A method and system for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas

Abstract

The present invention provides a method and system for suppressing vegetation information of optical remote sensing images in arid and semi-arid areas based on image filtering. Specifically, the method includes step 1: pre-processing the collected optical remote sensing images to obtain the surface reflectance images of each band; step 2: calculating the normalized vegetation index, and then calculating the vegetation coverage of the area to be processed based on the vegetation index; step 3: constructing a vegetation coverage judgment model; step 4: combining the vegetation coverage judgment model, searching the mean value of the image pixel to be processed corresponding to the low vegetation coverage area according to the variable window as the value of each central pixel to be processed corresponding to the high vegetation coverage area, and obtaining the vegetation information suppression result image corresponding to the image to be processed. The present invention realizes the vegetation information suppression of optical remote sensing images in arid and semi-arid areas, solves the requirements of the prior knowledge and field data collection work in removing the interference of vegetation information in the existing technical methods, and improves the reliability of the image vegetation information suppression results.

Description

Technical Field

[0001] The invention belongs to the field of remote sensing information extraction and digital image processing, and relates to vegetation information suppression of multi-spectral or hyperspectral remote sensing images in various bands of arid and semi-arid areas, and specifically relates to a method and system for suppressing vegetation information of optical remote sensing images in arid and semi-arid areas based on image filtering. Background Art

[0002] In the field of remote sensing basic geology and quantitative inversion of soil properties, optical remote sensing has become one of the important data sources. With the development of remote sensing sensors and their imaging technology, more and more optical remote sensing data from different platforms and sensors are available. Its advantages such as convenient acquisition, high imaging quality, and rich band information can provide rich and reliable data support for research in basic geology, soil properties and other fields.

[0003] Removing vegetation information interference is an important prerequisite for remote sensing application research in the fields of remote sensing geology, soil properties, etc. At present, scholars at home and abroad have proposed a variety of vegetation information suppression methods for optical images, so as to better realize the extraction of spectral information such as rocks and soils, and then carry out related research on basic geology and soil properties, mainly including vegetation suppression technology based on mixed pixel decomposition, principal component analysis based on multiple vegetation indices, and soft leaf fall technology. Among them, the mixed pixel decomposition method requires sufficient prior knowledge of spectral data processing, and requires field collection of spectral data, which is limited in processing satellite optical images; the principal component analysis of vegetation index is cumbersome and labor-intensive; and soft leaf fall technology can only enhance specific information. In addition, in recent years, many scholars have explored and improved the vegetation suppression method of suppression-masking-forced invariance-histogram equalization. This method mainly achieves vegetation suppression by statistically fitting the scatter plot of vegetation index and reflectance of each band, and then flattens the segmented mean of the scatter plot fitting curve. However, this two-dimensional curve-based processing method cannot make full use of the spatial position relationship between image pixels, and it is difficult to obtain reliable vegetation suppression results.

[0004] Vegetation information suppression is crucial for research in remote sensing geology, soil properties and other fields. Convenient, efficient and reliable vegetation suppression processing will lay a good data foundation for subsequent research. Aiming at the defects of the suppression-mask-forced invariance-histogram equalization method, combined with the sparse and uneven vegetation coverage conditions in arid and semi-arid areas, the method of filtering the image of the high vegetation coverage area based on the pixel reflectance of the low vegetation coverage area of ​​each band image is used instead of filtering the two-dimensional curve to achieve vegetation information suppression in such areas. The processing process can make full use of the spatial position relationship between each pixel and obtain more impressive vegetation suppression results. Summary of the invention

[0005] In view of the limitations of the above-mentioned existing optical image vegetation information suppression methods, the purpose of the present invention is to provide a method and system for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas based on image filtering. On the one hand, it gets rid of the high requirements of the existing optical remote sensing image vegetation information suppression technology on spectral data processing experience and field measured spectral work; on the other hand, it solves the problems of insufficient utilization of image spatial information and low reliability of suppression results in the existing methods.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions to achieve the above problems:

[0007] A method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas, the method comprising:

[0008] Step 1: Collect optical remote sensing images of arid and semi-arid areas that need vegetation suppression treatment, pre-process the collected optical remote sensing images of each band, and obtain surface reflectance images of different bands;

[0009] Step 2: Use the pre-processed red light and near infrared band images to calculate the normalized vegetation index, and then calculate the vegetation coverage of the area to be processed based on the vegetation index;

[0010] Step 3: Construct a vegetation coverage judgment model and divide it into low and high vegetation coverage areas according to the specified vegetation coverage threshold;

[0011] Step 4: Combined with the vegetation coverage judgment model, with the pixel to be processed corresponding to the high vegetation coverage area as the center, search for the low vegetation coverage area according to the set step window until the number of pixels corresponding to the low vegetation coverage area in the window reaches the set number. The mean value of the image pixel to be processed corresponding to the low vegetation coverage area is used as the value of each central pixel to be processed corresponding to the high vegetation coverage area, and the vegetation information suppression result image corresponding to the image to be processed is obtained.

[0012] Furthermore, the preprocessing of the collected optical remote sensing images in each band in step 1 includes:

[0013] The collected optical original images are sequentially subjected to radiometric calibration, atmospheric correction, and orthorectification, and then projected and transformed into the target coordinate system to obtain the preprocessed surface reflectance images of each band.

[0014] The optical remote sensing images may be multispectral or hyperspectral images acquired by different platforms and different sensors.

[0015] The vegetation index calculation method in step 2 is as follows:

[0016] The normalized vegetation index NDVI of the area to be processed is calculated using the pre-processed red light and near-infrared band reflectance images.

[0017] Where: R NIR , R R Represent the spectral reflectance in the near-infrared and red light bands respectively.

[0018] The calculation method of vegetation coverage in step 2 is as follows:

[0019]

[0020] Among them, NDVI min When the minimum value of the confidence interval is taken, the corresponding vegetation index, NDVI max It is the vegetation index corresponding to the maximum value of the confidence interval.

[0021] The vegetation coverage judgment model in step three is a 0-1 matrix. The low and high vegetation coverage areas are divided according to the specified vegetation coverage threshold to construct a 0-1 matrix, in which the 0 value area corresponds to the high vegetation coverage area and the 1 value area corresponds to the low vegetation coverage area.

[0022] In more detail, step 4 of the present invention is:

[0023] Referring to the 0-1 matrix of the vegetation coverage judgment model, the image pixels of each spectral band corresponding to the 0-value area are processed pixel by pixel, and this is used as the central pixel to be processed. The 1 value corresponding to the 0-1 matrix is ​​searched according to the square window with a set step size until the number of 1-value pixels in the window reaches the specified number. The mean value of the image pixels to be processed corresponding to the 1 value is used as the value of each central pixel to be processed corresponding to the 0 value, thereby obtaining the vegetation information suppression result image corresponding to the image to be processed.

[0024] Step 4 also specifically includes:

[0025] Step 4.1, move the window to search for pixels in low vegetation coverage areas:

[0026] Process the image pixels of each band in the 0-1 matrix 0-value area one by one, and do not process the image area corresponding to the 1-value area. Use a 3×3 window to perform an initial search on the 0-1 matrix with each pixel to be processed in the 0-value area as the center. The window side length increases by a step of 2 until the number of 1-value pixels in the search window is not less than the specified number m2. Record the corresponding positions of the 1-value pixels in the image to be processed obtained by searching with each pixel to be processed as the center.

[0027] Step 4.2, pixel mean filtering in high vegetation coverage areas:

[0028] Calculate the pixel mean of the image to be processed corresponding to the 1-valued pixel searched with each pixel to be processed as the center in step 4.1, and obtain the pixel value of each pixel to be processed after the mean filtering;

[0029] Step 4.3, generate vegetation suppression result image:

[0030] The result image of vegetation information suppression in each band image is composed of the processed result of the image to be processed corresponding to the 0-value area in the 0-1 matrix and the original pixel of the image to be processed corresponding to the 1-value area.

[0031] The present invention also discloses an information system for a method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas, comprising an image loading and preprocessing module, characterized in that it also comprises: a vegetation coverage estimation module and a vegetation information suppression module, wherein the image loading and preprocessing module, the vegetation coverage estimation module and the vegetation information suppression module are sequentially connected.

[0032] The image loading and preprocessing module is used to collect optical remote sensing images of arid and semi-arid areas that need vegetation suppression treatment, and preprocess the collected optical remote sensing images of each band to obtain surface reflectance images of different bands;

[0033] The vegetation coverage estimation module is used to obtain the vegetation coverage of the area to be processed based on the vegetation index through normalization processing;

[0034] The vegetation information suppression module is used to realize vegetation information suppression based on mean filtering of images in low vegetation coverage areas.

[0035] In addition, the present invention may also be an electronic device, comprising a processor and a memory;

[0036] The memory is used for storing;

[0037] The processor is used to execute the method for suppressing vegetation information in optical remote sensing images of arid and semi-arid areas of the present invention by calling.

[0038] At the same time, the present invention can also be a computer program product, including a computer program and / or instructions, characterized in that when the computer program and / or instructions are executed by a processor, the method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas of the above-mentioned technical solution of the present invention is implemented.

[0039] Compared with the prior art, the present invention has the following technical effects:

[0040] (I) The present invention provides an effective method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas, which breaks the requirements of some existing algorithms for rich processing experience of spectral data and a large amount of field measured spectral data collection work, and has better operability.

[0041] (II) The vegetation information suppression method proposed in the present invention is oriented to image filtering. By searching for pixels adjacent to non-vegetation areas through a moving window of variable size, it can make full use of the reflectance information of adjacent pixels in areas with high vegetation coverage, thereby solving the problem of insufficient utilization of image spatial information and insufficient reliability of vegetation suppression results in the prior art methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a flow chart of the method for suppressing vegetation information in optical remote sensing images of the present invention;

[0043] Figure 2 Schematic diagram of the vegetation suppression process. DETAILED DESCRIPTION

[0044] Specific embodiments of the present invention are given below. It should be noted that the present invention is not limited to the following specific embodiments, and all equivalent changes made on the basis of the technical solution of this application fall within the protection scope of the present invention.

[0045] Optical images can be multispectral or hyperspectral images from different platforms and sensors, as well as optical combined images from different sensors and different bands.

[0046] The optical images to be processed must contain red light and near-infrared band image data that can be used to calculate vegetation coverage.

[0047] Embodiment 1:

[0048] A method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas based on image filtering, the method comprising:

[0049] Step 1: Collect optical remote sensing images of arid and semi-arid areas that need vegetation suppression treatment, pre-process the collected optical remote sensing images of each band, and obtain surface reflectance images of different bands;

[0050] The images used in this example are red light, near infrared, and shortwave infrared bands of Landsat 8 data of typical arid and semi-arid areas in Duolun County, Inner Mongolia in June 2020. The size of the image to be processed is 4438×3716. The vegetation coverage in the area is sparse and uneven, which meets the applicability requirements of the method proposed in the present invention to the geographical environmental conditions of the area to be processed.

[0051] Optical remote sensing image preprocessing:

[0052] The red, near-infrared and short-wave infrared bands of the collected Landsat 8 data were subjected to radiometric calibration, atmospheric correction and orthorectification in turn, and the surface reflectance data of each band after preprocessing in the WGS-84 coordinate system and UTM projection were obtained;

[0053] Step 2: Use the pre-processed red light and near infrared band images to calculate the normalized vegetation index, and then calculate the vegetation coverage of the area to be processed based on the vegetation index;

[0054] Step 2.1, vegetation index calculation:

[0055] The normalized vegetation index NDVI image of the area to be processed is calculated using the pre-processed Landsat 8 red and near-infrared band reflectance images. The calculation is shown in formula 1;

[0056]

[0057] In (Formula 1), R NIR , R R Represent the spectral reflectance in the near-infrared and red light bands respectively.

[0058] Step 2.2, vegetation coverage estimation:

[0059] Take the NDVI within the confidence range of 5%-95% to estimate the vegetation coverage. By statistically analyzing the cumulative probability distribution of the NDVI image in step 2.1, take the NDVI value of 0.1619 corresponding to 5% as the minimum NDVI min , the NDVI value corresponding to 95% is 0.4334, which is the maximum NDVI max , compare the NDVI value of each pixel with the NDVI min The difference is divided by NDVI max With NDVI min The difference result is taken as the vegetation coverage of each pixel, as shown in Formula 2.

[0060]

[0061] Step 3: Divide the low and high vegetation coverage areas according to the specified vegetation coverage threshold, and construct a 0-1 matrix, where the 0 value area corresponds to the high vegetation coverage area and the 1 value area corresponds to the low vegetation coverage area;

[0062] Step 3.1, construct a 0-1 matrix:

[0063] According to the vegetation coverage threshold m1 of 60%, a vegetation coverage judgment model 0-1 matrix is ​​constructed, and the high vegetation coverage area with a vegetation coverage greater than 60% is assigned a value of 0, and the low vegetation coverage area with a vegetation coverage less than or equal to 60% is assigned a value of 1.

[0064] Step 4: Refer to the 0-1 matrix to process the red, near-infrared, and short-wave infrared image pixels corresponding to the 0-value area pixel by pixel. With the pixel to be processed as the center, search for the 1 value corresponding to the 0-1 matrix in a square window with a step size of 2 until the number of 1-value pixels in the window reaches the specified number. The pixel value of the central pixel of the search window is processed by the mean filter of the image pixel to be processed corresponding to the searched 1-value area to obtain the vegetation information suppression result image corresponding to the image to be processed. Figure 2 Schematic diagram of the vegetation suppression process.

[0065] Step 4.1, move the window to search for pixels in low vegetation coverage areas:

[0066] Process the image pixels of each band in the 0-1 matrix 0-value area corresponding to each pixel pixel by pixel, and do not process the image area corresponding to the 1-value area. Use a 3×3 window to perform an initial search on the 0-1 matrix with each pixel to be processed in the 0-value area as the center, and increase the window side length by a step of 2 until the number of 1-value pixels in the search window is not less than m2. Then stop the window search for the current center pixel. In the embodiment, m2 is 1, and the corresponding position of the 1-value pixel obtained by searching with each pixel to be processed as the center in the image to be processed is recorded. Use the same variable window search with other 0-value pixels as the center to record the position of the 1-value pixel;

[0067] Step 4.2, pixel mean filtering in high vegetation coverage areas:

[0068] Calculate the pixel mean of the image to be processed corresponding to the 1-valued pixel searched with each pixel to be processed as the center in step 4.1, and obtain the pixel value of each pixel to be processed after the mean filtering;

[0069]

[0070] (Formula 3)

[0071] (Formula 3), R0 process is the spectral reflectance after mean filtering of the current 0-value pixel position to be processed; n represents the number of 1-value pixels searched by moving the variable window with the current 0-value pixel as the center, and n is the smallest integer greater than or equal to m2; R1 i The spectral reflectance of the original band image corresponding to the i-th 1-value area pixel searched by moving the variable window with the current 0-value pixel as the center.

[0072] Step 4.3, generate vegetation suppression result image:

[0073] The result of the mean filtering of the image corresponding to the 0-value area in the 0-1 matrix and the original pixel value of the image to be processed corresponding to the 1-value area together constitute the result image after the vegetation information of each band image is suppressed. Based on the overall technical solution of the present invention, the present invention also discloses a vegetation information suppression system for optical remote sensing images in arid and semi-arid areas, and the vegetation information suppression system includes an image loading and preprocessing module, a vegetation coverage estimation module, and a vegetation information suppression module;

[0074] The image loading and preprocessing module is used to load the multispectral or hyperspectral image to be processed and to perform optical image preprocessing;

[0075] The vegetation coverage estimation module is used to perform vegetation coverage estimation based on the normalized vegetation index;

[0076] The vegetation information suppression module is used to perform vegetation information suppression in high vegetation coverage areas based on mean filtering of images in low vegetation coverage areas.

[0077] The present invention also provides an electronic device, comprising a processor and a memory;

[0078] The memory is used for storing;

[0079] The processor is used to execute the method for suppressing vegetation information in optical remote sensing images of arid and semi-arid areas of the present invention by calling.

[0080] At the same time, the product protected by the present invention can also be a computer program product, including a computer program and / or instructions. When the computer program and / or instructions are executed by a processor, the method of suppressing vegetation information in optical remote sensing images of arid and semi-arid areas of the present invention is implemented.

[0081] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may adopt the form of a complete software embodiment, a complete hardware embodiment, or a combination of software and hardware embodiments. In addition, the present invention is in the form of a computer program product that can be implemented on one or more computer-usable storage media containing computer-usable program codes. The computer-usable storage medium includes, but is not limited to, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), disk memories, compact disc read-only memories (CD-ROM), optical memories, etc.

[0082] The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A system that specifies the functions of a box or multiple boxes.

[0083] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction system, which is implemented in the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0084] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they understand the basic creative concepts.

[0085] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention belong to the scope of the present invention and its equivalent technologies, the present invention is also intended to include these changes and variations.

Claims

1. A method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas, characterized in that: The method described is: Step 1: Collect optical remote sensing images of arid and semi-arid areas that need vegetation suppression treatment, pre-process the collected optical remote sensing images of each band, and obtain surface reflectance images of different bands; Step 2: Use the pre-processed red light and near infrared band images to calculate the normalized vegetation index, and then calculate the vegetation coverage of the area to be processed based on the vegetation index; Step 3: Construct a vegetation coverage judgment model and divide it into low and high vegetation coverage areas according to the specified vegetation coverage threshold; Step 4: Combined with the vegetation coverage judgment model, with the pixel to be processed corresponding to the high vegetation coverage area as the center, search for the low vegetation coverage area according to the set step window until the number of pixels corresponding to the low vegetation coverage area in the window reaches the set number. The mean value of the image pixel to be processed corresponding to the low vegetation coverage area is used as the value of each central pixel to be processed corresponding to the high vegetation coverage area, and the vegetation information suppression result image corresponding to the image to be processed is obtained.

2. The method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas according to claim 1, characterized in that: The preprocessing of the collected optical remote sensing images in each band in step 1 includes: The collected optical original images are sequentially subjected to radiometric calibration, atmospheric correction, and orthorectification, and then projected and transformed into the target coordinate system to obtain the preprocessed surface reflectance images of each band. The optical remote sensing images are multispectral and hyperspectral images acquired by different platforms and different sensors.

3. The method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas according to claim 1, characterized in that: The vegetation index calculation method in step 2 is as follows: The normalized vegetation index NDVI of the area to be processed is calculated using the pre-processed red light and near-infrared band reflectance images. Where: R NIR , R R Represent the spectral reflectance in the near-infrared and red light bands respectively.

4. The method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas according to claim 1, characterized in that: The calculation method of vegetation coverage in step 2 is as follows: Among them, NDVI min When the minimum value of the confidence interval is taken, the corresponding vegetation index, NDVI max It is the vegetation index corresponding to the maximum value of the confidence interval.

5. The method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas according to claim 1, characterized in that: The vegetation coverage judgment model in step three is a 0-1 matrix. Low and high vegetation coverage areas are divided according to the specified vegetation coverage threshold to construct a 0-1 matrix, in which the 0 value area corresponds to the high vegetation coverage area and the 1 value area corresponds to the low vegetation coverage area.

6. The method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas according to claim 5, characterized in that: The step four is: Referring to the 0-1 matrix of the vegetation coverage judgment model, the image pixels of each spectral band corresponding to the 0-value area are processed pixel by pixel, and this is used as the central pixel to be processed. The 1 value corresponding to the 0-1 matrix is ​​searched according to the square window with a set step size until the number of 1-value pixels in the window reaches the specified number. The mean value of the image pixels to be processed corresponding to the 1 value is used as the value of each central pixel to be processed corresponding to the 0 value, thereby obtaining the vegetation information suppression result image corresponding to the image to be processed.

7. The method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas according to claim 6, characterized in that: The step 4 specifically includes: Step 4.1, move the window to search for pixels in low vegetation coverage areas: Process the image pixels of each band in the 0-1 matrix 0-value area one by one, and do not process the image area corresponding to the 1-value area. Use a 3×3 window to perform an initial search on the 0-1 matrix with each pixel to be processed in the 0-value area as the center. The window side length increases by a step of 2 until the number of 1-value pixels in the search window is not less than the specified number m2. Record the corresponding positions of the 1-value pixels in the image to be processed obtained by searching with each pixel to be processed as the center. Step 4.2, pixel mean filtering in high vegetation coverage areas: Calculate the pixel mean of the image to be processed corresponding to the 1-valued pixel searched with each pixel to be processed as the center in step 4.1, and obtain the pixel value of each pixel to be processed after the mean filtering; Step 4.3, generate vegetation suppression result image: The result image of vegetation information suppression in each band image is composed of the processed result of the image to be processed corresponding to the 0-value area in the 0-1 matrix and the original pixel of the image to be processed corresponding to the 1-value area.

8. An information system for implementing the method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas as claimed in claims 1 to 7, comprising an image loading and preprocessing module, characterized in that It also includes: a vegetation coverage estimation module, a vegetation information suppression module, an image loading and preprocessing module, a vegetation coverage estimation module and a vegetation information suppression module which are connected in sequence. The image loading and preprocessing module is used to collect optical remote sensing images of arid and semi-arid areas that need vegetation suppression treatment, and preprocess the collected optical remote sensing images of each band to obtain surface reflectance images of different bands; The vegetation coverage estimation module is used to obtain the vegetation coverage of the area to be processed based on the vegetation index through normalization processing; The vegetation information suppression module is used to realize vegetation information suppression based on mean filtering of images in low vegetation coverage areas.

9. An electronic device, characterized in that: including a processor and a memory; The memory is used for storing; The processor is used to execute the method for suppressing vegetation information in optical remote sensing images in arid and semi-arid areas as described in any one of claims 1 to 7 by calling.

10. A computer program product comprising a computer program and / or instructions, characterized in that: When the computer program and / or instruction is executed by a processor, the method for suppressing vegetation information in optical remote sensing images of arid and semi-arid areas according to any one of claims 1 to 7 is implemented.

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