CN112927150A - Water reflection area spectrum recovery method of hyperspectral image and terminal device - Google Patents
Water reflection area spectrum recovery method of hyperspectral image and terminal device Download PDFInfo
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Abstract
The invention is suitable for the technical field of image processing, and provides a method for restoring a spectrum of a water reflection area of a hyperspectral image and terminal equipment, wherein the method comprises the following steps: carrying out region identification on the acquired hyperspectral image of the water body to obtain a water body region image and a water body reflection region image; counting a first reflectivity mean sequence and a first reflectivity standard deviation sequence of the corresponding spectrum of the water body region image, and counting a second reflectivity mean sequence and a second reflectivity standard deviation sequence of the corresponding spectrum of the water body reflection region image; and obtaining the spectrum reflectivity sequence after the water reflection area image is recovered according to the first reflectivity mean value sequence, the first reflectivity standard deviation sequence, the second reflectivity mean value sequence and the second reflectivity standard deviation sequence. The invention can obtain complete water body spectrum information, thereby improving the accuracy of identification and utilization by using the water body spectrum information.
Description
Technical Field
The invention belongs to the technical field of image processing, and particularly relates to a method for restoring a spectrum of a water reflection area of a hyperspectral image and terminal equipment.
Background
At present, the key point of distinguishing a hyperspectral image from a traditional RGB image is that the spectral resolution within an imaging waveband range reaches the nanometer level, so that ground objects which cannot be identified in conventional remote sensing can be effectively identified and quantitatively inverted in hyperspectral remote sensing.
However, with the improvement of the spatial resolution of the hyperspectral remote sensing, the reflection phenomenon of the water body in the hyperspectral image gradually increases, the reflection can be simply eliminated from the water body in the past, but the difference between the spectrum information of the reflection in the water body and the water body spectrum is large, and the simple elimination of the reflection from the water body can cause the water body spectrum information of the reflection part to be lost in the water body spectrum information, so that the accuracy of the identification and utilization of the water body spectrum information is influenced.
Disclosure of Invention
In view of this, the embodiment of the invention provides a method for restoring a water reflection region spectrum of a hyperspectral image and a terminal device, so as to solve the problem in the prior art that the accuracy is not high when water spectrum information obtained based on the hyperspectral image is identified and utilized.
The embodiment of the invention provides a method for restoring a spectrum of a water reflection area of a hyperspectral image, which comprises the following steps:
carrying out region identification on the acquired hyperspectral image of the water body to obtain a water body region image and a water body reflection region image;
counting a first reflectivity mean sequence and a first reflectivity standard deviation sequence of the corresponding spectrum of the water body region image, and counting a second reflectivity mean sequence and a second reflectivity standard deviation sequence of the corresponding spectrum of the water body reflection region image;
and obtaining the spectrum reflectivity sequence of the restored water reflection area image according to the first reflectivity mean sequence, the first reflectivity standard deviation sequence, the second reflectivity mean sequence and the second reflectivity standard deviation sequence.
A second aspect of the embodiments of the present invention provides a device for restoring a spectrum of a water reflection region of a hyperspectral image, including:
the identification module is used for carrying out region identification on the acquired water body hyperspectral image to obtain a water body region image and a water body reflection region image;
the statistical module is used for counting a first reflectivity mean sequence and a first reflectivity standard deviation sequence of the corresponding spectrum of the water body region image, and counting a second reflectivity mean sequence and a second reflectivity standard deviation sequence of the corresponding spectrum of the water body reflection region image;
and the recovery module is used for obtaining the spectrum reflectivity sequence after the water reflection area image is recovered according to the first reflectivity mean sequence, the first reflectivity standard deviation sequence, the second reflectivity mean sequence and the second reflectivity standard deviation sequence.
A third aspect of the embodiments of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method for restoring the spectrum of the reflection region of the hyperspectral image in the water body according to any one of the above descriptions when executing the computer program.
A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the method for restoring the spectrum of the reflection region of the water body of the hyperspectral image.
Compared with the prior art, the embodiment of the invention has the following beneficial effects: the embodiment of the invention obtains the water body area image and the water body reflection area image by carrying out area identification on the acquired water body hyperspectral image, a first reflectivity mean sequence and a first reflectivity standard deviation sequence of the spectrum corresponding to the water body area image can be respectively counted, and a second reflectivity mean sequence and a second reflectivity standard deviation sequence of the spectrum corresponding to the water reflection region image, obtaining a spectrum reflectivity sequence after the water reflection area image is recovered according to the first reflectivity mean sequence, the first reflectivity standard deviation mean sequence, the second reflectivity mean sequence and the second reflectivity standard deviation sequence, the spectrum of the water reflection region image can be recovered by utilizing the spectral information corresponding to the water body region image and the spectral information corresponding to the water body reflection region image, complete water body spectral information is obtained, and the accuracy of identification and utilization by utilizing the water body spectral information is further improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions 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 based on these drawings without inventive exercise.
FIG. 1 is a schematic flow chart of an implementation of a method for restoring a spectrum of a water reflection region of a hyperspectral image according to an embodiment of the invention;
FIG. 2 is a schematic diagram of a hyperspectral image of a water body provided by an embodiment of the invention;
FIG. 3 is a schematic diagram of an image of a region of a body of water provided by an embodiment of the invention;
FIG. 4 is a schematic diagram of an image of a reflection region of a water body according to an embodiment of the present invention;
fig. 5 is a graph illustrating a first reflectivity mean sequence and a first reflectivity standard deviation sequence, and a second reflectivity mean sequence and a second reflectivity standard deviation sequence according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of curves corresponding to sequences of spectral reflectivities before and after restoring an image of a water reflection region according to an embodiment of the present invention;
FIG. 7 is an exemplary diagram of a device for restoring spectra of a reflection region of a water body of a hyperspectral image according to an embodiment of the invention;
FIG. 8 is an exemplary diagram of a recovery module provided by embodiments of the invention;
fig. 9 is a schematic diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to explain the technical means of the present invention, the following description will be given by way of specific examples.
Fig. 1 is a schematic flow chart of an implementation process of a method for restoring a spectrum of a water reflection region of a hyperspectral image according to an embodiment of the present invention, which is described in detail below.
As shown in fig. 2, when water quality analysis or environmental data analysis is performed according to the hyperspectral image, after the hyperspectral image of the water body in the planned water area is obtained, since trees, houses, mountains and the like are often found around lakes or rivers, the hyperspectral image of the water body also contains reflection of the trees, the houses, the mountains and the like, and since the spectrum of the reflection area in the hyperspectral image of the water body is greatly affected by the trees, the houses, the mountains and the like, the spectrum information of the water body cannot be directly reflected, and the normal inversion of water quality parameters of the water body is affected, the spectrum of the reflection area in the hyperspectral image of the water body needs to be restored.
And S101, carrying out region identification on the acquired water body hyperspectral image to obtain a water body region image and a water body reflection region image.
Optionally, before performing region identification on the acquired hyperspectral image of the water body, the method may further include: and performing atmospheric correction on the acquired water body hyperspectral image to obtain an image after atmospheric correction.
Wherein, carry out regional discernment to the water hyperspectral image who obtains, obtain water regional image and water reflection regional image, can include: and carrying out area identification on the image after atmospheric correction to obtain a water body area image and a water body reflection area image.
The atmospheric correction can comprise lens correction, radiation correction, reflectivity correction and the like, and the image subjected to atmospheric correction is subjected to region identification, so that a water body region image and a water body reflection region image can be obtained more accurately.
Optionally, the area identification is performed on the acquired water body hyperspectral image to obtain a water body area image and a water body reflection area image, and the method may include: calculating the water body index of the water body hyperspectral image to obtain the water body index of the water body hyperspectral image; according to the characteristics of water reflection in the water hyperspectral image, calculating a reflection index of the water hyperspectral image to obtain a reflection index of the water hyperspectral image; and carrying out region identification on the water body hyperspectral image according to the water body index and the reflection index to obtain a water body region image and a water body reflection region image.
The acquired water body hyperspectral image may contain trees, houses, mountains and other real objects, sky, water body real object reflection and the like, and the complete water body spectral information can be accurately acquired only by carrying out region identification on the water body hyperspectral image. When the region identification is carried out, the Difference and the ratio of a green wave band and a near infrared wave band can be selected according to the characteristics of a Water body spectral curve, a Water body Index (NDWI) is calculated, the reflection Index can be calculated according to the characteristics of a real object reflection spectral curve in a Water body hyperspectral image, the region identification is carried out on the Water body hyperspectral image according to the Water body Index to obtain a Water body region image, and the region identification is carried out on the Water body hyperspectral image according to the reflection Index to obtain a Water body reflection region image.
For example, because real objects such as trees, houses, mountains, and the like and reflection images thereof in a water body have similar spectral characteristics, when the real objects in the water body are mainly trees, differences and ratios of red and near infrared bands can be selected according to the characteristics of a tree spectral curve, and a Vegetation Index (NDVI) can be calculated. When the real object reflection in the water body is mainly a house, the building index can be calculated according to the characteristics of the house spectral curve. The method comprises the steps of carrying out region identification on the water body hyperspectral image according to reflection indexes corresponding to object reflection in the water body, and obtaining the water body reflection region image more accurately.
Optionally, the area identification is performed on the water body hyperspectral image according to the water body index and the reflection index, so that a water body area image and a water body reflection area image are obtained, and the method can include the following steps: performing region identification on the water body hyperspectral image according to the water body index and the reflection index to obtain an initial water body region image containing a water body and sky and an initial water body reflection region image containing a real object and a reflection; performing region identification on the initial water body region image based on single-band thresholds of the water body and the sky to obtain a water body region image; and carrying out region identification on the initial water body reflection region image based on the symmetry of the real object and the reflection and edge detection to obtain the water body reflection region image.
When the hyperspectral image of the water body is directly identified by the water body index, the obtained initial water body area image contains the water body and the sky, and the obtained initial water body reflection area image contains trees, houses, mountains and other real objects and reflection of the real objects in the water body, so that the initial water body area image and the initial water body reflection area image need to be further identified to obtain a water body area image only containing water bodies and a water body reflection area image only containing reflection.
For example, referring to fig. 3, according to the spectral difference between the water body and the sky, a single-band threshold of the water body and the sky may be selected to perform region identification on the initial water body region image, so as to obtain a water body region image. For example, an image corresponding to a single band B12(430.9nm) smaller than a threshold value of 0.35 may be selected to distinguish the water body from the sky, and obtain a water body region image.
Illustratively, the tree, house, mountain and other real objects and the reflection thereof in the water body have symmetry, and the tree, house, mountain and other real objects and the reflection thereof in the water body have larger difference between the edge and the water body, so that the contour image of the real objects and the reflection thereof can be obtained based on edge detection, the contour image of the real objects and the reflection thereof is divided into two according to the symmetry, and the water body reflection area image is obtained according to the characteristic that the reflection is close to the water body.
Optionally, performing region identification on the initial water body reflection region image based on the symmetry of the real object and the reflection and edge detection to obtain a water body reflection region image, which may include: carrying out Gaussian filtering processing on the initial water reflection area image to obtain a filtered gray level image; obtaining a water body reflection threshold according to a reflection image and a gray level image in the initial water body reflection area image; performing edge detection on the initial water body reflection region image according to a water body reflection threshold value, and identifying an edge water body reflection region image in the initial water body reflection region image; and carrying out region identification on the edge water body reflection region image based on the symmetry of the real object and the reflection to obtain a water body reflection region image.
For example, referring to fig. 4, after the initial water reflection region image is obtained, smoothing may be performed through gaussian filtering to remove noise in the initial water reflection region image. The method comprises the steps of obtaining real objects such as trees, houses, mountain bodies and the like and water body reflection thresholds of reflection of the real objects in a water body based on a filtered gray image, carrying out edge detection on an initial water body reflection area image according to the water body reflection thresholds, identifying the real objects such as trees, houses, mountain bodies and the like in the initial water body reflection area image and the edges of the reflection of the real objects in the water body, namely the edge water body reflection area image, and obtaining the water body reflection area image based on the symmetry of the real objects and the reflection and the characteristic that the reflection of the real objects in the water body is close to the water body.
Step S102, a first reflectivity mean sequence and a first reflectivity standard deviation sequence of the corresponding spectrum of the water body region image are counted, and a second reflectivity mean sequence and a second reflectivity standard deviation sequence of the corresponding spectrum of the water body reflection region image are counted.
Referring to fig. 5, after the water body area image is obtained, a first reflectivity mean sequence and a first reflectivity standard deviation sequence of the corresponding spectrum can be obtained through statistics according to the water body area image, a curve M1 reflecting the reflectivity mean trend of each wave band of the water body area image can be obtained through the first reflectivity mean sequence, and a curve S1 reflecting the dispersion degree of the reflectivity of each wave band of the water body area image can be obtained through the first reflectivity standard deviation sequence. Similarly, after the water reflection area image is obtained, a second reflectivity mean sequence and a second reflectivity standard deviation sequence of the corresponding spectrum can be obtained through statistics according to the water reflection area image, a curve M2 reflecting the reflectivity mean trend of each wave band of the water reflection area image can be obtained through the second reflectivity mean sequence, and a curve S2 reflecting the dispersion degree of the reflectivity of each wave band of the water reflection area image can be obtained through the second reflectivity standard deviation sequence. It can be seen from the curves M1 and M2 that the spectral information corresponding to the water body area image and the water body reflection area image have a large difference, and the corresponding water quality parameters cannot be accurately inverted by directly using the spectral information of the water body reflection area image or simply excluding the spectral information of the water body reflection area image.
And S103, obtaining a spectrum reflectivity sequence after the water reflection area image is recovered according to the first reflectivity mean sequence, the first reflectivity standard deviation sequence, the second reflectivity mean sequence and the second reflectivity standard deviation sequence.
Optionally, obtaining the spectrum reflectivity sequence after the water reflection region image is restored according to the first reflectivity mean sequence, the first reflectivity standard deviation sequence, the second reflectivity mean sequence and the second reflectivity standard deviation sequence, which may include:
according to
The spectrum reflectivity recovered by each wave band corresponding to the water reflection area image is obtained, the spectrum reflectivity recovered by all the wave bands corresponding to the water reflection area image is obtained according to the method for obtaining the spectrum reflectivity recovered by each wave band corresponding to the water reflection area image, and the spectrum reflectivity sequence recovered by the water reflection area image is obtained according to the spectrum reflectivity recovered by all the wave bands corresponding to the water reflection area image.
Wherein s is the spectral reflectivity of each recovered wave band corresponding to the water reflection region image, and s is1The spectral reflectance of each band corresponding to the atmosphere corrected image,s2a second reflectivity mean, s, corresponding to each band in the second reflectivity mean sequence3A second standard deviation of reflectivity, s, corresponding to each band in the second sequence of standard deviations of reflectivity4A first standard deviation of reflectivity, s, for each band in the sequence of first standard deviations of reflectivity5And the first reflectivity mean value corresponds to each wave band in the first reflectivity mean value sequence.
The curve s1 corresponding to the sequence of spectral reflectivities before the restoration of the water reflection region image and the curve s2 corresponding to the sequence of spectral reflectivities after the restoration of the water reflection region image are shown in fig. 6, and it can be seen from the curve s2 in fig. 6 and the curve M1 in fig. 5 that the embodiment is according to the present embodiment
The spectrum reflectivity of each wave band corresponding to the water reflection area image is recovered, the spectrum reflectivity sequence of the water reflection area image after recovery is further obtained, the spectrum reflectivity of the water reflection area image can be accurately recovered to the spectrum reflectivity of a normal water body image, the complete spectrum information of the water body image can be further obtained, the water quality parameter inversion is carried out by utilizing the complete spectrum information of the water body image, and the accuracy of the water quality parameter inversion result is improved.
The water reflection area spectrum recovery method of the hyperspectral image obtains a water body area image and a water body reflection area image by carrying out area identification on the obtained water body hyperspectral image, can respectively count a first reflectivity mean sequence and a first reflectivity standard deviation sequence of a spectrum corresponding to the water body area image, and a second reflectivity mean sequence and a second reflectivity standard deviation sequence of a spectrum corresponding to the water body reflection area image, obtains a spectrum reflectivity sequence after the water body reflection area image is recovered according to the first reflectivity mean sequence, the first reflectivity standard deviation mean sequence, the second reflectivity mean sequence and the second reflectivity standard deviation sequence, can recover the spectrum of the water body reflection area image by utilizing the spectrum information corresponding to the water body area image and the spectrum information corresponding to the water body reflection area image, and obtains complete water body spectrum information, and further improve the accuracy of utilizing water spectral information to discern and utilize.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Corresponding to the method for restoring the spectrum of the water reflection region of the hyperspectral image in the embodiment, fig. 7 is an exemplary diagram of a device for restoring the spectrum of the water reflection region of the hyperspectral image in an embodiment of the invention. As shown in fig. 7, the apparatus may include: an identification module 71, a statistics module 72 and a recovery module 73.
The identification module 71 is configured to perform area identification on the acquired hyperspectral image of the water body to obtain a water body area image and a water body reflection area image;
the counting module 72 is configured to count a first reflectivity mean sequence and a first reflectivity standard deviation sequence of the spectrum corresponding to the water body region image, and count a second reflectivity mean sequence and a second reflectivity standard deviation sequence of the spectrum corresponding to the water body reflection region image;
and the recovery module 73 is configured to obtain a spectrum reflectivity sequence after the water reflection area image is recovered according to the first reflectivity mean sequence, the first reflectivity standard deviation sequence, the second reflectivity mean sequence, and the second reflectivity standard deviation sequence.
Optionally, the identification module 71 may be configured to perform water body index calculation on the water body hyperspectral image to obtain a water body index of the water body hyperspectral image; according to the characteristic of water reflection in the water body hyperspectral image, calculating a reflection index of the water body hyperspectral image to obtain a reflection index of the water body hyperspectral image; and carrying out region identification on the water body hyperspectral image according to the water body index and the reflection index to obtain a water body region image and a water body reflection region image.
Optionally, the identifying module 71 may be configured to perform region identification on the water body hyperspectral image according to the water body index and the reflection index, so as to obtain an initial water body region image containing a water body and a sky and an initial water body reflection region image containing a real object and a reflection; performing region identification on the initial water body region image based on single-band thresholds of a water body and a sky to obtain a water body region image; and carrying out region identification on the initial water body reflection region image based on the symmetry of the real object and the reflection and edge detection to obtain a water body reflection region image.
Optionally, the identifying module 71 may be configured to perform gaussian filtering on the initial water reflection region image to obtain a filtered grayscale image; obtaining a water body reflection threshold according to the reflection in the initial water body reflection area image and the gray level image; performing edge detection on the initial water body reflection region image according to the water body reflection threshold value, and identifying an edge water body reflection region image in the initial water body reflection region image; and carrying out region identification on the edge water body reflection region image based on the symmetry of the real object and the reflection to obtain a water body reflection region image.
Optionally, the identification module 71 may be further configured to perform atmospheric correction on the acquired water body hyperspectral image to obtain an atmospheric corrected image;
and carrying out area identification on the image after atmospheric correction to obtain a water body area image and a water body reflection area image.
Alternatively, referring to fig. 8, the recovery module 73 may include:
a first calculating unit 731 for calculating
Obtaining the spectrum reflectivity after recovery of each wave band corresponding to the water reflection area image;
wherein s is the spectral reflectivity of the restored each wave band corresponding to the water reflection region image, and s is1Spectral reflectance, s, for each band corresponding to the atmospheric corrected image2A second reflectivity mean, s, corresponding to each band in the second reflectivity mean sequence3Is the second reflectivity scaleThe second standard deviation of reflectivity, s, corresponding to each wave band in the standard deviation sequence4A first reflectivity standard deviation, s, corresponding to each band in the first reflectivity standard deviation sequence5A first reflectivity mean value corresponding to each wave band in the first reflectivity mean value sequence;
a second calculating unit 732, configured to obtain the recovered spectral reflectances of all the wave bands corresponding to the water reflection region image according to a method for obtaining the recovered spectral reflectances of each wave band corresponding to the water reflection region image;
the recovery unit 733 is configured to obtain a sequence of spectral reflectivities recovered from the water reflection region image according to the spectral reflectivities recovered from all the wave bands corresponding to the water reflection region image.
The water reflection area spectrum recovery device of the hyperspectral image obtains a water body area image and a water body reflection area image by carrying out area identification on the obtained water body hyperspectral image, can respectively count a first reflectivity mean sequence and a first reflectivity standard deviation sequence of a spectrum corresponding to the water body area image, and a second reflectivity mean sequence and a second reflectivity standard deviation sequence of a spectrum corresponding to the water body reflection area image, obtains a spectrum reflectivity sequence after the water body reflection area image is recovered according to the first reflectivity mean sequence, the first reflectivity standard deviation mean sequence, the second reflectivity mean sequence and the second reflectivity standard deviation sequence, and can recover the spectrum of the water body reflection area image by utilizing the spectrum information corresponding to the water body area image and the spectrum information corresponding to the water body reflection area image to obtain complete water body spectrum information, and further improve the accuracy of utilizing water spectral information to discern and utilize.
Fig. 9 is a schematic diagram of a terminal device according to an embodiment of the present invention. As shown in fig. 9, the terminal apparatus 900 of this embodiment includes: a processor 901, a memory 902 and a computer program 903 stored in said memory 902 and operable on said processor 901, such as a water reflection area spectrum recovery program of a hyperspectral image. When the processor 901 executes the computer program 903, the steps in the embodiment of the method for restoring the spectrum of the reflection region of the water body of the hyperspectral image, such as the steps S101 to S103 shown in fig. 1, are implemented, and when the processor 901 executes the computer program 903, the functions of the modules in the embodiments of the apparatuses, such as the functions of the modules 71 to 73 shown in fig. 7, are implemented.
Illustratively, the computer program 903 may be divided into one or more program modules, which are stored in the memory 902 and executed by the processor 901 to implement the present invention. The one or more program modules may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used for describing the execution process of the computer program 903 in the apparatus for restoring the spectrum of the reflection region of the water body of the hyperspectral image or the terminal device 900. For example, the computer program 903 may be divided into an identification module 71, a statistics module 72, and a recovery module 73, and specific functions of the modules are shown in fig. 7, which are not described in detail herein.
The terminal device 900 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal device may include, but is not limited to, a processor 901, a memory 902. Those skilled in the art will appreciate that fig. 9 is merely an example of a terminal device 900 and is not intended to limit terminal device 900 and may include more or fewer components than those shown, or some of the components may be combined, or different components, e.g., the terminal device may also include input output devices, network access devices, buses, etc.
The Processor 901 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 902 may be an internal storage unit of the terminal device 900, such as a hard disk or a memory of the terminal device 900. The memory 902 may also be an external storage device of the terminal device 900, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, provided on the terminal device 900. Further, the memory 902 may also include both an internal storage unit and an external storage device of the terminal apparatus 900. The memory 902 is used for storing the computer programs and other programs and data required by the terminal device 900. The memory 902 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A method for restoring the spectrum of a water reflection region of a hyperspectral image is characterized by comprising the following steps:
carrying out region identification on the acquired hyperspectral image of the water body to obtain a water body region image and a water body reflection region image;
counting a first reflectivity mean sequence and a first reflectivity standard deviation sequence of the corresponding spectrum of the water body region image, and counting a second reflectivity mean sequence and a second reflectivity standard deviation sequence of the corresponding spectrum of the water body reflection region image;
and obtaining the spectrum reflectivity sequence of the restored water reflection area image according to the first reflectivity mean sequence, the first reflectivity standard deviation sequence, the second reflectivity mean sequence and the second reflectivity standard deviation sequence.
2. The method for restoring the water reflection region spectrum of the hyperspectral image according to claim 1, wherein the step of performing region recognition on the acquired water hyperspectral image to obtain a water region image and a water reflection region image comprises the following steps:
calculating the water body index of the water body hyperspectral image to obtain the water body index of the water body hyperspectral image;
according to the characteristic of water reflection in the water body hyperspectral image, calculating a reflection index of the water body hyperspectral image to obtain a reflection index of the water body hyperspectral image;
and carrying out region identification on the water body hyperspectral image according to the water body index and the reflection index to obtain a water body region image and a water body reflection region image.
3. The method for restoring the water reflection region spectrum of the hyperspectral image according to claim 2, wherein the step of performing region recognition on the water hyperspectral image according to the water body index and the reflection index to obtain a water body region image and a water reflection region image comprises the following steps:
performing region identification on the water body hyperspectral image according to the water body index and the reflection index to obtain an initial water body region image containing a water body and a sky and an initial water body reflection region image containing a real object and a reflection;
performing region identification on the initial water body region image based on single-band thresholds of a water body and a sky to obtain a water body region image;
and carrying out region identification on the initial water body reflection region image based on the symmetry of the real object and the reflection and edge detection to obtain a water body reflection region image.
4. The method for restoring the water reflection region spectrum of the hyperspectral image according to claim 3, wherein the step of performing region recognition on the initial water reflection region image based on the symmetry of a real object and reflection and edge detection to obtain the water reflection region image comprises the following steps:
performing Gaussian filtering processing on the initial water reflection area image to obtain a filtered gray level image;
obtaining a water body reflection threshold according to the reflection in the initial water body reflection area image and the gray level image;
performing edge detection on the initial water body reflection region image according to the water body reflection threshold value, and identifying an edge water body reflection region image in the initial water body reflection region image;
and carrying out region identification on the edge water body reflection region image based on the symmetry of the real object and the reflection to obtain a water body reflection region image.
5. The method for restoring the spectrum of the reflection region of the water body of the hyperspectral image according to any one of claims 1 to 4, characterized by further comprising, before performing region identification on the acquired hyperspectral image of the water body:
carrying out atmospheric correction on the acquired water body hyperspectral image to obtain an image after atmospheric correction;
the regional identification is carried out to the water hyperspectral image who obtains, obtains water regional image and water reflection regional image, includes:
and carrying out area identification on the image after atmospheric correction to obtain a water body area image and a water body reflection area image.
6. The method for restoring the spectrum of the water reflection area of the hyperspectral image according to claim 5, wherein the obtaining the sequence of the spectral reflectances of the restored water reflection area of the image according to the first reflectance mean sequence, the first reflectance standard deviation sequence, the second reflectance mean sequence and the second reflectance standard deviation sequence comprises:
according to
Obtaining the spectrum reflectivity after recovery of each wave band corresponding to the water reflection area image;
wherein s is the spectral reflectivity of the restored each wave band corresponding to the water reflection region image, and s is1Spectral reflectance, s, for each band corresponding to the atmospheric corrected image2A second reflectivity mean, s, corresponding to each band in the second reflectivity mean sequence3A second reflectivity standard deviation, s, corresponding to each band in the second reflectivity standard deviation sequence4A first reflectivity standard deviation, s, corresponding to each band in the first reflectivity standard deviation sequence5A first reflectivity mean value corresponding to each wave band in the first reflectivity mean value sequence;
acquiring the spectrum reflectivity after recovery of all wave bands corresponding to the water body reflection region image according to the method for acquiring the spectrum reflectivity after recovery of each wave band corresponding to the water body reflection region image;
and acquiring a spectrum reflectivity sequence of the restored water reflection area image according to the spectrum reflectivity of the restored all wave bands corresponding to the water reflection area image.
7. The utility model provides a water reflection region spectrum recovery unit of high spectral image which characterized in that includes:
the identification module is used for carrying out region identification on the acquired water body hyperspectral image to obtain a water body region image and a water body reflection region image;
the statistical module is used for counting a first reflectivity mean sequence and a first reflectivity standard deviation sequence of the corresponding spectrum of the water body region image, and counting a second reflectivity mean sequence and a second reflectivity standard deviation sequence of the corresponding spectrum of the water body reflection region image;
and the recovery module is used for obtaining the spectrum reflectivity sequence after the water reflection area image is recovered according to the first reflectivity mean sequence, the first reflectivity standard deviation sequence, the second reflectivity mean sequence and the second reflectivity standard deviation sequence.
8. The apparatus for restoring spectra of water reflection areas of hyperspectral images according to claim 7, wherein the restoring module comprises:
a first computing unit for computing based on
Obtaining the spectrum reflectivity after recovery of each wave band corresponding to the water reflection area image;
wherein s is the spectral reflectivity of the restored each wave band corresponding to the water reflection region image, and s is1Spectral reflectance, s, for each band corresponding to the atmospheric corrected image2A second reflectivity mean, s, corresponding to each band in the second reflectivity mean sequence3A second reflectivity standard deviation, s, corresponding to each band in the second reflectivity standard deviation sequence4A first reflectivity standard deviation, s, corresponding to each band in the first reflectivity standard deviation sequence5A first reflectivity mean value corresponding to each wave band in the first reflectivity mean value sequence;
the second calculation unit is used for obtaining the spectrum reflectivity after recovery of all wave bands corresponding to the water reflection region image according to the method for obtaining the spectrum reflectivity after recovery of each wave band corresponding to the water reflection region image;
and the recovery unit is used for obtaining the spectrum reflectivity sequence of the water reflection region image after recovery according to the spectrum reflectivity of the water reflection region image after recovery of all wave bands.
9. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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