CN113627296A - Chlorophyll a concentration interpolation method and device, electronic equipment and storage medium - Google Patents
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Abstract
The invention provides a chlorophyll a concentration interpolation method, which is applied to the technical field of mapping and comprises the following steps: the method comprises the steps of obtaining a chlorophyll a concentration image to be interpolated, carrying out EMD decomposition on row data and column data to obtain inherent modal function components and allowance of the row data and the column data, carrying out interpolation calculation to obtain inherent modal function components after the row data interpolation and inherent modal function components after the column data interpolation, adding the inherent modal function components after the row data interpolation and the allowance of the row data to obtain signal data after the row data interpolation, adding the inherent modal function components after the column data interpolation and the allowance of the column data to obtain signal data after the column data interpolation, calculating the average value of the signal data after the row data interpolation and the column data interpolation, and obtaining the chlorophyll a concentration image after the interpolation based on the average value of the signal data after the row data interpolation and the column data interpolation. The application also discloses a chlorophyll a concentration interpolation device, electronic equipment and a storage medium.
Description
Technical Field
The present application relates to the field of surveying and mapping technologies, and in particular, to a chlorophyll a concentration interpolation method, apparatus, electronic device, and storage medium.
Background
A Moderate-resolution Imaging spectrometer (MODIS) is a remote sensing instrument used for observing global biological and physical processes in the American Earth Observation System (EOS), is carried on two Terra and Aqua satellites, has 36 spectral bands (0.4-14.4 mu m), has the resolutions of 250m, 500m and 1000m, observes the Earth surface once every 1-2 days, acquires images of targets such as land surface, ocean water color, cloud, biological geochemistry, aerosol, atmospheric temperature, phytoplankton and the like, and can be freely acquired. But the utilization rate of data is very low due to the large-area missing condition of the product data of the concentration of the whole chlorophyll a.
Disclosure of Invention
The application mainly aims to provide a chlorophyll a concentration interpolation method, a chlorophyll a concentration interpolation device, electronic equipment and a storage medium, and the chlorophyll a concentration interpolation method can effectively improve the utilization rate of chlorophyll a concentration products.
In order to achieve the above object, a first aspect of embodiments of the present application provides a method for interpolating a chlorophyll-a concentration, including:
acquiring a chlorophyll a concentration image to be interpolated, wherein the chlorophyll a concentration image comprises row data and column data;
performing EMD on the row data to obtain an inherent modal function component and a margin of the row data, and performing EMD on the column data to obtain an inherent modal function component and a margin of the column data;
carrying out interpolation calculation on the inherent modal function component of the row data and the inherent modal function component of the column data by utilizing a cubic spline interpolation method to obtain the inherent modal function component after the row data is interpolated and the inherent modal function component after the column data is interpolated;
adding the inherent modal function component after the line data interpolation and the margin of the line data to obtain signal data after the line data interpolation, and adding the inherent modal function component after the line data interpolation and the margin of the line data to obtain signal data after the line data interpolation;
calculating the average value of the signal data after the line data interpolation and the average value of the signal data after the line data interpolation;
and obtaining an interpolated chlorophyll a concentration image based on the average value of the signal data after the line data interpolation and the average value of the signal data after the line data interpolation.
In an embodiment, the obtaining the chlorophyll-a concentration image to be interpolated includes:
obtaining MODIS data of chlorophyll a concentration to be interpolated and a GOCI remote sensing image of the object at the same time;
inverting the GOCI remote sensing image into chlorophyll a concentration data;
converting the resolution of the data of the chlorophyll a concentration into the resolution which is the same as that of the object to obtain the converted data of the chlorophyll a concentration;
and fusing the converted MODIS data of the chlorophyll a concentration and the GOCI remote sensing image into the chlorophyll a concentration image to be interpolated.
In one embodiment, for each row of data, performing EMD on the row of data by adopting a first mode to obtain an inherent modal function component and a margin of the row of data;
the first mode includes:
s1, searching a maximum value point and a minimum value point in the row of data, and fitting an upper envelope curve and a lower envelope curve;
s2, calculating the difference value between the line data and the average value of the upper envelope curve and the lower envelope curve of the line data;
s3, judging whether the difference value meets a preset condition or not;
s4, if the difference does not meet the preset condition, searching an upper envelope line and a lower envelope line of the difference, calculating a target difference value, wherein the target difference value is the difference value between the difference value and the average value of the upper envelope line and the lower envelope line of the difference value, taking the target difference value as the difference value, and executing S3 again;
s5, if the difference value meets the preset condition, taking the difference value as imf of the line data;
s6, calculating the difference between the line data and the imf, and expressing the difference as a margin;
for the margin, S1 to S6 are repeatedly performed until imf or the margin is decomposed to satisfy that the amplitude variation is smaller than the preset threshold, or the margin has monotonicity.
In an embodiment, for each column of column data, performing EMD on the column data in the first manner obtains an inherent mode function component and a margin of the column data.
In one embodiment, the preset conditions include:
the difference value zero crossing point data number is one or equal to the data number of the extreme point data number; and the number of the first and second groups,
the average of the sum of the upper and lower envelopes of the difference is equal to zero.
In one embodiment, when EMD is performed on the line data, and the limit standard deviation of the difference value of two consecutive decompositions is within a preset range value, EMD is stopped on the line data.
In an embodiment, during the process of fusing the converted data of the chlorophyll-a concentration and the GOCI remote sensing image into the image of the chlorophyll-a concentration to be interpolated,
and for each point of the chlorophyll a concentration image to be interpolated, if the converted chlorophyll a concentration data at a certain point and the GOCI remote sensing image have the same value, adopting the converted chlorophyll a concentration data as the image data of the point, and if the converted chlorophyll a concentration data at a certain point has the value, adopting the GOCI remote sensing image data.
A second aspect of the embodiments of the present application provides a chlorophyll a concentration interpolation apparatus, including:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a chlorophyll a concentration image to be interpolated, and the chlorophyll a concentration image comprises row data and column data;
the EMD decomposition module is used for performing EMD decomposition on the row data to obtain an inherent modal function component and a margin of the row data, and performing EMD decomposition on the column data to obtain an inherent modal function component and a margin of the column data;
the interpolation module is used for carrying out interpolation calculation on the inherent modal function component of the row data and the inherent modal function component of the column data by utilizing a cubic spline interpolation method to obtain the inherent modal function component after the row data is interpolated and the inherent modal function component after the column data is interpolated;
the first calculation module is used for adding the inherent modal function component after the line data interpolation and the margin of the line data to obtain signal data after the line data interpolation, and adding the inherent modal function component after the line data interpolation and the margin of the line data to obtain signal data after the line data interpolation;
the second calculation module is used for calculating the average value of the signal data after the line data interpolation and the average value of the signal data after the line data interpolation;
and the output module is used for obtaining an interpolated chlorophyll a concentration image based on the average value of the signal data after the line data interpolation and the average value of the signal data after the line data interpolation.
A third aspect of embodiments of the present application provides an electronic device, including:
the chlorophyll-a concentration interpolation method is characterized by comprising a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor executes the program to realize the chlorophyll-a concentration interpolation method provided by the first aspect of the embodiment of the present application.
A fourth aspect of embodiments of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the chlorophyll-a concentration interpolation method provided in the first aspect of embodiments of the present application.
As can be seen from the foregoing embodiments of the present application, the chlorophyll-a concentration interpolation method, apparatus, electronic device and storage medium provided by the present application decompose EMD acting on a time signal, apply the EMD to a spatial signal, and associate the valued data around the missing data, thereby solving the problems of low accuracy and insufficient interpolation after interpolation by the conventional interpolation method. The prior information of an observation area is not needed, the speed of the interpolation method is high, the correlation of the interpolated result is high, and the method has high actual operability.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic flow chart of a chlorophyll a concentration interpolation method according to an embodiment of the present disclosure;
fig. 2 is an experimental original diagram of a chlorophyll a concentration interpolation method according to an embodiment of the present disclosure;
fig. 3 is an experimental mask diagram based on a chlorophyll-a concentration interpolation method according to an embodiment of the present disclosure;
fig. 4 is a graph of experimental results of an interpolation method based on chlorophyll-a concentration according to an embodiment of the present disclosure;
fig. 5 is a result precision diagram of a chlorophyll a concentration interpolation apparatus according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of a chlorophyll a concentration interpolation apparatus according to an embodiment of the present disclosure;
fig. 7 shows a schematic structural diagram of an electronic device.
Detailed Description
In order to make the purpose, features and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Referring to fig. 1, fig. 1 is a schematic flow chart of a chlorophyll a concentration interpolation method according to an embodiment of the present application, where the method is applicable to an electronic device, and the electronic device includes: the method mainly comprises the following steps of using mobile phones, tablet computers, portable computers, intelligent watches, intelligent glasses and other electronic equipment capable of performing data processing in the moving process and using desktop computers, all-in-one machines, intelligent televisions and other electronic equipment capable of performing data processing in the moving process, wherein the electronic equipment mainly comprises the following electronic equipment:
s101, obtaining a chlorophyll a concentration image to be interpolated, wherein the chlorophyll a concentration image comprises row data and column data.
In one embodiment, S101 includes: acquiring data of chlorophyll a concentration to be interpolated and a GOCI remote sensing image of the object at the same time; inverting the GOCI remote sensing image into chlorophyll a concentration data; converting the resolution of the data of the chlorophyll a concentration into the resolution which is the same as that of the object to obtain the converted data of the chlorophyll a concentration; and fusing the converted chlorophyll a concentration data with the GOCI remote sensing image to form the chlorophyll a concentration image to be interpolated. Therefore, the availability of the data of the chlorophyll a concentration is enriched, and the efficiency of the EMD method is improved.
In the present disclosure, the data of chlorophyll-a concentration to be interpolated may be the MODIS data product.
In the present disclosure, the inversion method may be implemented by a band ratio method, a vegetation index method, machine learning, a neural network, and the like, and details thereof are not repeated here.
In an example, the resolution of the GOCI remote sensing image is 500M, and the resolution of the data of the chlorophyll-a concentration to be interpolated is 4KM, so the resolution of the remote sensing image is down-sampled to 4 KM. The interpolation method can be realized by methods such as a nearest neighbor method, a bilinear interpolation method, a cubic convolution interpolation method and the like, and the fusion method can be realized by methods such as an average value method, a weight method and the like, and details are not repeated here.
S102, performing EMD on the row data to obtain the inherent modal function component and the allowance of the row data, and performing EMD on the column data to obtain the inherent modal function component and the allowance of the column data.
In the present disclosure, EMD is performed on each row of data and each column of data in a first manner, taking row data x (t) as an example, the first manner specifically includes: s1, searching a maximum value point and a minimum value point in the row data X (t), and fitting an upper envelope line max (t) and a lower envelope line min (t); s2, calculating the difference value between the row data X (t) and the average value of the upper envelope curve max (t) and the lower envelope curve min (t) of the row data X (t)
S3, judging the difference h1(t) whether a preset condition is satisfied; s4, if the difference h1(t) if the preset condition is not satisfied, the difference h is searched1(t) upper and lower envelope lines, calculating a target difference hEyes of a user(t), the target difference value hEyes of a user(t) is the difference h1(t) and the difference h1(t) difference of average values of upper and lower envelope lines, and the target difference hEyes of a user(t) as the difference h1(t), S3 is performed again; s5, if the difference h1(t) satisfies the preset condition, taking the difference h1(t) as an Intrinsic Mode Functions component (IMF) of the line data, and recording as IMF (t); s6, calculating a difference between the line data x (t) and imf (t), which is expressed as a margin r (t), and r (t) x (t) -imf (t); and repeatedly executing S1 to S6 for the residual r (t) until imf (t) or the residual r (t) is decomposed into the condition that the amplitude change is less than a preset threshold value, or the residual has monotonicity. When the row data x (t) completes the EMD decomposition,
in the present disclosure, the preset threshold may be 0.2, 0.3, etc., which the present disclosure does not limit.
In an embodiment of the present disclosure, the preset condition includes: the difference h1(t) the difference between the data number of the zero crossing point and the data number of the extreme point is one or equal; and, the difference h1The average of the sum of the upper envelope and the lower envelope of (t) is equal to zero.
In an embodiment of the present disclosure, when performing EMD decomposition on line data, and a limit standard deviation of a difference value of two consecutive decompositions is within a preset range value, the performing of EMD decomposition on the line data is stopped. In one example, when two successive decompositions hk(t) and hk-1(t) stopping the decomposition if the standard deviation SD is limited to 0.2-0.3, wherein the formula of SD is as follows:
s103, carrying out interpolation calculation on the inherent modal function component of the row data and the inherent modal function component of the column data by utilizing a cubic spline interpolation method to obtain the inherent modal function component after the row data is interpolated and the inherent modal function component after the column data is interpolated.
S104, adding the inherent modal function component after the line data interpolation and the margin of the line data to obtain signal data after the line data interpolation, and adding the inherent modal function component after the line data interpolation and the margin of the line data to obtain signal data after the line data interpolation.
And S105, calculating the average value of the signal data after the line data interpolation and the average value of the signal data after the line data interpolation.
And S106, obtaining an interpolated chlorophyll a concentration image based on the average value of the signal data after the line data interpolation and the average value of the signal data after the line data interpolation.
As shown in fig. 2, the data of partial chlorophyll a concentration is shown, wherein each grid represents the chlorophyll a concentration value of one region, and the total number of pixels is 70 × 20.
In order to check the precision of the EMD interpolation and the range of the complement value, data of a plurality of areas are selected as missing data, and the selected areas are subjected to mask processing.
As shown in fig. 3, the mask data is the data of the chlorophyll a concentration, and the mask positions are two rectangular areas, wherein the area 1 is the mask between different concentrations, and the area 2 is the mask between the same concentrations.
As shown in fig. 4, the data of the chlorophyll a concentration is interpolated by the EMD method.
As shown in FIG. 5, for the interpolation result precision of the data of partial chlorophyll-a concentration, the correlation coefficient R of the chlorophyll-a concentration data before and after interpolation is shown2The expression is
Wherein, Cov (x)i，x0) Is xi，x0The covariance of (a) of (b),
are respectively xi，x0The variance of (c). R2A value closer to 1 indicates better precision of the complement.
Referring to fig. 6, fig. 6 is a schematic structural diagram of a chlorophyll a concentration interpolation apparatus according to an embodiment of the present application, the apparatus mainly includes:
the obtaining module 601 is configured to obtain a chlorophyll a concentration image to be interpolated, where the chlorophyll a concentration image includes row data and column data.
The EMD decomposition module 602 is configured to perform EMD decomposition on the row data to obtain an inherent modal function component and a margin of the row data, and perform EMD decomposition on the column data to obtain an inherent modal function component and a margin of the column data.
The interpolation module 603 is configured to perform interpolation calculation on the eigen-modal function component of the row data and the eigen-modal function component of the column data by using a cubic spline interpolation method to obtain an eigen-modal function component after the row data is interpolated and an eigen-modal function component after the column data is interpolated.
A first calculating module 604, configured to add the intrinsic mode function component after the line data interpolation and the margin of the line data to obtain signal data after the line data interpolation, and add the intrinsic mode function component after the line data interpolation and the margin of the line data to obtain signal data after the line data interpolation.
A second calculating module 605, configured to calculate an average value of the signal data after the line data interpolation and an average value of the signal data after the line data interpolation.
An output module 606, configured to obtain an interpolated chlorophyll-a concentration image based on the average value of the signal data after the line data interpolation and the average value of the signal data after the line data interpolation.
In an embodiment of the present disclosure, the obtaining the chlorophyll-a concentration image to be interpolated includes:
acquiring data of chlorophyll a concentration to be interpolated and a GOCI remote sensing image of the object at the same time; inverting the GOCI remote sensing image into chlorophyll a concentration data; converting the resolution of the data of the chlorophyll a concentration into the resolution which is the same as that of the object to obtain the converted data of the chlorophyll a concentration; and fusing the converted chlorophyll a concentration data with the GOCI remote sensing image to form the chlorophyll a concentration image to be interpolated.
In an embodiment of the disclosure, for each row of data, performing EMD decomposition on the row of data by using a first method to obtain an inherent modal function component and a margin of the row of data; the first mode includes: s1, searching a maximum value point and a minimum value point in the row of data, and fitting an upper envelope curve and a lower envelope curve; s2, calculating the difference value between the line data and the average value of the upper envelope curve and the lower envelope curve of the line data; s3, judging whether the difference value meets a preset condition or not; s4, if the difference does not meet the preset condition, searching an upper envelope line and a lower envelope line of the difference, calculating a target difference value, wherein the target difference value is the difference value between the difference value and the average value of the upper envelope line and the lower envelope line of the difference value, taking the target difference value as the difference value, and executing S3 again; s5, if the difference value meets the preset condition, taking the difference value as imf of the line data; s6, calculating the difference between the line data and the imf, and expressing the difference as a margin; for the margin, S1 to S6 are repeatedly performed until imf or the margin is decomposed to satisfy that the amplitude variation is smaller than the preset threshold, or the margin has monotonicity.
In an embodiment of the present disclosure, for each column of column data, performing EMD on the column data in the first manner to obtain an inherent modal function component and a margin of the column data.
In an embodiment of the present disclosure, the preset condition includes: the difference value zero crossing point data number is one or equal to the data number of the extreme point data number; and the average of the sum of the upper and lower envelopes of the difference is equal to zero.
In an embodiment of the present disclosure, when performing EMD decomposition on line data, and a limit standard deviation of a difference value of two consecutive decompositions is within a preset range value, the performing of EMD decomposition on the line data is stopped.
In an embodiment of the present disclosure, during the process of fusing the converted data of the chlorophyll-a concentration and the GOCI remote sensing image into the chlorophyll-a concentration image to be interpolated,
and for each point of the chlorophyll a concentration image to be interpolated, if the converted chlorophyll a concentration data at a certain point and the GOCI remote sensing image have the same value, adopting the converted chlorophyll a concentration data as the image data of the point, and if the converted chlorophyll a concentration data at a certain point has the value, adopting the GOCI remote sensing image data.
Referring to fig. 7, fig. 7 is a hardware structure diagram of an electronic device.
The electronic device described in this embodiment includes:
a memory 41, a processor 42 and a computer program stored on the memory 41 and executable on the processor, the processor when executing the program implementing the chlorophyll-a concentration interpolation method described in the foregoing embodiment shown in fig. 1.
Further, the electronic device further includes:
at least one input device 43; at least one output device 44.
The memory 41, processor 42 input device 43 and output device 44 are connected by a bus 45.
The input device 43 may be a camera, a touch panel, a physical button, or a mouse. The output device 44 may specifically be a display screen.
The Memory 41 may be a high-speed Random Access Memory (RAM) Memory or a non-volatile Memory (non-volatile Memory), such as a magnetic disk Memory. The memory 41 is used for storing a set of executable program code, and the processor 42 is coupled to the memory 41.
Further, the embodiment of the present disclosure also provides a computer-readable storage medium, where the computer-readable storage medium may be an electronic device provided in the foregoing embodiments, and the computer-readable storage medium may be the electronic device in the foregoing embodiment shown in fig. 7. The computer-readable storage medium has stored thereon a computer program which, when executed by a processor, implements the chlorophyll-a concentration interpolation method described in the foregoing embodiment shown in fig. 1. Further, the computer-readable storage medium may be various media that can store program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
It should be noted that each functional module in each embodiment of the present disclosure may be integrated into one processing module, or each module may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode.
The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be substantially or partially embodied in the form of a software product, or all or part of the technical solution that contributes to the prior art.
It should be noted that, for the sake of simplicity, the above-mentioned method embodiments are described as a series of acts or combinations, but those skilled in the art should understand that the present invention is not limited by the described order of acts, as some steps may be performed in other orders or simultaneously according to the present invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred and that no acts or modules are necessarily required of the invention.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In view of the above description of the method, device, electronic device and readable storage medium for chlorophyll-a concentration interpolation provided by the present invention, those skilled in the art will appreciate that the concepts according to the embodiments of the present invention may be modified in the specific implementation manners and application ranges.
Claims (10)
1. A chlorophyll a concentration interpolation method is characterized by comprising the following steps:
acquiring a chlorophyll a concentration image to be interpolated, wherein the chlorophyll a concentration image comprises row data and column data;
performing EMD on the row data to obtain an inherent modal function component and a margin of the row data, and performing EMD on the column data to obtain an inherent modal function component and a margin of the column data;
carrying out interpolation calculation on the inherent modal function component of the row data and the inherent modal function component of the column data by utilizing a cubic spline interpolation method to obtain the inherent modal function component after the row data is interpolated and the inherent modal function component after the column data is interpolated;
adding the inherent modal function component after the line data interpolation and the margin of the line data to obtain signal data after the line data interpolation, and adding the inherent modal function component after the line data interpolation and the margin of the line data to obtain signal data after the line data interpolation;
calculating the average value of the signal data after the line data interpolation and the average value of the signal data after the line data interpolation;
and obtaining an interpolated chlorophyll a concentration image based on the average value of the signal data after the line data interpolation and the average value of the signal data after the line data interpolation.
2. The method according to claim 1, wherein the obtaining of the chlorophyll-a concentration image to be interpolated comprises:
acquiring data of chlorophyll a concentration to be interpolated, which is acquired by a plurality of sensors, and a GOCI remote sensing image of the object at the same time;
inverting the GOCI remote sensing image into chlorophyll a concentration data;
converting the resolution of the data of the chlorophyll a concentration into the resolution which is the same as that of the object to obtain the converted data of the chlorophyll a concentration;
and fusing the converted chlorophyll a concentration data with the GOCI remote sensing image to form the chlorophyll a concentration image to be interpolated.
3. The method of claim 1, wherein for each row of data, performing EMD on the row of data in a first manner to obtain a natural mode function component and a margin of the row of data;
the first mode includes:
s1, searching a maximum value point and a minimum value point in the row of data, and fitting an upper envelope curve and a lower envelope curve;
s2, calculating the difference value between the line data and the average value of the upper envelope curve and the lower envelope curve of the line data;
s3, judging whether the difference value meets a preset condition or not;
s4, if the difference does not meet the preset condition, searching an upper envelope line and a lower envelope line of the difference, calculating a target difference value, wherein the target difference value is the difference value between the difference value and the average value of the upper envelope line and the lower envelope line of the difference value, taking the target difference value as the difference value, and executing S3 again;
s5, if the difference value meets the preset condition, taking the difference value as imf of the line data;
s6, calculating the difference between the line data and the imf, and expressing the difference as a margin;
for the margin, S1 to S6 are repeatedly performed until imf or the margin is decomposed to satisfy that the amplitude variation is smaller than the preset threshold, or the margin has monotonicity.
4. The method of claim 3, wherein for each column of column data, EMD decomposition of the column data in the first manner yields a natural mode function component and a margin for the column data.
5. The method according to claim 3 or 4, wherein the preset conditions include:
the difference value zero crossing point data number is one or equal to the data number of the extreme point data number; and the number of the first and second groups,
the average of the sum of the upper and lower envelopes of the difference is equal to zero.
6. The method of claim 3 or 4, wherein,
and when EMD is performed on the line data and the limiting standard deviation of the difference value of the two continuous decompositions is within a preset range value, EMD is stopped being performed on the line data.
7. The method according to claim 2, wherein, in the process of fusing the converted chlorophyll-a concentration data with the GOCI remote sensing image into the chlorophyll-a concentration image to be interpolated,
and for each point of the chlorophyll a concentration image to be interpolated, if the converted chlorophyll a concentration data at a certain point and the GOCI remote sensing image have the same value, adopting the converted chlorophyll a concentration data as the image data of the point, and if the converted chlorophyll a concentration data at a certain point has the value, adopting the GOCI remote sensing image data.
8. A chlorophyll-a concentration interpolation apparatus, comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a chlorophyll a concentration image to be interpolated, and the chlorophyll a concentration image comprises row data and column data;
the EMD decomposition module is used for performing EMD decomposition on the row data to obtain an inherent modal function component and a margin of the row data, and performing EMD decomposition on the column data to obtain an inherent modal function component and a margin of the column data;
the interpolation module is used for carrying out interpolation calculation on the inherent modal function component of the row data and the inherent modal function component of the column data by utilizing a cubic spline interpolation method to obtain the inherent modal function component after the row data is interpolated and the inherent modal function component after the column data is interpolated;
the first calculation module is used for adding the inherent modal function component after the line data interpolation and the margin of the line data to obtain signal data after the line data interpolation, and adding the inherent modal function component after the line data interpolation and the margin of the line data to obtain signal data after the line data interpolation;
the second calculation module is used for calculating the average value of the signal data after the line data interpolation and the average value of the signal data after the line data interpolation;
and the output module is used for obtaining an interpolated chlorophyll a concentration image based on the average value of the signal data after the line data interpolation and the average value of the signal data after the line data interpolation.
9. An electronic device, comprising: memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the computer program, implements the steps of the chlorophyll-a concentration interpolation method according to any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the chlorophyll-a concentration interpolation method according to any one of claims 1 to 7.
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| CN108038351A (en) * | 2017-12-06 | 2018-05-15 | 武汉大学 | A kind of chlorophyll computational methods based on remote sensing image and water ecological model |
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