CN114627033A - High-reflection target enhancement method based on polarization fusion - Google Patents
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Abstract
The invention discloses a high-reflectivity target enhancement method based on polarization fusion, which relates to the technical field of optical image processing and comprises the following steps: the method comprises the steps of imaging a high-contrast target by adopting polarization imaging in advance, analyzing and obtaining polarization images in multiple directions, carrying out multi-scale transformation based on a multi-scale geometric transformation method, obtaining a transformation image, calibrating different fusion strategies for coefficients of different frequency bands to carry out fusion, obtaining a fusion image F, carrying out dynamic range adjustment and enhancement on the fusion image F, and obtaining an enhanced image H with uniform gray value distribution. The method solves the problem of removing reflection of high-reflection targets in the image, recovers the target information in the area covered by the high reflection, improves the detailed information of the target and the integral visual effect of the image, and recovers the target information more naturally and truly.
Description
Technical Field
The invention relates to the technical field of optical image processing, in particular to a high-reflectivity target enhancement method based on polarization fusion.
Background
In visual detection, the surface of a high-reflectivity object (glass, water surface, smooth metal and the like) reflects the sun or other light sources to generate obvious highlight, so that the formed image has obvious flare, and on one hand, the illumination of the image is not uniform, and the visual detection precision is influenced; and on the other hand, target material and texture characteristics are difficult to invert. Therefore, it is necessary to study a high-contrast target image enhancement technique.
The existing highlight removing method mainly adopts an image processing method, firstly detects a highlight area in an image, and then replaces the highlight area with surrounding information. And polarized light imaging has the characteristics of weak strong light and strong weak light, so that the polarized light imaging has inherent technical advantage in the aspect of eliminating high light. The basic principle is that when a light source irradiates a high-reflection target, a p component parallel to an incident interface and an s component perpendicular to the incident interface are generated, and only the s component exists at a certain angle (Brewster angle), so that the p component and the s component can be completely eliminated by rotating a polaroid. However, in practical application, especially in the visual imaging detection of outdoor moving targets, the angle cannot be controlled, the imaging time is short, and the polarizer cannot be rotated in time.
An effective solution to the problems in the related art has not been proposed yet.
Disclosure of Invention
Aiming at the problems in the related art, the invention provides a high-reflectivity target enhancement method based on polarization fusion, so as to overcome the technical problem that the target details are unclear due to a high-reflectivity target in the existing visual imaging process.
The technical scheme of the invention is realized as follows:
a high-inverse target enhancement method based on polarization fusion comprises the following steps:
step S1, imaging a high-contrast target by adopting polarization imaging in advance, analyzing and acquiring polarization images in multiple directions, and acquiring an intensity image I, a polarization degree image P and a polarization angle image A of the target;
step S2, performing multi-scale transformation on the intensity image I, the polarization degree image P and the polarization angle image A based on a multi-scale geometric transformation method to obtain a transformation image, wherein the transformation image comprises the step of fusing different fusion strategies for calibrating coefficients of different frequency bands;
step S3, carrying out multi-scale inverse transformation to obtain a fusion image F;
and step S4, based on the histogram equalization method, performing dynamic range adjustment and enhancement on the fusion image F to obtain an enhanced image H with uniformly distributed gray values.
Wherein the polarization imaging images high contrast targets, comprising: and split-beam polarization imaging and split-focus planar polarization imaging.
Step S101, the beam splitting type polarization imaging comprises the following steps:
the linear polarization images of 0 degree, 60 degree and 120 degree are obtained by pre-analysis, and are respectively expressed as: i (0), I (60) and I (120);
calculating to obtain an intensity image I, a polarization degree image P and a polarization angle image A, wherein the parameters are expressed as:
step S102, the method for the partial-focus plane type polarization imaging comprises the following steps:
the linear polarization images of 0 degree, 45 degree, 90 degree and 135 degree are obtained by pre-analysis, and are respectively expressed as: i (0), I (45), I (90) and I (135);
calculating to obtain an intensity image I, a polarization degree image P and a polarization angle image A, wherein the parameters are expressed as:
the method for fusing the coefficients of different frequency bands by calibrating different fusion strategies comprises the following steps:
step S201, performing N-layer wavelet decomposition on the intensity image I, the polarization degree image P and the polarization angle image A in advance based on the two-dimensional discrete stationary wavelet to obtain a wavelet coefficient AXi,HXi,VXi,DXi；
Wherein X respectively represents an intensity image I, a polarization degree image P and a polarization angle image A, I represents the number of decomposition layers, and 1, 2.. and N are taken;
step S202, calibrating the low-frequency coefficient AI of the N-th layer decompositionN,APN,AANPerforming arithmetic mean strategy fusion, wherein the fused coefficient is AFNExpressed as:
step S203, calibrating the high frequency coefficient DI of the layer 1 decomposition1,DP1,DA1Performing region energy maximum value strategy fusion, wherein the region size is l multiplied by l, and the fused coefficient is DF1Expressed as:
where max is a large value operation, and Power () operation is a region sum operation, expressed as:
step S204, calibrating other frequency band coefficients, which are expressed as:
AX1,HX1,VX1,AX2,HX2,VX2,DX2,…,HXN,VXN,DXN；
step S205, performing fusion according to a local energy weighted average strategy, where the size of the local area is k × k (k < l), XI is a band coefficient corresponding to the intensity image I, XP is a band coefficient corresponding to the polarization degree image P, XA is a band coefficient corresponding to the polarization angle image a, and the fused coefficient is XF and is expressed as:
XF＝WXI*XI+WXP*XP+WXA*XA；
wherein, WXI，WXP，WXAIs a weight, expressed as:
where Power () is the regional energy sum.
The method for acquiring the fusion image F comprises the following steps:
step S301, calibrating all frequency band coefficients of the transformed image, and performing two-dimensional discrete stationary inverse transformation to obtain a fused image F.
Wherein the dynamic range adjustment is enhanced, comprising the steps of;
s401, counting the number ni of pixels of each gray level of the fusion image F, wherein i is more than or equal to 0 and less than L, and L represents all gray levels in the image;
step S402, obtaining the probability of the pixel with the gray level i in the image, and expressing it as:
px(i)＝p(x＝i)＝ni/n；
wherein n is the number of all pixels in the image, px (i) is an image histogram with a pixel value of i, and the image histogram is normalized to [0,1 ]; px is the cumulative distribution function, which is the cumulative normalized histogram of the image, expressed as:
step S403, calculating an enhanced image H, which is expressed as:
wherein, cdfminFor the cumulative distribution function minimum, width and height represent the length and height of the fused image, respectively, and L is the number of gray levels and v is the pixel value of v in the original image
The invention has the beneficial effects that:
1. the invention utilizes the characteristic that the polarization of light has weak strong light, solves the problem of removing reflection of high reflective targets in the image by combining an image fusion method, recovers the target information in the area covered by the high light, and improves the detailed information of the target and the integral visual effect of the image.
2. The invention adopts a multi-scale multi-strategy fusion method, applies different fusion strategies to different frequency bands, and compared with the traditional image processing method of replacing highlight areas, the method of the invention has more natural and real target information recovery.
3. The polarization simultaneous imaging method is utilized to acquire the polarization image containing the high-reflection target in real time, and the image fusion and enhancement algorithm with strong real-time performance is utilized, so that the method can be used for enhancing the outdoor high-reflection moving target.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a schematic diagram of polarization distribution of light reflected and refracted at a medium surface according to a high-contrast target enhancement method based on polarization fusion according to an embodiment of the present invention;
FIG. 2 is a schematic diagram showing the variation of the polarization component with angle of the surface of a glass medium in a high-contrast target enhancement method based on polarization fusion according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a high-inverse target enhancement method based on polarization fusion according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of an image enhancement effect of a high anti-target based on polarization fusion according to the method for enhancing a high anti-target based on polarization fusion of the embodiment of the present invention;
FIG. 5 is a scene diagram of an intensity image obtained by analysis of a polarization fusion-based high-contrast target enhancement method according to an embodiment of the present invention;
FIG. 6 is a scene diagram of a polarization degree image obtained by analysis of a polarization fusion-based high-contrast target enhancement method according to an embodiment of the present invention;
FIG. 7 is a polarization angle image scene diagram obtained by analysis of a polarization fusion-based high-contrast target enhancement method according to an embodiment of the present invention;
FIG. 8 is a fused image scene diagram of a high inverse target enhancement method based on polarization fusion according to an embodiment of the present invention;
fig. 9 is a scene diagram of a histogram equalization enhanced image of a polarization fusion-based high anti-target enhancement method according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments that can be derived by one of ordinary skill in the art from the embodiments given herein are intended to be within the scope of the present invention.
According to an embodiment of the invention, a high-inverse target enhancement method based on polarization fusion is provided.
The invention is based on the principle that the polarization of light has "strong light weakening", and fig. 1 shows a schematic diagram of the reflection and refraction of light at the interface of two different media, and it can be seen from the diagram that the vibration (polarization) of light can be decomposed into two components perpendicular to the incident plane (s component) and parallel to the incident plane (p component), and the reflectance of the s component and the p component is different when the interface is reflected. Taking the example of light incident on a glass medium from air, where the refractive index n1 of air is 1, and assuming that the refractive index n2 of glass is 1.5, then the reflectance curves of s-component and p-component at different incident angles can be obtained according to the fresnel formula, as shown in fig. 2. It can be seen from the reflectance curve that the s component is different from the p component under most incident angles, and particularly when the angle is equal to 56.3 degrees, the reflectance of the p component is 0, and this angle is called brewster angle, and all reflected light is s component light, so that the s component can be completely filtered out by rotating the polarizer, thereby solving the problem of high-reflection target light reflection. However, in practical applications, especially when imaging an outdoor high-reflection moving target (such as a bus), since the incident angle of a light source (such as a solar or night street lamp) changes, the incident angle of the light source cannot be controlled to be brewster angle, and meanwhile, the requirement of real-time imaging of the moving target cannot be met by filtering and reflecting light by rotating a polarizing film, so that the prior art needs to be improved.
As shown in fig. 3-9, the highly inverse target enhancement method based on polarization fusion according to the embodiment of the present invention is based on that when reflection occurs on the glass surface, even if the incident angle of the light source is not at the brewster angle, the reflectance of the s-component and the p-component is different, so that the reflection component is greatly attenuated in the polarization parameter image (e.g., the degree of polarization, the polarization angle). From the image perspective, for a common intensity image, in a part of the image where original details are clear, due to the existence of a high-reflection object, details of an area covered by the high-reflection object are covered, that is, a high-frequency signal is low-frequency, but details of other areas are still rich; for the polarized image, due to the polarization effect, the energy of the high-reflection target is greatly suppressed, and the details of the area covered by the high-reflection target are well recovered. Therefore, in order to fully utilize the complementary advantages of the intensity image and the polarization image, the influence of the high-contrast target on the visual imaging can be effectively reduced by utilizing the polarization fusion method and applying different strategies to signals with different frequencies.
Specifically, the method comprises the following steps:
step S1, polarization direction image decomposition and preprocessing:
in the technical solution, as shown in fig. 4, a real-time polarization imaging camera with a focus-splitting plane is adopted, that is, polarizing plates in different directions are installed on each pixel of each detector. The 4 adjacent pixels are respectively provided with a 90-degree, 45-degree, 135-degree and 0-degree polaroid, according to the arrangement mode, an I (0), an I (45), an I (90) and an I (135) image can be obtained by decomposing an original image, and because four pixels are synthesized into one pixel, interpolation fitting needs to be carried out on the image during decomposition so as to ensure that the resolution of the image is not changed, and the precision requirement can be met by adopting classical bilinear interpolation.
Step S2, performing polarization information analysis:
according to the technical scheme, a stokes vector solving formula is utilized to calculate and obtain an intensity image I, a polarization degree image P and a polarization angle image A, which are expressed as follows:
in particular, as shown in fig. 5-7, fig. 5 shows images taken by a conventional camera, from which it can be seen that there is a highly reflective target, the information of the area covered by which is not masked. Fig. 6 and fig. 7 show the resolved polarization degree image and the polarization angle image, and the information recovery processing of the area covered by the highly reflective target can be clearly seen from the polarization degree image.
Step S3, performing multi-scale transform decomposition:
in the technical scheme, the intensity image I, the polarization degree image P and the polarization angle image A are subjected to multi-scale transformation decomposition by utilizing two-dimensional discrete stationary wavelet transformation, in the embodiment, the number of decomposition layers N is 2, and a wavelet base is obtained by db2, wherein;
wavelet system of intensity image IThe number is as follows: AI1,HI1,VI1,DI1,AI2,HI2,VI2,DI2；
The wavelet coefficients of the polarization degree image P are: AP (Access Point)1,HP1,VP1,DP1,AP2,HP2,VP2,DP2；
The wavelet coefficients of the polarization angle image a are: AA1,HA1,VA1,DA1,AA2,HA2,VA2,DA2；
In step S4, wavelet coefficient fusion is performed.
The technical scheme adopts multi-scale and multi-strategy fusion, namely different fusion strategies are adopted to obtain fused wavelet coefficients for different frequency band coefficients, and the method specifically comprises the following steps:
step S401, for low frequency sub-band AI2,AP2,AA2Obtaining the fused low-frequency coefficient by adopting an arithmetic mean method to make the fused low-frequency coefficient AF2Expressed as:
step S402, for the frequency band AI of the intensity image1,HI1,VI1,HI2,VI2,DI2Frequency band AP of polarization degree image1,HP1,VP1,HP2,VP2,DP2Frequency band AA of polarization angle image1,HA1,VA1,HA2,VA2,DA2And fusing by adopting a region energy weighted average method.
In the technical scheme, the area size is 3 multiplied by 3, and the corresponding frequency band coefficient AF of the fused image is made1,HF1,VF1,HF2,VF2,DF2By AF1For example, the calculation method is as follows:
AF1＝WAI1*AI1+WAP1*AP1+WAA1*AA1；
wherein the content of the first and second substances,
step S403, for the high frequency sub-band DI1,DA1,DP1The region energy maximum strategy is adopted for fusion, in this embodiment, the size of the region is 5 × 5, and the corresponding band coefficient after fusion is DF1Expressed as:
where max is a large value operation, and Power () operation is a region sum operation, expressed as:
in step S5, a multi-scale inverse transform is performed.
In the technical scheme, as shown in fig. 8, a two-dimensional discrete stationary wavelet inverse transformation is adopted to obtain a fusion image F. From the fusion result, the highlight area in the intensity image is greatly eliminated, and the image details are recovered.
In step S6, histogram equalization processing is performed.
According to the technical scheme, the dynamic range of the gray values of the fusion image F is adjusted and enhanced by using a histogram equalization processing method, so that the visual effect of the image is further improved, and as shown in FIG. 9, the image is more reasonable in restoration distribution and better in visual effect.
By means of the technical scheme, the polarization simultaneous imaging technology is utilized to obtain the polarization image of the outdoor high-reflection moving target by utilizing the inherent technical advantage of the polarization of light in the aspect of removing the reflection of the target, a multi-scale multi-strategy fusion method is used, and a histogram equalization algorithm is applied to realize the recovery and enhancement of the information of the high-brightness region covering target, so that the purposes of removing the reflection of the high-reflection target image and enhancing the visual effect of the image are achieved. The method adopted by the invention has reliable principle and simple operation, and has wide application prospect in the aspect of visual polarization imaging detection, particularly outdoor high-reflection moving target imaging detection.
According to the technical scheme, the polarization of light has the basic characteristics of strong light weakening and weak light strengthening, the polarization direction image containing the high-reflection target is obtained in a polarization imaging mode, and the polarization degree image and the polarization angle image are obtained through analysis by utilizing a polarization information analysis formula model. For the intensity image, the gray value of a high-contrast target area is obviously large, the texture and the details of the area are covered, and from the aspect of frequency domain, the image belongs to the high-frequency signal and is gradually low-frequency, and the detail information of the image is still rich in other non-high-contrast areas in the scene and belongs to the high-frequency signal; and because the polarization characteristic of the polarization degree and the polarization angle image is slightly influenced by the light intensity, the texture and the details of the polarization degree and the polarization angle image are rich in a high-reflection target area and belong to high-frequency signals, the intensity image, the polarization degree image and the polarization angle image can be subjected to fusion processing, and the high light effect caused by a high-reflection target is reduced. Decomposing the intensity image, the polarization degree image and the polarization angle image into different frequency bands by using a multi-scale geometric transformation method, fusing coefficients of the different frequency bands by using different strategies to obtain a fused image, and finally adjusting the dynamic range of the fused image by using a histogram equalization method to improve the overall visual effect of the image. The method solves the problem that the highlight effect of a high-reflection target is difficult to remove by using the polarization characteristic of strong light weakening and applying an image fusion method, improves the target details and the image visual effect, and has the characteristics of simple principle, convenient operation, strong adaptability, real-time property and the like.
In summary, with the above technical solution of the present invention, the following effects can be achieved:
1. the invention utilizes the characteristic that the polarization of light has weak strong light, solves the problem of removing reflection of high reflective targets in the image by combining an image fusion method, recovers the target information in the area covered by the high light, and improves the detailed information of the target and the integral visual effect of the image.
2. The invention adopts a multi-scale multi-strategy fusion method, applies different fusion strategies to different frequency bands, and compared with the traditional image processing method of replacing highlight areas, the method of the invention has more natural and real target information recovery.
3. The polarization simultaneous imaging method is utilized to acquire the polarization image containing the high-reflection target in real time, and the image fusion and enhancement algorithm with strong real-time performance is utilized, so that the method can be used for enhancing the outdoor high-reflection moving target.
While the foregoing is directed to the preferred embodiment of the present invention, other and further embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (7)
1. A high-inverse target enhancement method based on polarization fusion is characterized by comprising the following steps:
imaging a high-contrast target by adopting polarization imaging in advance, analyzing and acquiring polarization images in multiple directions, and acquiring an intensity image I, a polarization degree image P and a polarization angle image A of the target;
performing multi-scale transformation on the intensity image I, the polarization degree image P and the polarization angle image A based on a multi-scale geometric transformation method to obtain a transformation image, wherein different fusion strategies are calibrated for coefficients of different frequency bands for fusion;
performing multi-scale inverse transformation to obtain a fusion image F;
and based on a histogram equalization method, performing dynamic range adjustment and enhancement on the fusion image F to obtain an enhanced image H with uniform gray value distribution.
2. The method for enhancing a high inverse target based on polarization fusion according to claim 1, wherein the polarization imaging images the high inverse target, and comprises: and split-beam polarization imaging and split-focus planar polarization imaging.
3. The method for high-inverse target enhancement based on polarization fusion according to claim 2, wherein the beam splitting type polarization imaging comprises the following steps:
the linear polarization images of 0 degree, 60 degree and 120 degree are obtained by pre-analysis, and are respectively expressed as: i (0), I (60) and I (120);
calculating to obtain an intensity image I, a polarization degree image P and a polarization angle image A, wherein the parameters are expressed as:
4. the polarization fusion based high inverse target enhancement method according to claim 2, wherein the in-focus planar polarization imaging comprises the steps of:
the linear polarization images of 0 degree, 45 degree, 90 degree and 135 degree are obtained by pre-analysis, and are respectively expressed as: i (0), I (45), I (90) and I (135);
calculating to obtain an intensity image I, a polarization degree image P and a polarization angle image A, wherein the parameters are expressed as:
5. the method for enhancing high inverse target based on polarization fusion according to claims 3 and 4, wherein the fusion is performed by calibrating different fusion strategies for coefficients of different frequency bands, comprising the following steps:
carrying out N-layer wavelet decomposition on the intensity image I, the polarization degree image P and the polarization angle image A in advance based on two-dimensional discrete stationary wavelets to obtain a wavelet coefficient AXi,HXi，VXi，DXi；
Wherein X respectively represents an intensity image I, a polarization degree image P and a polarization angle image A, I represents the number of decomposition layers, and 1, 2.. and N are taken;
calibrating low-frequency coefficient AI of Nth layer decompositionN，APN，AANPerforming arithmetic mean strategy fusion, wherein the fused coefficient is AFNExpressed as:
high frequency coefficient DI for performing a calibrated layer 1 decomposition1,DP1,DA1Performing region energy maximum value strategy fusion, wherein the region size is l multiplied by l, and the fused coefficient is DF1Expressed as:
where max is a large value operation, and Power () operation is a region sum operation, expressed as:
scaling other band coefficients, expressed as:
AX1,HX1,VX1,AX2,HX2,VX2,DX2,…,HXN,VXN,DXN；
fusing according to a region energy weighted average strategy, wherein the size of a region is k × k (k < l), let XI be a band coefficient corresponding to an intensity image I, XP be a band coefficient corresponding to a polarization degree image P, XA be a band coefficient corresponding to a polarization angle image a, and the fused coefficient is XF and is expressed as:
XF＝WXI*XI+WXP*XP+WXA*XA；
wherein, WXI，WXP，WXAIs a weight, expressed as:
where Power () is the regional energy sum.
6. The method for enhancing a high inverse target based on polarization fusion according to claim 5, wherein the step of obtaining the fusion image F comprises the following steps:
and calibrating all frequency band coefficients of the transformed image, and performing two-dimensional discrete stationary inverse transformation to obtain a fused image F.
7. The polarization fusion based high inverse target enhancement method according to claim 6, wherein the dynamic range adjustment enhancement comprises the following steps;
counting the pixel number ni of each gray level of the fusion image F, wherein i is more than or equal to 0 and less than L, and L represents all gray levels in the image;
the probability of acquiring a pixel with a gray level i in an image is expressed as:
px(i)＝p(x＝i)＝ni/n；
wherein n is the number of all pixels in the image, px (i) is an image histogram with a pixel value of i, and the image histogram is normalized to [0,1 ]; px is the cumulative distribution function, which is the cumulative normalized histogram of the image, expressed as:
an enhanced image H is computed, represented as:
wherein, cdfminFor the cumulative distribution function minimum, width and height respectively representThe length and height of the fused image, while L is the number of gray levels and v is the pixel value of v in the original image.
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| CN117876253A (en) * | 2024-03-13 | 2024-04-12 | 长春理工大学 | Low-illumination color polarization image enhancement method and system |
| CN117876253B (en) * | 2024-03-13 | 2024-05-28 | 长春理工大学 | Low-illumination color polarization image enhancement method and system |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116091361A (en) * | 2023-03-23 | 2023-05-09 | 长春理工大学 | Multi-polarization parameter image fusion method, system and terrain exploration monitor |
| CN117876253A (en) * | 2024-03-13 | 2024-04-12 | 长春理工大学 | Low-illumination color polarization image enhancement method and system |
| CN117876253B (en) * | 2024-03-13 | 2024-05-28 | 长春理工大学 | Low-illumination color polarization image enhancement method and system |
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