CN113627296B - Chlorophyll a concentration interpolation method and device, electronic equipment and storage medium - Google Patents
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Abstract
The application provides a chlorophyll a concentration interpolation method, which is applied to the technical field of mapping and comprises the following steps: acquiring a chlorophyll a concentration image to be interpolated, performing EMD (empirical mode decomposition) on row data and column data to obtain an intrinsic mode function component and a residual quantity of the row data and the column data, performing interpolation calculation to obtain an intrinsic mode function component after the row data interpolation and an intrinsic mode function component after the column data interpolation, adding the intrinsic mode function component after the row data interpolation and the residual quantity of the row data to obtain signal data after the row data interpolation, adding the intrinsic mode function component after the column data interpolation and the residual quantity of the column data to obtain signal data after the column data interpolation, calculating an average value of the signal data after the row data interpolation and the column data interpolation, and obtaining a 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 application relates to the technical field of mapping, in particular to a chlorophyll a concentration interpolation method, a chlorophyll a concentration interpolation device, electronic equipment and a storage medium.
Background
The medium resolution imaging spectrometer (MODIS, moderate-resolution Imaging Spectroradiometer) is a remote sensing instrument for observing global biological and physical processes in the united states earth observation system (EOS, earth Observation System) planning, and is mounted on two satellites of Terra and Aqua, the MODIS has 36 spectral bands (0.4 μm-14.4 μm), the resolution is 250m, 500m and 1000m, the earth surface is observed once every 1-2 days, and images of targets such as land surface, ocean water color, cloud, bio-geochemistry, aerosol, atmospheric temperature, phytoplankton and the like are acquired for free. However, the data availability is very low due to the large area missing of the global chlorophyll a concentration product data.
Disclosure of Invention
The main purpose of the application is to provide a chlorophyll a concentration interpolation method, a chlorophyll a concentration interpolation device, electronic equipment and a storage medium, which can effectively improve the utilization rate of chlorophyll a concentration products.
To achieve the above object, a first aspect of an embodiment of the present application provides a chlorophyll a concentration interpolation method, including:
acquiring a chlorophyll a concentration image to be interpolated, wherein the chlorophyll a concentration image comprises row data and column data;
performing EMD (empirical mode decomposition) on the row data to obtain an intrinsic mode function component and a margin of the row data, and performing EMD on the column data to obtain an intrinsic mode function component and a margin of the column data;
performing interpolation calculation on the intrinsic mode function component of the row data and the intrinsic mode function component of the column data by using a cubic spline interpolation method to obtain an intrinsic mode function component of the row data after interpolation and an intrinsic mode function component of the column data after interpolation;
adding the data-interpolated natural mode function component and the margin of the row data to obtain data of the data-interpolated signal, and adding the data-interpolated natural mode function component and the margin of the column data to obtain data of the data-interpolated signal;
calculating the average value of the signal data after the data interpolation and the average value of the signal data after the data interpolation;
and obtaining an interpolated chlorophyll a concentration image based on the average value of the signal data after the data interpolation and the average value of the signal data after the data interpolation.
In an embodiment, the acquiring the chlorophyll a concentration image to be interpolated includes:
obtaining MODIS data of chlorophyll a concentration to be interpolated and GOCI remote sensing images at the same time as the object;
inverting the GOCI remote sensing image into chlorophyll a concentration data;
converting the resolution of the chlorophyll-a concentration data into the same resolution as the subject, and obtaining converted chlorophyll-a concentration data;
and fusing the MODIS data of the converted chlorophyll a concentration with the GOCI remote sensing image to form the chlorophyll a concentration image to be interpolated.
In an embodiment, for each row of data, performing EMD (empirical mode decomposition) on the row of data in a first mode to obtain an intrinsic mode function component and a margin of the row of data;
the first mode includes:
s1, searching maximum value points and minimum value points in the row data, and fitting an upper envelope line and a lower envelope line;
s2, calculating the difference value between the row data and the average value of the upper envelope curve and the lower envelope curve of the row 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 a difference value between the difference value and an 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 row data;
s6, calculating a difference value between the row data and the imf, wherein the difference value is expressed as a allowance;
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 a preset threshold, or the margin has monotonicity.
In an embodiment, for each column of column data, EMD decomposition is performed on the column data using the first method to obtain an intrinsic mode function component and a residual of the column data.
In an embodiment, the preset condition includes:
the difference value zero crossing point data number is different from the extreme point data number by one or equal; the method comprises the steps of,
the average value of the sum of the upper envelope and the lower envelope of the difference is equal to zero.
In an embodiment, when the EMD decomposition is performed on the data, the EMD decomposition is stopped on the data when the limit standard deviation of the difference values of the two consecutive decompositions is within a preset range value.
In an embodiment, in the process of fusing the converted chlorophyll-a concentration data with the GOCI remote sensing image to form 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 only has the value, adopting the GOCI remote sensing image data.
A second aspect of an embodiment of the present application provides a chlorophyll a concentration interpolation device, including:
the acquisition module is used for acquiring a chlorophyll a concentration image to be interpolated, wherein the chlorophyll a concentration image comprises row data and column data;
the EMD decomposition module is used for carrying out EMD decomposition on the row data to obtain an intrinsic mode function component and a margin of the row data, and carrying out EMD decomposition on the column data to obtain an intrinsic mode function component and a margin of the column data;
the interpolation module is used for carrying out interpolation calculation on the intrinsic mode function component of the data and the intrinsic mode function component of the column data by utilizing a cubic spline interpolation method to obtain the intrinsic mode function component of the data after interpolation and the intrinsic mode function component of the column data after interpolation;
the first calculation module is used for adding the intrinsic mode function component after the line data interpolation and the margin of the line data to obtain the signal data after the line data interpolation, and adding the intrinsic mode function component after the line data interpolation and the margin of the line data to obtain the signal data after the line data interpolation;
the second calculation module is used for calculating the average value of the signal data after the data interpolation and the average value of the signal data after the 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 data interpolation and the average value of the signal data after the data interpolation.
A third aspect of an embodiment of the present application provides an electronic device, including:
the system comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, and is characterized in that the processor realizes the chlorophyll a concentration interpolation method provided by the first aspect of the embodiment of the application when executing the program.
A fourth aspect of the embodiments of the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the chlorophyll-a concentration interpolation method provided by the first aspect of the embodiments of the present application.
According to the embodiment of the application, the chlorophyll a concentration interpolation method, the device, the electronic equipment and the storage medium provided by the application are used for decomposing EMD acting on a time signal, applying the EMD to a space signal and correlating valued data around missing data, so that the problems of low accuracy and insufficient interpolation after interpolation in the traditional interpolation method are solved. No prior information of the observation area is 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 application or the technical solutions in the prior art, the drawings that are necessary for the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application and that other drawings may be obtained from them without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a chlorophyll a concentration interpolation method according to an embodiment of the present application;
fig. 2 is an experimental original graph based on a chlorophyll a concentration interpolation method according to an embodiment of the present application;
fig. 3 is an experimental mask diagram based on a chlorophyll a concentration interpolation method according to an embodiment of the present application;
fig. 4 is a graph of experimental results based on a chlorophyll a concentration interpolation method according to an embodiment of the present application;
FIG. 5 is a graph showing the accuracy of the results of the chlorophyll-a concentration interpolation apparatus according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a chlorophyll a concentration interpolation device according to an embodiment of the present application;
fig. 7 shows a schematic structural diagram of an electronic device.
Detailed Description
In order to make the application object, feature and advantage of the present application more obvious and understandable, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Referring to fig. 1, fig. 1 is a flowchart of a chlorophyll a concentration interpolation method according to an embodiment of the application, where the method may be applied to an electronic device, and the electronic device includes: electronic equipment such as mobile phones, tablet computers, portable computers, intelligent watches and intelligent glasses capable of performing data processing in moving and electronic equipment such as desktop computers, all-in-one machines and intelligent televisions capable of performing data processing in moving mainly comprise the following steps:
s101, acquiring 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 GOCI remote sensing images at the same time as the object; inverting the GOCI remote sensing image into chlorophyll a concentration data; converting the resolution of the chlorophyll-a concentration data into the same resolution as the subject, and obtaining converted chlorophyll-a concentration data; and fusing the converted chlorophyll a concentration data with the GOCI remote sensing image to form the chlorophyll a concentration image to be interpolated. The availability of the chlorophyll a concentration data 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 a 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, which will not be described herein.
In an example, the resolution of the remote sensing image of the GOCI is 500M, and the resolution of the data of chlorophyll-a concentration to be interpolated is 4KM, so the resolution of the remote sensing image is downsampled to 4KM. The interpolation method can be realized by a nearest neighbor method, a bilinear interpolation method, a three-time convolution interpolation method and the like, and the fusion method can be realized by an average value method, a weight method and the like, and the detailed description is omitted here.
S102, performing EMD (empirical mode decomposition) on the row data to obtain an intrinsic mode function component and a margin of the row data, and performing EMD on the column data to obtain an intrinsic mode function component and a margin of the column data.
In the present disclosure, for each row data and each column data, EMD decomposition is performed in a first manner, taking row data X (t) as an example, where the first manner specifically includes: s1, searching maximum value points and minimum value points in the data X (t), and fitting an upper envelope line max (t) and a lower envelope line min (t); s2, calculating the data X (t) and the data X (t)Difference in average of upper envelope max (t) and lower envelope min (t)S3, judging the difference value h 1 (t) whether a preset condition is satisfied; s4, if the difference value h 1 (t) if the preset condition is not satisfied, searching the difference h 1 Upper and lower envelopes of (t) calculating a target difference h Order of (A) (t) the target difference value h Order of (A) (t) is the difference h 1 (t) and the difference h 1 (t) the difference of the average values of the upper envelope and the lower envelope, and comparing the target difference h Order of (A) (t) as the difference h1 (t), executing S3 again; s5, if the difference value h1 (t) meets the preset condition, taking the difference value h1 (t) as an intrinsic mode function component (IMF, intrinsic Mode Functions) of the line data, and marking the intrinsic mode function component as IMF (t); s6, calculating a difference value between the data X (t) and the imf (t), wherein the difference value is expressed as a margin r (t), and r (t) =X (t) -imf (t); s1 to S6 are repeatedly performed for the margin r (t) until imf (t) or margin r (t) is decomposed to satisfy that the amplitude variation is smaller than a preset threshold, or the margin has monotonicity. When the data X (t) completes EMD decomposition, the +.>
In the present disclosure, the preset threshold may be 0.2,0.3 or the like, which is not limited by the present disclosure.
In an embodiment of the disclosure, the preset condition includes: the difference value h 1 (t) the number of zero crossing points differs from the number of extreme points by one or more; and the difference value h 1 The 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 EMD decomposition is performed on data, the EMD decomposition is stopped on the data when a limit standard deviation of a difference value of two consecutive decomposition is within a preset range value. In one example, when h is decomposed twice in succession k (t) and h k-1 The limit standard deviation SD of (t) is between 0.2 and 0.3, i.e. decomposition can be stoppedWherein the calculation formula of SD is:
s103, carrying out interpolation calculation on the intrinsic mode function component of the row data and the intrinsic mode function component of the column data by using a cubic spline interpolation method to obtain the intrinsic mode function component after the row data is interpolated and the intrinsic mode function component after the column data is interpolated.
And S104, adding the intrinsic mode function component after the data interpolation and the margin of the row data to obtain the signal data after the data interpolation, and adding the intrinsic mode function component after the data interpolation and the margin of the column data to obtain the signal data after the data interpolation.
S105, calculating the average value of the signal data after the data interpolation and the average value of the signal data after the data interpolation.
S106, obtaining an interpolated chlorophyll a concentration image based on the average value of the data-interpolated signal data and the average value of the data-interpolated signal data.
As shown in fig. 2, the data of partial chlorophyll a concentration is shown, wherein each grid represents the chlorophyll a concentration value of a region, and the total number of pixels is 70×20.
In order to check the accuracy of EMD interpolation and the range of complement values, data of a plurality of areas are selected as missing data, and mask processing is carried out on the selected areas.
As shown in fig. 3, the mask data is the data of partial 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 interpolation data of the partial chlorophyll a concentration data is the data of the chlorophyll a concentration interpolated by the EMD method.
As shown in fig. 5, the interpolation result accuracy of the data of the partial chlorophyll-a concentration is,showing the correlation coefficient R of chlorophyll a concentration data before and after interpolation 2 The expression isWherein Cov (x i ，x 0 ) Is x i ，x 0 Covariance of->Respectively x i ，x 0 Is a variance of (c). R is R 2 The closer the value is to 1, the better the accuracy of the complement.
Referring to fig. 6, fig. 6 is a schematic structural diagram of a chlorophyll a concentration interpolation device according to an embodiment of the application, where the device mainly includes:
an acquisition module 601 is configured to acquire 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 intrinsic mode function component and a residual of the row data, and perform EMD decomposition on the column data to obtain an intrinsic mode function component and a residual of the column data.
The interpolation module 603 is configured to interpolate the data-based natural mode function component and the column-based natural mode function component by using a cubic spline interpolation method to obtain the data-based interpolated natural mode function component and the column-based interpolated natural mode function component.
The first calculation module 604 is configured to add the line data interpolated natural mode function component and the line data residual to obtain the line data interpolated signal data, and add the line data interpolated natural mode function component and the line data residual to obtain the line data interpolated signal data.
The second calculating module 605 is configured to calculate an average value of the signal data after the data interpolation, and an average value of the signal data after the data interpolation.
And an output module 606, configured to obtain an interpolated chlorophyll-a concentration image based on the average value of the signal data after the data interpolation and the average value of the signal data after the data interpolation.
In an embodiment of the present disclosure, the acquiring the chlorophyll a concentration image to be interpolated includes:
acquiring data of chlorophyll a concentration to be interpolated and GOCI remote sensing images at the same time as the object; inverting the GOCI remote sensing image into chlorophyll a concentration data; converting the resolution of the chlorophyll-a concentration data into the same resolution as the subject, and obtaining converted chlorophyll-a concentration data; 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 present disclosure, for each line of line data, performing EMD decomposition on the line of data in a first manner to obtain an intrinsic mode function component and a residual of the line of data; the first mode includes: s1, searching maximum value points and minimum value points in the row data, and fitting an upper envelope line and a lower envelope line; s2, calculating the difference value between the row data and the average value of the upper envelope curve and the lower envelope curve of the row 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 a difference value between the difference value and an 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 row data; s6, calculating a difference value between the row data and the imf, wherein the difference value is expressed as a allowance; 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 a preset threshold, or the margin has monotonicity.
In an embodiment of the present disclosure, for each column of column data, EMD decomposition is performed on the column data in the first manner to obtain an intrinsic mode function component and a residual of the column data.
In an embodiment of the disclosure, the preset condition includes: the difference value zero crossing point data number is different from the extreme point data number by one or equal; and the average value of the sum of the upper envelope and the lower envelope of the difference is equal to zero.
In an embodiment of the disclosure, when the EMD decomposition is performed on the data, the EMD decomposition is stopped on the data when the limiting standard deviation of the difference values of the two consecutive decompositions is within a preset range value.
In an embodiment of the disclosure, in the process of fusing the converted chlorophyll-a concentration data with the GOCI remote sensing image to obtain 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 only has the value, adopting the GOCI remote sensing image data.
Referring to fig. 7, fig. 7 shows a hardware configuration diagram of an electronic device.
The electronic device described in the present embodiment includes:
the memory 41, the processor 42 and the computer program stored in the memory 41 and executable on the processor, the processor executing the program realizes the chlorophyll a concentration interpolation method described in the 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, the processor 42, the input device 43 and the output device 44 are connected by a bus 45.
The input device 43 may be a camera, a touch panel, a physical button, a mouse, or the like. The output device 44 may be in particular a display screen.
The memory 41 may be a high-speed random access memory (RAM, random Access Memory) memory or a non-volatile memory (non-volatile memory), such as a disk memory. Memory 41 is used to store a set of executable program code and processor 42 is coupled to memory 41.
Further, the embodiment of the present disclosure also provides a computer readable storage medium, which may be provided in the electronic device in the above embodiments, and the computer readable storage medium may be the electronic device in the above 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 embodiment shown in fig. 1 described above. Further, the computer-readable medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, etc. which may store the program code.
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 may be integrated into one module. The integrated modules may be implemented in hardware or in software functional modules.
The integrated modules, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such an understanding, the technical solution of the application may be embodied essentially or partly in the form of a software product or in part in addition to the prior art.
It should be noted that, for the sake of simplicity of description, the foregoing method embodiments are all expressed as a series of combinations of actions, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily all required for the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to the related descriptions of other embodiments.
The foregoing describes a chlorophyll a concentration interpolation method, apparatus, electronic device and readable storage medium provided by the present application, and those skilled in the art should not understand the present application to limit the scope of the present application in terms of specific embodiments and application ranges according to the concepts of the embodiments of the present application.
Claims (10)
1. A chlorophyll a concentration interpolation method, comprising:
acquiring a chlorophyll a concentration image to be interpolated, wherein the chlorophyll a concentration image comprises row data and column data;
performing EMD (empirical mode decomposition) on the row data to obtain an intrinsic mode function component and a margin of the row data, and performing EMD on the column data to obtain an intrinsic mode function component and a margin of the column data;
performing interpolation calculation on the intrinsic mode function component of the row data and the intrinsic mode function component of the column data by using a cubic spline interpolation method to obtain an intrinsic mode function component of the row data after interpolation and an intrinsic mode function component of the column data after interpolation;
adding the data-interpolated natural mode function component and the margin of the row data to obtain data of the data-interpolated signal, and adding the data-interpolated natural mode function component and the margin of the column data to obtain data of the data-interpolated signal;
calculating the average value of the signal data after the data interpolation and the average value of the signal data after the data interpolation;
and obtaining an interpolated chlorophyll a concentration image based on the average value of the signal data after the data interpolation and the average value of the signal data after the data interpolation.
2. A method according to claim 1, wherein the acquiring of chlorophyll a concentration images to be interpolated comprises:
acquiring data of chlorophyll a concentration to be interpolated acquired by a plurality of sensors and GOCI remote sensing images at the same time as the object;
inverting the GOCI remote sensing image into chlorophyll a concentration data;
converting the resolution of the chlorophyll-a concentration data into the same resolution as the subject, and obtaining converted chlorophyll-a concentration data;
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 line of line data, performing EMD decomposition on the line of data in a first manner to obtain an intrinsic mode function component and a residual of the line of data;
the first mode includes:
s1, searching maximum value points and minimum value points in the row data, and fitting an upper envelope line and a lower envelope line;
s2, calculating the difference value between the row data and the average value of the upper envelope curve and the lower envelope curve of the row 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 a difference value between the difference value and an 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 row data;
s6, calculating a difference value between the row data and the imf, wherein the difference value is expressed as a allowance;
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 a preset threshold, or the margin has monotonicity.
4. A method according to claim 3, wherein for each column of column data, EMD-decomposing the column data in the first manner results in an intrinsic mode function component and a margin of the column data.
5. The method according to claim 3 or 4, wherein the preset conditions comprise:
the difference value zero crossing point data number is different from the extreme point data number by one or equal; the method comprises the steps of,
the average value of the sum of the upper envelope and the lower envelope of the difference is equal to zero.
6. The method of claim 3 or 4, wherein,
and stopping performing EMD decomposition on the data when the limit standard deviation of the difference values of the two continuous decomposition is within a preset range value.
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 only has the value, adopting the GOCI remote sensing image data.
8. A chlorophyll a concentration interpolation device, characterized by comprising:
the acquisition module is used for acquiring a chlorophyll a concentration image to be interpolated, wherein the chlorophyll a concentration image comprises row data and column data;
the EMD decomposition module is used for carrying out EMD decomposition on the row data to obtain an intrinsic mode function component and a margin of the row data, and carrying out EMD decomposition on the column data to obtain an intrinsic mode function component and a margin of the column data;
the interpolation module is used for carrying out interpolation calculation on the intrinsic mode function component of the data and the intrinsic mode function component of the column data by utilizing a cubic spline interpolation method to obtain the intrinsic mode function component of the data after interpolation and the intrinsic mode function component of the column data after interpolation;
the first calculation module is used for adding the intrinsic mode function component after the line data interpolation and the margin of the line data to obtain the signal data after the line data interpolation, and adding the intrinsic mode function component after the line data interpolation and the margin of the line data to obtain the signal data after the line data interpolation;
the second calculation module is used for calculating the average value of the signal data after the data interpolation and the average value of the signal data after the 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 data interpolation and the average value of the signal data after the data interpolation.
9. An electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the chlorophyll a concentration interpolation method according to any one of claims 1 to 7 when executing the computer program.
10. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program, when executed by a processor, implements 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 |
| WO2021000361A1 (en) * | 2019-07-04 | 2021-01-07 | 浙江大学 | Geostationary ocean color satellite data reconstruction method based on empirical orthogonal function decomposition method |
| CN113160100A (en) * | 2021-04-02 | 2021-07-23 | 深圳市规划国土房产信息中心(深圳市空间地理信息中心) | Fusion method, fusion device and medium based on spectral information image |
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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 |
| WO2021000361A1 (en) * | 2019-07-04 | 2021-01-07 | 浙江大学 | Geostationary ocean color satellite data reconstruction method based on empirical orthogonal function decomposition method |
| CN113160100A (en) * | 2021-04-02 | 2021-07-23 | 深圳市规划国土房产信息中心(深圳市空间地理信息中心) | Fusion method, fusion device and medium based on spectral information image |
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