CN111076817B - Abnormal target detection method based on optical multi-dimensional information integrated perception system - Google Patents
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Abstract
The invention relates to an abnormal target detection technology, in particular to an abnormal target detection method based on an optical multi-dimensional information integrated sensing system, which solves the problems of inaccurate abnormal target detection and large spectral data redundancy existing in the conventional abnormal target detection method, aims at the traction of optical remote sensing requirements, aims at extracting more attributes of a target and improving the target detection precision, and mainly comprises the following processes: obtaining polarization spectrum data, reconstructing polarization state information, calculating significance, obtaining a significance map, distributing weight, calculating a detection operator and fusing polarization information.
Description
Technical Field
The invention relates to an abnormal target detection technology, in particular to an abnormal target detection method based on an optical multi-dimensional information integrated perception system.
Background
The optical multi-dimensional information integrated sensing system is a novel optical detection technology which integrates imaging, spectrum, polarization and sensing to acquire multi-dimensional information, and can acquire a data hypercube of a detected target simultaneously, wherein the data hypercube contains two-dimensional space information, spectrum information of each dimension in an image and polarization state information of each spectrum section. The spectral image has the characteristics of high spectral resolution, integrated atlas, multiple spectral channels and the like, and can play great advantages in target detection and identification, so the method has higher application value in the fields of marine ecology, environmental monitoring, military and national defense, urban traffic, accurate agriculture and forestry and the like. The abnormal target detection technology is an unsupervised target detection method, and is used for searching sparse pixels of unknown signals in image data. The technology for detecting the abnormal target by the polarized spectrum is an abnormal target detection technology which is characterized in that the polarized information of the target is added on the basis of a spectrum image and the imaging, the spectrum and the polarized information are integrated, and has important strategic significance in the aspects of novel camouflage disclosure (such as a novel spectrum camouflage technology) and improvement of target identification precision.
At present, a common abnormal target detection method mainly comprises abnormal target detection based on a high spatial resolution image and abnormal target detection based on a hyperspectral image. The abnormal target detection based on the high-spatial-resolution image is mainly implemented by calculating a saliency map by using a saliency detection method in computer vision, and the commonly used methods comprise a sparse and low-rank representation-based method, a Fourier transform-based method, a learning-based method and the like. Abnormal target detection based on the high-spatial-resolution image mainly uses high-resolution spatial data for mining, and the amount of data which can be used by an algorithm is small, so that the abnormal target detection is inaccurate. The abnormal target detection based on the hyperspectral image mainly comprises the steps of searching sparse pixels of unknown spectral signals in the hyperspectral image by utilizing the hyperspectral resolution of the hyperspectral image, and searching pixel points which have obvious differences between spectral characteristics and spectral characteristics of surrounding pixels and appear at low probability. The abnormal target detection based on the hyperspectral image can effectively utilize spectral information and improve the detection precision, but the spectral information is greatly influenced by external factors (such as heavy fog, haze and the like) when being acquired, and the spectral data redundancy is high.
Disclosure of Invention
The invention aims to solve the problems of inaccurate abnormal target detection and high spectral data redundancy existing in the conventional abnormal target detection method, and provides an abnormal target detection method based on an optical multi-dimensional information integrated sensing system. Aiming at the traction required by optical remote sensing, the method aims at extracting more attributes of the target and improving the target detection precision.
In order to achieve the purpose, the invention is realized by the following technical scheme:
an abnormal target detection method based on an optical multi-dimensional information integrated perception system comprises the following steps:
acquiring polarization spectrum data;
an optical multi-dimensional information integrated sensing system acquires polarization spectrum information;
secondly, reconstructing polarization state information;
definition IPM(k) For an input multi-dimensional polarization spectrum image, wherein M is the number of wave bands of the image, k is the number of pixel points, and P is {1, 2, 3, 4}, the polarization state information of different angles is respectively represented, and extracted single-spectrum data I are subjected to single-spectrum data IPM(k)＝{IP1(k)，IP2(k)，...，IPM(k) Extracting pixel points in the same polarization direction in the region, and realizing complete reconstruction of spatial information of continuous spectrum segments in different polarization state directions by a neighborhood pixel interpolation method;
step three, calculating significance;
after reconstructing the polarization state information, the significance of the data is calculated, the significance being defined as follows:
wherein, i is any pixel point of the local window, j is the central pixel point of the local window, and x2(pi，pj) Euclidean distance, x, between the position information in the window for i and j1(pi，pj) Is the spectral distance between i and j, and c is the scale parameter;
step four, obtaining a saliency map;
definition sNThe central pixel point j of the local window is the average value s of the significance of all pixel points i of the local windowNThe calculation method of (2);
wherein, N is the number of all pixel points in the window, a is the number of the pixel points with non-zero significance value in the window; traversing the whole image through a sliding window to calculate s of central pixels of each windowNA saliency map s (k), s (k) ═ s, composing an image1，s2，...，sN}；
Step five, calculating the weight;
the weights are calculated as follows:
wherein M represents the wave band number of the image, r represents the spectral curve of the sample pixel, and the sample is assumed to be judged as the background pixel point and obeys the mean value mubCovariance of CbNormal distribution of (1), p (r | H)0) Is the probability that a detected pixel is a background pixel;
normalizing p (r | H) by equation (4)0)：
Where N is the number of pixel points, k is the current pixel point, k is 1, 2k|H0) Is the corresponding weight after each pixel is normalized;
the final weight calculation formula is
Wherein, S (k) is the significance map calculated in the step four;
step six, calculating a detection operator;
anomaly detection operator deltaPThe formula (r) is as follows:
δP(r)＝(r-μP)TCP -1(r-μP) (6)
wherein the mean vector muPSum covariance matrix CPIs defined as formula (7), (8):
wherein r isiSpectral curve, P, representing the ith pixelP(ri|H0) Is represented by riThe weight of (c);
by traversing the polarization direction P ═ {1, 2, 3, 4}, the anomaly detection operator δ for each polarization direction is calculatedP(r)；
Step seven, carrying out polarization information fusion,
the final abnormal target detection operator delta (r) is expressed as follows
Wherein, p is the proportion of each polarization state information;
according to the selected threshold value T, the detection result omega (r) is as follows:
the obtained omega (r) is the detection result, and the pixel point with the value of 1 represents that the abnormal target is detected.
Further, in the first step, the optical multi-dimensional information integrated sensing system acquires polarization spectrum information by using a micro pixilated polarizing film, wherein the pixilated polarizing film is a polarizing film formed by regularly arranging four polarization states, and each polarization state is at a pixel level in physical dimension, and is selected from 0 degree, 45 degrees, 90 degrees and 135 degrees.
Meanwhile, the present invention also provides a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps of the abnormal target detection method based on the optical multi-dimensional information-integrated sensing system.
In addition, the invention also provides a computer device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of the abnormal target detection method based on the optical multi-dimensional information integration perception system.
Compared with the prior art, the invention has the following beneficial effects:
1. compared with the traditional high-spatial-resolution target detection, the method can better utilize spectral information and polarization information and fuse the high-spatial-resolution information with the spectral information and the polarization information, so that the target detection effect is better and the detection accuracy of the abnormal target is improved.
2. The method of the invention breaks through the defect that the assumption of multivariate Gaussian distribution of the traditional RX abnormal point detection algorithm cannot completely and truly describe the actual scene, and obviously improves the detection precision.
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FIG. 1 is a flowchart of an abnormal target detection method of the optical multi-dimensional information integrated sensing system of the present invention;
FIG. 2 is a schematic diagram of polarization state information reconstruction in accordance with the present invention;
FIG. 3a is a schematic diagram of the complete reconstruction of spatial information in the polarization state direction of 0 ° according to the method of the present invention;
FIG. 3b is a schematic diagram of the complete reconstruction of spatial information in the direction of 45 ° polarization according to the method of the present invention;
FIG. 3c is a schematic diagram of the complete reconstruction of spatial information in the 90 ° polarization direction according to the method of the present invention;
FIG. 3d is a schematic diagram of the complete reconstruction of spatial information in the direction of 135 ° polarization state according to the method of the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and specific embodiments.
The invention provides an abnormal target detection method based on an optical multi-dimensional information integrated sensing system, which is used for detecting an abnormal target by using obtained polarization spectrum data and solves the problems that the available information of the traditional abnormal target detection based on high spatial resolution and the abnormal target detection algorithm based on hyperspectrum is insufficient, and the abnormal target detection result is inaccurate.
As shown in fig. 1, the abnormal target detection method based on the optical multi-dimensional information integrated sensing system provided by the present invention mainly includes the following processes: obtaining polarization spectrum data, reconstructing polarization state information, calculating significance, obtaining a significance map, distributing weight, calculating a detection operator and fusing polarization information.
Acquiring polarization spectrum data;
the optical multidimensional information integrated sensing system adopts a micro pixilated polarizing film to obtain polarization information, the pixilated polarizing film is a polarizing film formed by regularly arranging four polarization states, each polarization state is in a pixel level on the physical dimension, the four polarization states can be flexibly selected, and the device selects 0 degree, 45 degrees, 90 degrees and 135 degrees, and the pixel dimension is 7.4 microns;
secondly, reconstructing polarization state information;
definition IPM(k) For an input multi-dimensional polarization spectrum image, wherein M is the number of bands, k is the number of pixel points, and P ═ 1, 2, 3, 4, which respectively represent polarization state information of 0 °, 45 °, 90 °, 135 °, for the extracted single-band data IPM(k)＝{IP1(k)，IP2(k)，...，IPM(k) Extracting pixel points in the same polarization direction in the region, and realizing complete reconstruction of spatial information in different polarization state directions of continuous spectrum segments by a neighborhood pixel interpolation method, as shown in fig. 2;
step three, calculating significance;
after reconstructing the polarization state information, the significance of the data, I, is first calculatedPM(k) For the input multi-dimensional polarization spectrum image, M is the number of wave bands, k is the number of pixel points, P ═ 1, 2, 3, 4}, IPM(k)＝{IP1(k)，IP2(k)，...，IPM(k)}；
Significance is defined as follows:
wherein, i is any pixel point of the local window, and j is a central pixel point of the local window;
x2(pi，pj) The Euclidean distance between the position information of i and j in the window;
x1(pi，pj) Is the spectral distance between i and j, and c is the scale parameter;
step four, obtaining a saliency map;
definition sNThe central pixel point j of the local window is the average value s of the significance of all pixel points i of the local windowNIs calculated as formula (2);
wherein, N is the number of all pixel points in the window, a is the number of the pixel points with non-zero significance value in the window; traversing the whole image through a sliding window to calculate s of central pixels of each windowNA saliency map s (k), s (k) { s ═ s, composing this image1，s2，...，sN}；
Step five, calculating the weight;
the background pixels and the abnormal points are given different weights, so that the influence of the abnormal points and noise is reduced during background model estimation, and the normal adaptability of the background model is better, wherein the weights are calculated as follows:
wherein M represents the wave band number of the image, r represents the spectral curve of the sample pixel, and the sample is assumed to be judged as the background pixel point and obeys the mean value mubCovariance of CbNormal distribution of (1), p (r | H)0) Is oneProbability that the detected pixel point is a background pixel;
normalizing p (r | H) by equation (4)0)：
Where N is the number of pixel points, k is the current pixel point, k is 1, 2k|H0) Is the corresponding weight after each pixel is normalized;
the final weight calculation formula is
Wherein, S (k) is the significance map calculated in the step four;
step six, calculating a detection operator;
the detection operator formula is as follows:
δP(r)＝(r-μP)TCP -1(r-μP) (6)
δP(r) is the calculated anomaly detection operator, where the mean vector μPSum covariance matrix CPIs defined as formula (7), (8):
wherein r isiSpectral curve, P, representing the ith pixelP(ri|H0) Is represented by riThe weight of (a) is calculated by the formula;
by traversing the polarization direction P ═ {1, 2, 3, 4}, the anomaly detection operator δ for each polarization direction is calculatedP(r)；
Step seven, carrying out polarization information fusion, wherein the formula is as follows
Wherein, δ (r) is the final abnormal target detection operator, p is the proportion of each polarization state information, a threshold T is selected according to requirements, and the detection result ω (r) is as follows:
and finally, the obtained omega (r) is a detection result, and the pixel point with the value of 1 represents that an abnormal target is detected.
The method solves the problems of less algorithm available information and inaccurate detection of the existing abnormal target detection method, can obviously increase the algorithm available information, and improves the detection precision.
Compared with the traditional high-spatial-resolution target detection, the method can better utilize spectral information and polarization information and fuse the high-spatial-resolution information with the spectral information and the polarization information, so that the target detection effect is better.
The embodiment of the invention also provides a computer-readable storage medium for storing a program, and the program realizes the steps of the abnormal target detection method based on the optical multi-dimensional information integrated perception system when being executed. In some possible embodiments, the various aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the invention described in the methods presented above in this description, when said program product is run on said terminal device.
In addition, the invention also provides a computer device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein when the processor executes the program, the steps of the abnormal target detection method based on the optical multi-dimensional information integration perception system are realized. A program product for implementing the above method, which may employ a portable compact disc read only memory (CD-ROM) and include program code, may be run on a terminal device, a computer device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Claims (4)
1. An abnormal target detection method based on an optical multi-dimensional information integrated perception system is characterized by comprising the following steps:
acquiring polarization spectrum data;
an optical multi-dimensional information integrated sensing system acquires polarization spectrum information;
secondly, reconstructing polarization state information;
definition IPM(k) For an input multi-dimensional polarization spectrum image, wherein M is the number of wave bands of the image, k is the number of pixel points, and P is {1, 2, 3, 4}, the polarization state information of different angles is respectively represented, and extracted single-spectrum data I are subjected to single-spectrum data IPM(k)＝{IP1(k)，IP2(k)，...，IPM(k) }, same in extraction regionThe pixel points in the polarization direction realize the complete reconstruction of the spatial information of the continuous spectrum section in different polarization state directions by a neighborhood pixel interpolation method;
step three, calculating significance;
after reconstructing the polarization state information, the significance of the data is calculated, the significance being defined as follows:
wherein, i is any pixel point of the local window, j is the central pixel point of the local window, and x2(pi，pj) Euclidean distance, x, between the position information in the window for i and j1(pi，pj) Is the spectral distance between i and j, and c is the scale parameter;
step four, obtaining a saliency map;
definition sNThe central pixel point j of the local window is the average value s of the significance of all pixel points i of the local windowNIs calculated as formula (2);
wherein, N is the number of all pixel points in the window, a is the number of the pixel points with non-zero significance value in the window; traversing the whole image through a sliding window to calculate s of central pixels of each windowNA saliency map s (k), s (k) ═ s, composing an image1，s2，...，sN}；
Step five, calculating the weight;
the weights are calculated as follows:
where M represents the number of bands of the image and r represents the spectral curve of the sample pixelAssuming that the sample is judged as the background pixel point obeying the mean value as mubCovariance of CbNormal distribution of (1), p (r | H)0) Is the probability that a detected pixel is a background pixel;
normalizing p (r | H) by equation (4)0)：
Where N is the number of pixel points, k is the current pixel point, k is 1, 2k|H0) Is the corresponding weight after each pixel is normalized;
the final weight calculation formula is
Step six, calculating a detection operator;
anomaly detection operator deltaPThe formula (r) is as follows:
δP(r)＝(r-μP)TCP -1(r-μP) (6)
wherein the mean vector muPSum covariance matrix CPIs defined as formula (7), (8):
wherein r isiSpectral curve, P, representing the ith pixelP(ri|H0) Is represented by riThe weight of (c);
each polarization is calculated by traversing the polarization direction P ═ {1, 2, 3, 4}Direction anomaly detection operator deltaP(r)；
Step seven, carrying out polarization information fusion,
the final abnormal target detection operator delta (r) is expressed as follows
Wherein, p is the proportion of each polarization state information;
according to the selected threshold value T, the detection result omega (r) is as follows:
the obtained omega (r) is the detection result, and the pixel point with the value of 1 represents that the abnormal target is detected.
2. The abnormal target detection method based on the optical multi-dimensional information integrated perception system according to claim 1, wherein the abnormal target detection method comprises the following steps:
in the first step, the optical multi-dimensional information integrated sensing system adopts a micro pixilated polarizing film to obtain polarization spectrum information, the pixilated polarizing film is a polarizing film formed by regularly arranging four polarization states, and each polarization state is in a pixel level on the physical dimension and is selected from 0 degree, 45 degrees, 90 degrees and 135 degrees.
3. A computer-readable storage medium having stored thereon a computer program, characterized in that: which computer program, when being executed by a processor, carries out the steps of the method as set forth in claim 1 or 2.
4. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein: the processor, when executing the program, implements the steps of the method of claim 1 or 2.
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