtain a dark channel image; selecting the brightest pixel position with set proportion from the dark channel image, and taking the light intensity of the original image corresponding to the maximum value of the window average pixel values as the light intensity of the underwater background at infinity; estimating the minimum transmittance of a window in which a pixel is positioned according to a dark channel principle by using the estimated background light intensity under the infinity and the total light intensity of the image to obtain the global transmittance of the image;
(2.2) estimating the backward scattered light of each pixel point based on the polarization information, selecting a polarization angle with the largest probability of occurrence from the polarization angle graph, screening out the polarization degree corresponding to the pixel position of the polarization angle, selecting the maximum value as the polarization degree of the backward scattered light, and further solving the backward scattered light of the image;
and (2.3) obtaining a restored polarized image by combining the underwater physical imaging model according to the estimated underwater transmissivity, the underwater background light intensity at infinity and the backward scattered light.
4. The underwater positioning method based on polarization characteristics and sky image restoration according to claim 1, wherein the formula of underwater polarization image restoration is:
Wherein (x, y) represents the pixel coordinates of the image, L (x, y) represents the restored image, and I (x, y) represents the total light of the image to be restoredStrong, t (x, y) represents the transmittance under water, A ∞ Represents the light intensity of the underwater background at infinity, I s (x, y) represents the scattered light component of the image, and has I s (x，y)＝A ∞ (1-t(x，y))。
5. The underwater positioning method based on polarization characteristics and sky image restoration according to claim 1, wherein the step (3) of calculating the underwater polarization mode based on the polarization opposite perception model comprises the steps of:
(3.1) designing a polarization perception model, and respectively acquiring sky images (I) with four polarization directions (0 DEG, 45 DEG, 90 DEG and 135 DEG) 0° ，I 45° ，I 90° ，I 135° ) Polarized light between mutually perpendicular angles forms a group of polarized channels, and weight factors are added in front of each polarized channel for enhancing and inhibiting the polarized channels so as to solve the polarized information of the underwater sky image, namely the underwater polarized mode;
and (3.2) solving the optimal weight factor in a self-adaptive optimization mode to solve the optimal information entropy of the underwater polarization mode diagram, firstly setting an initial weight factor and the information entropy of the underwater polarization mode diagram, then calculating the information entropy according to the current weight factor, then updating the weight factor, if the image information entropy of the current state is larger than the image information entropy of the previous state, updating the weight factor, otherwise, increasing the weight factor in a fixed step length until the weight factor corresponding to the optimal information entropy is selected, and obtaining the underwater polarization mode with the optimal information entropy.
6. The underwater positioning method based on polarization characteristics and sky image restoration according to claim 1, wherein the extracting the position of the solar meridian according to the underwater polarization mode in the step (4) and combining the solar azimuth angle to perform the underwater positioning calculation comprises the following steps:
(4.1) extracting a solar meridian according to the underwater polarization mode to obtain an included angle between the solar meridian and a body axis;
(4.2) calculating the solar azimuth through solar calendar;
and (4.3) establishing a relation model of the underwater space coordinate system and the solar meridian, and calculating the azimuth information of the underwater carrier according to the extracted solar meridian position and the solar azimuth information.
7. An underwater positioning system based on polarization characteristics and sky image restoration, comprising:
the polarized image detection processing module is used for acquiring sky images in a plurality of polarization directions under water, denoising the sky polarized images by using wiener filtering and a BRDF model, taking an underwater physical imaging model as a background, estimating the transmissivity, the underwater background light intensity at infinity and the backward scattered light in the underwater imaging model by adopting a dark channel priori principle and polarization characteristics, and realizing the restoration of the underwater polarized images;
the polarization information processing module is used for acquiring polarization information from the restored polarized image based on a polarization opposite perception model and calculating an underwater polarization mode, and the polarization opposite perception model adopts a weight factor to regulate and control the information entropy of the underwater polarization mode so as to acquire an optimal underwater polarization mode;
the positioning module is used for extracting the solar meridian in the underwater polarization mode and calculating the azimuth information of the underwater vehicle by combining the solar azimuth angle.
8. The underwater positioning system based on polarization characteristics and sky image restoration according to claim 7, wherein the method for estimating the transmittance, the background light intensity under infinity and the backscattered light by the polarized image detection processing module comprises the following steps: estimating the transmissivity in the underwater imaging physical model and the underwater background light intensity at infinity according to the dark channel priori principle, carrying out dark channel processing on the image by using a 3x3 window, and searching for the darkest pixel in the local area of the current pixel to obtain a dark channel image; selecting the brightest pixel position with set proportion from the dark channel image, and taking the light intensity of the original image corresponding to the maximum value of the window average pixel values as the light intensity of the underwater background at infinity; estimating the minimum transmittance of a window in which a pixel is positioned according to a dark channel principle by using the estimated background light intensity under the infinity and the total light intensity of the image to obtain the global transmittance of the image; and estimating the back scattered light of each pixel point based on the polarization information, selecting a polarization angle with the largest occurrence probability from the polarization angle graph, screening out the polarization degree corresponding to the pixel position of the polarization angle, selecting the maximum value as the polarization degree of the back scattered light, and further solving the back scattered light of the image.
9. The underwater positioning system based on polarization characteristics and restoration of sky image of claim 7, wherein the formula of restoration of the underwater polarization image is:
Wherein (x, y) represents the pixel coordinates of the image, L (x, y) represents the restored image, I (x, y) represents the total light intensity of the image to be restored, t (x, y) represents the underwater transmittance, A ∞ Represents the light intensity of the underwater background at infinity, I s (x, y) represents the scattered light component of the image, and has I s (x，y)＝A ∞ (1-t(x，y))。
10. A computer system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the computer program when loaded into the processor realizes the steps of a method for underwater localization based on polarization characteristics and restoration of sky images according to any of claims 1-6.
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