Patent Publication Number: US-2023146206-A1

Title: Image processing device, image processing method, and program

Description:
TECHNICAL FIELD 
     The present disclosure relates to an image processing device, an image processing method, and a program. More specifically, the present disclosure relates to an image processing device, an image processing method, and a program for determining the activity of a plant on the basis of a camera image. 
     BACKGROUND ART 
     There has been a technology of capturing an image of a variety of plants including crops, flowers, or trees with a camera mounted on a drone or the like, for example, and measuring the activity of each plant by analyzing the captured image. 
     One example of a vegetation index that indicates a plant activity is an NDVI (Normalized Difference Vegetation Index). 
     An NDVI of a plant included in a camera image is calculated through analysis of the camera image, whereby the activity of the plant in the image can be estimated. 
     It is to be noted that one example of a conventional technology about an NDVI which is a vegetation index indicating a plant activity is described in PTL 1 (PCT Patent Publication No. WO2018/034166). 
     For example, in a farm where trees, flowers, vegetables such as green onions, cabbages, Chinese cabbages, or spinaches, etc. are grown, plants to be grown are usually planted in fixed lines or lines where respective linear “ridges” are formed. 
     That is, cultivation is carried out while vegetation portion lines such as “ridges” on which plants to be grown are planted are formed at a fixed interval. 
     As a result, vegetation portion lines where plants to be grown are planted and soil portion lines where no plant is planted are alternately formed. 
     When vegetation portion lines are formed at an interval in the abovementioned manner, plants to be grown can be exposed to plenty of sunshine. Moreover, the soil portion lines can be used as walkways so that the related works are facilitated. Thus, there are many advantages. 
     However, if an image of a farm where vegetation portion lines and soil portion lines coexist is captured from above with a camera mounted on a drone or the like, the captured image includes the soil portion lines as well as the vegetation portion lines. 
     When an NDVI value which is a vegetation index value is calculated from this image, a process of calculating the NDVI value is based on pixel value data that includes pixel values of a part of the soil portion lines. This causes a problem that precise vegetation index values in vegetation portions only cannot be calculated. 
     CITATION LIST 
     Patent Literature 
     PTL 1 
     
         
         PCT Patent Publication No. WO2018/034166 
       
    
     SUMMARY 
     Technical Problem 
     The present disclosure has been made in view of the abovementioned problem, for example, and an object thereof is to provide an image processing device, an image processing method, and a program for, in a configuration of determining a plant activity on the basis of a camera image, precisely calculating a vegetation index which indicates a plant activity such as an NDVI value of a plant in a vegetation portion line on the basis of an image obtained by capturing a farm where the vegetation portion line and a soil portion line coexist. 
     When the configuration and processes according to the present disclosure are applied, the activity of a plant can be determined with high precision. 
     Solution to Problem 
     A first aspect of the present disclosure is an image processing device including a vegetation index value set image correcting section that receives an input of a vegetation index value set image in which a vegetation index value is set as a pixel value and that generates a corrected image of the vegetation index value set image, the vegetation index value indicating a plant activity, in which the vegetation index value set image correcting section calculates, for each of pixels constituting the vegetation index value set image, an average pixel value of the pixel and neighboring pixels, and generates an averaged image in which the calculated average pixel values are set, generates a binarized image by binarizing a difference image between the vegetation index value set image and the averaged image in accordance with a specified threshold, and generates, as the corrected image of the vegetation index value set image, a multiplication image by multiplying the vegetation index value set image and the binarized image. 
     Furthermore, a second aspect of the present disclosure is an image processing method that is executed in an image processing device. 
     The image processing device includes a vegetation index value set image correcting section that receives an input of a vegetation index value set image in which a vegetation index value indicating a plant activity is set as a pixel value and that generates a corrected image of the vegetation index value set image. The method includes causing the vegetation index value set image correcting section to calculate, for each of pixels constituting the vegetation index value set image, an average pixel value of the pixel and neighboring pixels, and generate an averaged image in which the calculated average pixel values are set, generate a binarized image by binarizing a difference image between the vegetation index value set image and the averaged image in accordance with a specified threshold, and generate, as the corrected image of the vegetation index value set image, a multiplication image by multiplying the vegetation index value set image and the binarized image. 
     Furthermore, a third aspect of the present disclosure is a program for causing an image processing device to execute image processing. 
     The image processing device includes a vegetation index value set image correcting section that receives an input of a vegetation index value set image in which a vegetation index value indicating a plant activity is set as a pixel value and that generates a corrected image of the vegetation index value set image. The program causes the vegetation index value set image correcting section to perform a process of calculating, for each of pixels constituting the vegetation index value set image, an average pixel value of the pixel and neighboring pixels, and generating an averaged image in which the calculated average pixel values are set, a process of generating a binarized image by binarizing a difference image between the vegetation index value set image and the averaged image in accordance with a specified threshold, and a process of generating, as the corrected image of the vegetation index value set image, a multiplication image by multiplying the vegetation index value set image and the binarized image. 
     It is to be noted that the program according to the present disclosure can be provided by a recording medium or communication medium for providing the program in a computer readable format to an information processing device or a computer system that is capable of executing various program codes, for example. Since the program is provided in a computer readable format, processing in accordance with the program is realized in the information processing device or the computer system. 
     Any other objects, features, and advantages of the present disclosure will become apparent from the detailed description based on an embodiment and attached drawings which are described later. It is to be noted that, in the present description, a system refers to a logical set structure including a plurality of devices, and the devices included in the structure are not necessarily included in the same casing. 
     According to the configuration of one embodiment of the present disclosure, a device and a method of generating and outputting a corrected image including a high-precision vegetation index value such as an NDVI value in a vegetation portion region on the basis of an image, in which the vegetation portion and a soil portion coexist, are implemented. 
     Specifically, the device includes a vegetation index value set image correcting section that generates a corrected image of a vegetation index value set image in which a vegetation index value such as an NDVI value is set as a pixel value, for example. The vegetation index value set image correcting section calculates, for each of pixels constituting the vegetation index value set image, an average pixel value of the pixel and neighboring pixels, generates an averaged image in which the average pixel value is set, generates a binarized image by binarizing a difference image between the vegetation index value set image and the averaged image in accordance with a specified threshold, and generates, as the corrected image of the vegetation index value set image, a multiplication image obtained by multiplying the vegetation index value set image and the binarized image. 
     With this configuration, the device and the method of generating and outputting a corrected image including a high-precision vegetation index value such as an NDVI value in a vegetation portion region on the basis of an image in which the vegetation portion and a soil portion coexist. 
     It is to be noted that the effects described in the present description are just examples, and thus, are not limited. In addition, any additional effect may be provided. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG.  1    is a diagram for explaining an example of capturing an image from above a farm. 
         FIG.  2    is a diagram for explaining a captured image of a farm and an NDVI image which is generated on the basis of the captured image. 
         FIG.  3    is a diagram for explaining problems in an NDVI image which is generated on the basis of a captured image of a farm. 
         FIG.  4    is a diagram for explaining problems in an NDVI image which is generated on the basis of a captured image of a farm. 
         FIG.  5    is a diagram for explaining problems in an NDVI image which is generated on the basis of a captured image of a farm. 
         FIG.  6    is a diagram for explaining problems in an NDVI image which is generated on the basis of a captured image of a farm. 
         FIG.  7    is a diagram for explaining the configuration and processes in an image processing device according to the present disclosure. 
         FIG.  8    is a diagram for explaining the configuration and processes in an NDVI image correcting section of the image processing device according to the present disclosure. 
         FIG.  9    is a diagram for explaining one example of an NDVI image which is an input image to the NDVI image correcting section. 
         FIG.  10    is a diagram for explaining the details of a process that is executed by an averaging section of the NDVI image correction section. 
         FIG.  11    is a diagram for explaining the details of a process that is executed by the averaging section of the NDVI image correction section. 
         FIG.  12    is a diagram for explaining the details of a process that is executed by the averaging section of the NDVI image correction section. 
         FIG.  13    is a diagram for explaining the details of a process that is executed by a subtraction section of the NDVI image correction section. 
         FIG.  14    is a diagram for explaining the details of a process that is executed by a binarization section of the NDVI image correction section. 
         FIG.  15    is a diagram for explaining the details of a process that is executed by a multiplication section of the NDVI image correction section. 
         FIG.  16    is a diagram for explaining the details of a process that is executed by a multiplication image averaging section of the NDVI image correction section. 
         FIG.  17    is a diagram for explaining the details of a process that is executed by the multiplication image averaging section of the NDVI image correction section. 
         FIG.  18    is a flowchart for explaining a detailed sequence of processes that are executed by the image processing device according to the present disclosure. 
         FIG.  19    is a diagram for explaining the details of a process that is executed by the NDVI image correction section of the image processing device according to the present disclosure. 
         FIG.  20    is a diagram for explaining a hardware configuration example of the image processing device according to the present disclosure. 
     
    
    
     DESCRIPTION OF EMBODIMENT 
     Hereinafter, an image processing device, an image processing method, and a program according to the present disclosure will be explained with reference to the drawings. It is to be noted that the explanation will be given in accordance with the following order. 
     1. Index (vegetation index) indicating activity of plant 
     2. Example of conventional process of calculating NDVI value which is activity index value of plant, and problems 
     3. Details of configuration and processes in image processing device according to present disclosure 
     3-1. Process that is executed by averaging section  121   
     3-2. Process that is executed by subtraction section  122   
     3-3. Process that is executed by binarization section  123   
     3-4. Process that is executed by multiplication section  124   
     3-5. Process that is executed by multiplication image averaging section  125   
     4. Sequence of processes that are executed by image processing device according to present disclosure 
     5. Hardware configuration example of image processing device 
     6. Conclusion of configuration according to present disclosure 
     1. Index (Vegetation Index) Indicating Activity of Plant 
     First, an index (vegetation index) that indicates the activity of a plant will be explained. 
     As previously explained, there has been a technology of capturing an image of a variety of plants including crops, flowers, and trees with a camera mounted on a drone or the like, for example, analyzing the captured image, and measuring the activity of each plant. 
     Examples of an index (vegetation index) that indicates the activity of a plant include an NDVI (Normalized Difference Vegetation Index). 
     In most cases, an NDVI is calculated in accordance with the following (Expression 1). 
       NDVI=( NIR−RED )/( NIR+RED )  (Expression 1)
 
     in the above (Expression 1), 
     RED (infrared) and NIR (near infrared) represent the intensity (pixel value) of a RED (infrared) wavelength (approximately 0.63 to 0.69 μm) and the intensity (pixel value) of an NIR (near infrared) wavelength (approximately 0.76 to 0.90 μm) in each pixel in an image captured by a camera (multi-spectral camera) that is capable of taking an image of two types of wavelengths of infrared rays and infrared rays simultaneously. 
     Pixel values which indicate the RED (infrared) intensity and the NIR (near infrared) intensity acquired from a camera image are obtained by measuring reflection light from a subject. 
     In plants, chlorophyll absorbs light of an infrared wavelength to perform photosynthesis, and light that cannot be absorbed is released as diffuse reflection from leaves. Therefore, it can be determined that a leaf that absorbs light of a reddish wavelength has a high activity. 
     For example, a camera  11  is mounted on a drone  10 , as depicted in  FIG.  1   , to capture an image of a farm from above. The camera  11  is a multi-spectral camera which simultaneously captures a RED wavelength (infrared) and an NRI wavelength (near infrared). 
     In the farm, trees, flowers, vegetables such as green onions, cabbages, Chinese cabbages, or spinaches, etc. are grown, for example. 
     As depicted in  FIG.  1   , plants to be grown are planted in fixed lines or vegetation portion lines along which respective linear “ridges” are formed, for example. 
     A plurality of vegetation portion lines is formed at a fixed interval. As a result of setting vegetation portion lines at a fixed interval in this manner, plants to be grown can be exposed to plenty of sunshine. Moreover, the related works can be facilitated. Thus, there are many advantages. 
     However, this generates a configuration in which vegetation portion lines where plants to be grown are planted and soil portion lines where no plant is planted are alternately arranged in the farm, as depicted in  FIG.  1   . 
     When an image of the farm where vegetation portion lines and soil portion lines coexist, as depicted in  FIG.  1   , is captured with the camera  11  mounted on the drone  10 , the vegetation portion lines and the soil portion lines coexist in the captured image. 
     When such an image is used to calculate an NDVI value which is a vegetation index value, an NDVI value calculating process based on pixel value data including pixel values of the soil portion lines is performed. Therefore, precise vegetation index values in the vegetation portions only cannot be calculated. 
       FIG.  2    depicts an example of (a) camera image and an example of (b) NDVI image. 
     NDVI values corresponding to pixels in the camera image in  FIG.  2 ( a )  are calculated according to the abovementioned Expression (1). That is, 
       NDVI=( NIR−RED )/( NIR+RED )  (Expression 1)
 
     NDVI values corresponding to the pixels are calculated according to Expression (1). 
     One example of an image that is generated on the basis of the calculation result is (b) NDVI image in  FIG.  2   . 
     Pixel values that are set for the respective pixels in the NDVI image correspond to NDVI values. 
     Each NDVI value is set to NDVI=0.0 to 1.0, for example. Each white portion (high-intensity portion) in the (b) NDVI image in  FIG.  2    indicates a region having a high NDVI value (close to 1.0) and having a high plant activity. 
     Each black portion (low-intensity portion) in the (b) NDVI image in  FIG.  2    indicates a region having a low NDVI value (close to 0.0) and having a low plant activity. 
     However, black portions (low-intensity portions) in the (b) NDVI image in  FIG.  2    include soil portions where no plant to be grown is planted. Therefore, precise activity index values in the vegetation portions only cannot be obtained by calculating, for example, the total average value of pixel values (NDVI values) in this image. 
     2. Example of Conventional Process of Calculating NDVI Value which is Activity Index Value of Plant, and Problems 
     Next, an example of a conventional process of calculating an NDVI value which is a plant activity index value and problems thereof will be explained with reference to the drawings in  FIG.  3    and later. 
       FIG.  3    is a diagram depicting an example of capturing an image of a farm where vegetation portion lines and soil portion lines coexist, from above with the camera  11  mounted on the drone  10 , in the similar manner as that in  FIG.  1    which has been previously explained. 
     It is assumed that a portion of the farm is a poor growth region  20 , as depicted in  FIG.  3   . 
     When an NDVI image is generated from a captured image of the farm including the poor growth region  20 , an image region, in the NDVI image, corresponding to the poor growth region  20  is a low-intensity image region where a pixel value (NDVI value) is low, as depicted in  FIG.  4   . 
     It is to be noted that, in the NDVI image in  FIG.  4   , high-intensity (white) lines correspond to the vegetation portion lines while low-intensity (gray-black) lines correspond to the soil portion lines. 
     It is to be noted that, for easy understanding of the explanation, NDVI images in  FIG.  4    and later are schematic images in which vegetation portion lines are indicated by high-intensity (white) lines while soil portion lines are indicated by low-intensity (gray-black) lines such that the vegetation portion lines and the soil portion lines are clearly distinguished from each other. In an actual captured image, a boundary between lines is ambiguous. Hereinafter, in order to make it easy to understand processes according to the present disclosure, a schematic NDVI image in which a boundary between lines is clearly illustrated. 
     As depicted in  FIG.  4   , in an NDVI image that is generated on the basis of a captured image of a farm where vegetation portion lines and soil portion lines coexist, NDVI values of the vegetation portion lines and NDVI values of the soil portion lines coexist. Therefore, for example, even when the total average value of pixel values (NDVI values) in this image is calculated, precise activity index values (NDVI values) in the vegetation portions only cannot be obtained. 
     An example of a conventional process of calculating activity index values (NDVI values) of vegetation portions only on the basis of such an image will be explained with reference to  FIG.  5    and later. 
     In  FIG.  5   , (1) depicts an NDVI image including the poor growth region  20 , which is similar to that previously explained with reference to  FIG.  4   . 
     First, a histogram of pixel values (NDVI values) of all the pixels in the NDVI image is created. 
     In  FIG.  5   , (2) is a histogram of pixel values (NDVI values) of all the pixels in the (1) NDVI image in  FIG.  5   . 
     The (2) histogram in  FIG.  5    is a graph the horizontal axis of which indicates an NDVI value (0 to 1.0) and the vertical axis of which indicates the number of pixels. 
     A curve indicated by a solid line in the graph in (2) of  FIG.  5    is a “pixel value distribution curve (measured value) corresponding to the NDVI values,” that is, is a “histogram.” 
     As depicted in (2) of  FIG.  5   , the pixel value distribution curve has two peaks. It is inferred that the right peak, which is a large peak having a higher NDVI value, is a peak indicating a distribution of NDVI values of pixels corresponding to the vegetation portion lines. 
     On the other hand, it is inferred that the left peak, which is a small peak having a lower NDVI value, is a peak indicating a distribution of NDVI values of pixels corresponding to the soil portion lines. 
     On the basis of a result of this inference, a threshold, that is, 
     an “estimated threshold (NDVI value=0.4) between a vegetation portion and a soil portion” is defined, as illustrated in (2) of  FIG.  5   . 
     As illustrated in (2) of  FIG.  5   , an estimated distribution curve (estimated vegetation portion distribution curve) of the NDVI values of pixels corresponding to vegetation portions is added to the lower left region of the large peak having the higher NDVI value. 
     Furthermore, as illustrated in (2) of  FIG.  5   , an estimated distribution curve (estimated soil portion distribution curve) of the NDVI values of pixels corresponding to soil portions is added to the lower right region of the small peak having the lower NDVI value. 
     An intersection point (NDVI value=0.4) of these estimated distribution curves is obtained, and the intersection point (NDVI value=0.4) is defined as an “estimated threshold (NDVI value=0.4) between a vegetation portion and a soil portion.” 
     The estimated threshold is used to discriminate between a vegetation portion and a soil portion included in the (1) NDVI image in  FIG.  5   . 
     Specifically, a region having a pixel value (NDVI value) equal to the threshold=0.4 or greater is determined as a vegetation portion, and a region having a pixel value of less than the threshold=0.4 is determined as a soil portion. 
     Only a vegetation portion selected as a result of this determination, or a region determined as a vegetation portion having a pixel value equal to the threshold=0.4 or greater is regarded as a target the plant activity index value (NDVI value) of which is to be analyzed. 
     As a result of the region determination using this “threshold,” regions each having a pixel value of the threshold=less than 0.4 are determined as solid portions so that these regions can be excluded from targets the plant activity index value (NDVI value) of which are to be calculated. 
     However, when the region determination using the “threshold” is made, there is a possibility that the poor growth region  20  included in the (1) NDVI image in  FIG.  5    is determined as a soil portion region. 
     A specific example thereof will be explained with reference to  FIG.  6   . 
     (1) NDVI image in  FIG.  6    is identical to (1) NDVI image in  FIG.  5   . That is, (1) in  FIG.  6    depicts an NDVI image including the poor growth region  20  which is similar to that previously explained with reference to  FIG.  4   . 
     (2) in  FIG.  6    depicts a graph indicating the NDVI value of a lowermost pixel line AB in the (1) NDVI image in  FIG.  6   . 
     The horizontal axis indicates the pixel position on the pixel line AB. The vertical axis indicates the NDVI value of each pixel. 
     As illustrated in the graph, the NDVI value of the pixel line AB forms a curve having a plurality of peaks and valleys formed at a fixed interval. 
     High NDVI value portions (peak portions) and low NDVI value portions (valley portions) correspond to vegetation portions and soil portions, respectively. 
     It is assumed that, by using the “estimated threshold (NDVI value=0.4) between a vegetation portion and a soil portion” which has been explained with reference to  FIG.  5   , a process for discriminating between vegetation portions and soil portions is performed on the graph in (2) of  FIG.  6   . 
     A dotted line substantially at the center of the graph in (2) of  FIG.  6    is a line indicating the estimated threshold (NDVI value=0.4). 
     A region having an NDVI value higher than the estimated threshold (NDVI value=0.4) is determined as a vegetation portion region while a region having an NDVI value lower than the estimated threshold is determined as a soil portion region. 
     However, as illustrated in (2) of  FIG.  6   , a CD portion in (2) of  FIG.  6    corresponding to the poor growth region  20  has low peaks. The peaks in the CD portion correspond to vegetation portions, but are determined as soil portion regions because these peaks each have an NDVI value that is lower than the estimated threshold (NDVI value=0.4). 
     Therefore, when the region determination using the “estimated threshold” is made, a problem that a vegetation portion including a poor growth region is erroneously determined as a soil portion arises. 
     3. Details of Configuration and Processes in Image Processing Device According to Present Disclosure 
     Next, the details of the configuration and processes in an image processing device according to the present disclosure will be explained. 
     An image processing device according to the present disclosure is capable of solving the abovementioned problems and determining a plant activity with high precision. 
     That is, an image processing device according to the present disclosure is capable of precisely calculating a vegetation index which indicate a plant activity such as an NDVI value in a vegetation portion line on the basis of an image obtained by capturing a farm where vegetation portion lines and soil portion lines coexist. 
     When the configuration and processes according to the present disclosure are applied, a plant activity can be determined with high precision. 
     The details of the configuration and processes in an image processing device according to the present disclosure will be explained with reference to  FIG.  7    and later. 
       FIG.  7    is a diagram depicting a configuration example of an image processing device  100  according to the present disclosure. 
     As depicted in  FIG.  7   , the image processing device  100  according to the present disclosure includes an NDVI image generating section  101 , an NDVI image correcting section  102 , and an image displaying section  103 . 
     The NDVI image generating section  101  receives an input of a captured image  51 , and generates an NDVI image  52 . 
     The captured image  51  is captured by the camera  11  mounted on the drone  10  depicted in  FIG.  1   , for example. 
     The camera  11  is a multi-spectral camera. From the captured image  51 , the intensity (pixel value) of an RED (infrared) wavelength (approximately 0.63 to 0.69 μm) and the intensity of an NIR (near infrared) wavelength (approximately 0.76 to 0.90 μm) in each pixel can be acquired. 
     The captured image  51  is inputted to the NDVI image generating section  101 , and the NDVI image generating section  101  calculates the NDVI value of each pixel in the captured image  51  according to the abovementioned (Expression 1), that is, 
       NDVI=( NIR−RED )/( NIR+RED )  (Expression 1),
 
     in which RED (infrared) and NIR (near infrared) represent the intensity (pixel value) of a RED (infrared) wavelength (approximately 0.63 to 0.69 μm) and the intensity of an NIR (near infrared) wavelength (approximately 0.76 to 0.90 μm), respectively. 
     The NDVI image generating section  101  calculates the NDVI values of respective pixels in the captured image  51 , and generates the NDVI image  52  in which the calculated pixel values (NDVI values) are set in respective pixels. 
     The NDVI image  52  is similar to the (1) NDVI image in  FIG.  5    or the (1) NDVI image in  FIG.  6   , for example. 
     As previously explained, the NDVI value is set to NDVI=0.0 to 1.0, for example. In the (1) NDVI image in  FIG.  5    or  FIG.  6   , each white portion (high-intensity portion) indicates a region having a high NDVI value (close to 1.0), that is, a region having a high plant activity, and each black portion (low-intensity portion) indicates a region having a low NDVI value (close to 0.0), that is, a region having a low plant activity or being a soil portion region. 
     The NDVI image  52  generated by the NDVI image generating section  101  is inputted to the NDVI image correcting section  102 . 
     The NDVI image correcting section  102  corrects the NDVI image  52  generated by the NDVI image generating section  101 . 
     Specifically, an output image (corrected NDVI image)  53  in which a region assessed as a soil portion can be clearly distinguished from a region assessed as a vegetation portion included in the NDVI image  52  is generated, for example. 
     Alternatively, NDVI values in regions assessed as soil portions are eliminated, and an output image (corrected NDVI image)  53  which includes NDVI values in regions assessed as vegetation portions only, is generated. 
     The details of an image correcting process that is executed by the NDVI image correcting section  102  will be explained later. 
     The output image (corrected NDVI image)  53  generated by the NDVI image correcting section  102  is outputted to the image displaying section  103 , and is displayed. 
     The output image (corrected NDVI image)  53  which is displayed on the image displaying section  103  is either 
     (a) an output image (corrected NDVI image) in which regions assessed as soil portions and regions assessed as vegetation portions are clearly distinguishable from each other, or 
     (b) an output image (corrected NDVI image) from which NDVI values in regions assessed as soil portions have been eliminated, and which includes NDVI values in regions assessed as vegetation portions only. 
     On the basis of either of the image (a) or (b) and the output image (corrected NDVI image)  53 , the plant activity in each vegetation portion region can be precisely discerned. 
     It is to be noted that, in an embodiment which will be explained later, the image processing device  100  according to the present disclosure uses an “NDVI” as a vegetation index value to indicate an activity of a plant. However, this embodiment is one example, and the image processing device  100  according to the present disclosure can use a vegetation index value other than an “NDVI,” as a vegetation index value to indicate an activity of a plant. 
     That is, an NDVI image is one example of the vegetation index value set image. 
     In addition, the NDVI image generating section  101  of the image processing device  100  depicted in  FIG.  7    is one example of a vegetation index value set image generating section, and the NDVI image correcting section  102  is one example of a vegetation index value set image correcting section. 
     Hereinafter, an embodiment in which “NDVI” is used as a representative example of a vegetation index value will be explained. 
     The detailed configuration and process in the NDVI image correcting section  102  of the image processing device  100  depicted in  FIG.  7    will be explained with reference to  FIG.  8    and later. 
       FIG.  8    is a block diagram depicting the detailed configuration of the NDVI image correcting section  102  of the image processing device  100  depicted in  FIG.  7   . 
     As depicted in  FIG.  8   , the NDVI image correcting section  102  of the image processing device  100  includes an averaging section  121 , a subtraction section  122 , a binarization section  123 , a multiplication section  124 , and a multiplication image averaging section  125 . 
     It is to be noted that the multiplication image averaging section  125  is optional, and the multiplication image averaging section  125  may be omitted. 
     Hereinafter, the details of processes that are executed by these sections will be explained in order. 
     (3-1. Process that is Executed by Averaging Section  121 ) 
     First, a process that is executed by the averaging section  121  will be explained. 
     The NDVI image  52  generated by the NDVI image generating section  101  is inputted to the averaging section  121  of the NDVI image correcting section  102 , and the averaging section  121  generates an averaged image of the inputted NDVI image  52 . 
       FIG.  9    is a diagram depicting a specific example of the NDVI image  52  that is inputted to the averaging section  121 , that is, the NDVI image  52  generated by the NDVI image generating section  101  disposed on a stage prior to the averaging section  121 . 
     (1a) in  FIG.  9    depicts an NDVI image that is similar to that previously explained with reference to (1) in  FIG.  6   . 
     That is, the (1a) NDVI image in  FIG.  9    is obtained by capturing a farm including the poor growth region  20  which has been explained with reference to  FIG.  3   , and is identical to those in  FIG.  4   , (1) of  FIG.  5   , and (1) of  FIG.  6   . That is, an NDVI image in which a low pixel value (NDVI value) is set in a portion corresponding to the poor growth region  20 , is depicted. 
     (1b) in  FIG.  9    is a graph that is similar to that previously explained with reference to (2) in  FIG.  6   , and illustrates an NDVI value of the lowermost pixel line AB in the (1a) NDVI image in  FIG.  9   . 
     The horizontal axis indicates the pixel position on the pixel line AB. The vertical axis indicates an NDVI value of each pixel. 
     The graph in (1b) in  FIG.  9    is identical to that previously explained with reference to (2) in  FIG.  6   . In this graph, the NDVI value of the pixel line AB forms a curve having a plurality of peaks and valleys formed at a fixed interval. Portions (peak portions) where the NDVI value is high correspond to vegetation portions while portions (valley portions) where the NDVI value is low correspond to soil portions. 
     For example, the (1a) NDVI image  52  in  FIG.  9    is inputted to the averaging section  121 , and the averaging section  121  executes an averaging process thereon. 
     A specific example of the averaging process that is executed by the averaging section  121  will be explained with reference to  FIG.  10   . 
       FIG.  10    depicts the NDVI image  52  which is to be subjected to the averaging process. 
     First, the averaging section  121  acquires a vegetation portion direction  71  and a vegetation portion interval  72  from the NDVI image  52  which is a target to be subjected to the averaging process. In the example depicted in  FIG.  10   , the vegetation portion direction  71  is an up-down direction in the drawing. 
     It is to be noted that the vegetation portion direction  71  and the vegetation portion interval  72  are acquired through image analysis of the NDVI image  52  which is a target to be subjected to the averaging process. However, a user may confirm the image and input the vegetation portion direction  71  and the vegetation portion interval  72 . Alternatively, the vegetation portion direction  71  and the vegetation portion interval  72  may be acquired with reference to a preset sketch of the farm. 
     In a certain farm, a vegetation portion direction and a vegetation portion interval vary in each region in some cases. In such a case, vegetation portion directions and vegetation portion intervals in respective regions may be acquired, and then, a process explained below may be performed for each region. 
     Next, the averaging section  121  executes an averaging process on pixel values (NDVI values) set for respective pixels in the NDVI image  52  on the basis of the acquired vegetation portion direction  71  and the acquired vegetation portion interval  72 . 
     The averaging process is performed for each pixel in the NDVI image  52 . A process to be performed on a process target pixel  81  in  FIG.  10    will be explained. For the process target pixel  81 , a plurality of pixels, which is arranged in a direction perpendicular to the vegetation portion direction  71  and is disposed within the vegetation portion interval  72  in which the process target pixel  81  is disposed at the center, is selected, and the averaging process is performed on the pixel values (NDVI values) of the selected pixels. 
     Each vegetation portion interval  72  includes pixels of one vegetation portion line and pixels of one soil portion line. Therefore, an average pixel value of the pixels included in a certain vegetation portion interval  72  is a local average value of a vegetation portion and a soil portion. 
     The averaging section  121  performs the pixel-based averaging process on each of all the pixels constituting the NDVI image  52 . That is, the pixel-based averaging process is performed while the process target pixel is sequentially changed from the upper left end to the lower right end in the NDVI image  52 . Through what is called a moving average pixel value calculating process, the average pixel value of each of the pixels is calculated. 
     It is to be noted that, for a region where pixels cannot be selected in a vegetation portion interval centered on a process target pixel because the process target pixel is in an end region of the image, the process target pixel  81  is not set at the center, and pixels disposed in a range which includes the process target pixel  81 , pixels corresponding to one vegetation portion line, and pixels corresponding to one soil portion line, are selected as averaging target pixels, as depicted in  FIG.  11   , for example, and the averaging process is performed thereon. 
     In the abovementioned manner, an average pixel value of the pixel values (NDVI values) of a plurality of pixels that is arranged in a direction perpendicular to the vegetation portion direction and is disposed within a vegetation portion interval with respect to the process target pixel is calculated, and the calculated pixel value is set as a pixel value of the process target pixel. 
     The averaging section  121  executes this process on each of all the pixels in the NDVI image  52  to generate an averaged image. 
       FIG.  12    depicts an example of the averaged image which is generated as a result of the averaging process. 
     (2a) of  FIG.  12    illustrates an averaged image which is generated as a result of the abovementioned averaging process performed on the NDVI image  52 . 
     It is to be noted that (2b) of  FIG.  12    indicates the NDVI value or the average pixel value (average NDVI value) of the lowermost pixel line AB in the (2a) averaged image in  FIG.  12   , for reference. The horizontal axis indicates the pixel position on the pixel line AB. The vertical axis indicates the NDVI value of each pixel. 
     A graph indicated by a solid line indicates the average pixel value (average NDVI value). 
     A dotted line indicates an NDVI value in the inputted original NDVI image  52  before executing the averaging process. 
     (3-2. Process that is Executed by Subtraction Section  122 ) 
     Next, a process that is executed by the subtraction section  122  will be explained. 
     The following two images are inputted to the subtraction section  122 . 
     (1) the inputted original NDVI image  52  before executing the averaging process, and 
     (2) the averaged image (=(2a) averaged image in  FIG.  12   ) generated by the averaging section  121   
     By using the two inputted images, the subtraction section  122  subtracts a pixel value in the averaged image from a pixel value in the inputted original NDVI image  52 . 
     That is, the pixel value of a pixel in the averaged image is subtracted from the pixel value of the corresponding pixel in the inputted original NDVI image  52 , and a difference image including pixel values obtained as the subtraction result is generated. 
     A differential pixel value (differential NDVI value) which is the pixel value of each pixel constituting the difference image is as follows. 
       Differential pixel value (differential NDVI value) in the difference image=(pixel value (NDVI value) in the inputted NDVI image)−(average pixel value (average NDVI value) in the averaged image)
 
     The subtraction section  122  performs the above subtraction process on each of all the pixels in the inputted NDVI image  52 , and generates a difference image including differential pixel values (differential NDVI values) obtained as the subtraction result. 
       FIG.  13    depicts an example of the difference image that is generated as a result of the subtraction process at the subtraction section  122 . 
     (3a) of  FIG.  13    depicts a difference image that is generated as a result of the abovementioned subtraction process. 
     A differential pixel value (differential NDVI value) that is the pixel value of each pixel constituting the difference image is as follows. 
       Differential pixel value (differential NDVI value) in the difference image=(pixel value (NDVI value) in the inputted NDVI image)−(average pixel value (average NDVI value) in the averaged image)
 
     It is to be noted that (3b) of  FIG.  13    illustrates an NDVI value or a differential pixel value (differential NDVI value) of the lowermost pixel line AB in the (3a) difference image in  FIG.  13   , for reference. The horizontal axis indicates a pixel position on the pixel line AB. The vertical axis indicates the NDVI value of each pixel. 
     A graph indicated by a solid line indicates a differential pixel value (differential NDVI value) in the difference image. 
     A dotted line indicates an NDVI value in the inputted original NDVI image  52 . 
     As depicted in (3b) of  FIG.  13   , the NDVI value in the inputted original NDVI image  52  ranges from 0 to 1.0 while the differential pixel value (differential NDVI value) in the difference image ranges from a minus value to a plus value with “0” interposed therebetween. 
     (3-3. Process that is Executed by Binarization section  123 ) 
     Next, a process that is executed by the binarization section  123  will be explained. 
     The binarization section  123  binarizes the pixel values or the differential pixel values (differential NDVI values) of the pixels constituting the difference image (=the (3a) difference image in  FIG.  13   ) generated by the subtraction section  122 . 
     The binarization section  123  binarizes the pixel values of the pixels constituting the difference image (=(3a) difference image in  FIG.  13   ) generated by the subtraction section  122 . That is, a pixel value=1 is set for a differential pixel value (differential NDVI value) that is positive (plus), and a pixel value=0 is set for a differential pixel value that is equal to 0 or is negative (minus). 
     That is, the binarization section  123  binarizes the differential pixel values (differential NDVI values) of the pixels constituting the difference image (=(3a) difference image in  FIG.  13   ) generated by the subtraction section  122 , and generates a binarized image including binarized pixel values (binarized NDVI values) which are 0 or 1. 
       FIG.  14    illustrates an example of a binarized image that is generated as a result of the binarization process at the binarization section  123 . 
     (4a) in  FIG.  14    depicts a binarized image that is generated as a result of the abovementioned binarization process. 
     The binarized pixel values (binarized NDVI values) which are the pixel values of the pixels constituting the binarized image are 0 or 1. 
     That is, in the binarized image, a pixel value=1 is set in a case where a corresponding pixel in the difference image (=(3a) difference image in  FIG.  13   ) generated by the subtraction section  122  has a differential pixel value (differential NDVI value) that is positive (plus), and a pixel value=0 is set in a case where a corresponding pixel in the difference image has a differential pixel value is equal to 0 or is negative (minus). 
     It is to be noted that (4b) in  FIG.  14    illustrates the NDVI value, that is, a binarized pixel value (binarized NDVI value) of the lowermost pixel line AB of the (4a) binarized image in  FIG.  14   , for reference. The horizontal axis indicates a pixel position on the pixel line AB. The vertical axis indicates the NDVI value of each pixel. 
     A graph indicated by a solid line indicates a binarized pixel value (binarized NDVI value) in the binarized image. 
     A dotted line indicates an NDVI value in the inputted original NDVI image  52 . 
     As illustrated in (4b) of  FIG.  14   , a binarized pixel value (binarized NDVI value) in the binarized image is 0 or 1. 
     In the binarized image generated by the binarization section  123 , a portion where the binarized pixel value (binarized NDVI value)=1 can be assessed as a vegetation portion. On the other hand, a portion where the binarized pixel value (binarized NDVI value)=0 can be assessed as a soil portion. 
     It is to be noted that the process example, in which the binarization section  123  generates a binarized image in which a pixel value=1 is set in a case where a corresponding differential pixel value (differential NDVI value) in the difference image is positive (plus), and a pixel value=0 is set in a case where a corresponding differential pixel value in the difference image is equal to 0 or is negative (minus), has been explained. That is, an example of the binarization process using a threshold=0 has been explained. 
     The binarization section  123  may perform a process other than the above process. For example, the binarization section  123  may perform binarization using, as the threshold, a value other than “0” such as threshold=0.1, threshold=0.2, or threshold=−0.1. 
     (3-4. Process that is Executed by Multiplication Section  124 ) 
     Next, a process that is executed by the multiplication section  124  will be explained. 
     The following two images are inputted to the multiplication section  124 . 
     (1) the inputted original NDVI image  52 , and 
     (2) the binarized image generated by the binarization section  123  (=(4a) binarized image in  FIG.  14   ) 
     By using these two inputted images, the multiplication section  124  multiplies the pixel values in the inputted NDVI image  52  with the corresponding pixel values in the binarized image. 
     That is, the pixel value of a pixel in the input NDVI image  52  is multiplied with the pixel value of the corresponding pixel in the binarized image, and a multiplication image including pixel values obtained as the multiplication result is generated. 
     A multiplication pixel value (multiplication NDVI value) which is a pixel value of each pixel constituting the multiplication image is as follows. 
       Multiplication pixel value (multiplication NDVI value) in the multiplication image=(pixel value (NDVI value) in the inputted NDVI image)×(binarized pixel value (binarized NDVI value) in the binarized image)
 
     The multiplication section  124  performs the abovementioned multiplication process on each of all the pixels in the inputted NDVI image  52 , and generates a multiplication image including multiplication pixel values (multiplication NDVI values) obtained as the multiplication result. 
       FIG.  15    depicts an example of a multiplication image that is generated as a result of the multiplication process at the multiplication section  124 . 
     (5a) in  FIG.  15    depicts a multiplication image that is generated as a result of the abovementioned multiplication process. 
     A multiplication pixel value (multiplication NDVI value) which is the pixel value of each pixel constituting the multiplication image is as follows. 
       Multiplication pixel value (multiplication NDVI value) in the multiplication image=(pixel value (NDVI value) in the inputted NDVI image)×(binarized pixel value (binarized NDVI value) in the binarized image)
 
     It is to be noted that (5b) in  FIG.  15    illustrates an NDVI value, that is, the multiplication pixel value (multiplication NDVI value) of the lowermost pixel line AB in the (5a) multiplication image in  FIG.  15   , for reference. The horizontal axis indicates a pixel position on the pixel line AB. The vertical axis indicates the NDVI value of each pixel. 
     A graph indicated by a solid line indicates a multiplication pixel value (multiplication NDVI value) in the multiplication image. 
     A dotted line indicates an NDVI value in the inputted original NDVI image  52 . 
     As illustrated in (5b) of  FIG.  15   , a multiplication pixel value (multiplication NDVI value) in the multiplication image indicated by a solid line reflects a pixel value (NDVI value) of a peak portion (=vegetation portion) in the inputted original NDVI image  52  indicated by a dotted line, and a pixel value of 0 is set in a valley portion (soil portion). 
     That is, regarding each vegetation portion in the multiplication image, a pixel value (NDVI value) in the inputted original NDVI image  52  is reflected. Regarding each soil portion in the multiplication image, a pixel value (NDVI value)=0 is uniformly set. 
     Regarding the poor growth region CD portion, a pixel value (NDVI value) in the inputted original NDVI image  52  is also reflected in a multiplication pixel value (multiplication NDVI value) in the multiplication image, as is clear from the graph illustrated in (5b) of  FIG.  15   . 
     The (5a) multiplication image in  FIG.  15    is outputted as the output image (corrected NDVI image)  53  depicted in  FIGS.  7  and  8    to the image displaying section  103 , and is displayed. 
     In the (5a) multiplication image in  FIG.  15   , all the pixel values (NDVI values) in each soil portion are uniformly set to 0 (black which indicates the minimum pixel value). A user (image observer) can easily discern that the black regions indicate soil portions while non-black regions indicate vegetation portions. 
     Furthermore, if the pixel value (NDVI value) setting states in the non-black regions are observed, the plant activities in the respective regions can be analyzed. 
     In addition, a user (image observer) can confirm that, in the CD region on the lower right side of the (5a) multiplication image in  FIG.  15   , the regions other than the 0 (black which indicates the minimum pixel value) regions indicate vegetation regions and that these vegetation regions in the CD region each have a lower pixel value (NDVI value) and a lower plant activity than those in the other vegetation regions. 
     It is to be noted that the (5a) multiplication image in  FIG.  15    may be outputted as the output image (corrected NDVI image)  53  to the image displaying section  103 , and may be displayed. However, the multiplication image may be further outputted to the multiplication image averaging section  125  depicted in  FIG.  8   , an averaged multiplication image may be generated at the multiplication image averaging section  125 , and the generated image may be used as the output image (corrected NDVI image)  53 . 
     (3-5. Process that is Executed by Multiplication Image Averaging Section  125 ) 
     Next, a process that is executed by the multiplication image averaging section  125  will be explained. 
     A process at the multiplication image averaging section  125  is not required but optional, as previously explained. 
     The multiplication image averaging section  125  performs the averaging process on the multiplication image generated by the multiplication section  124 , generates an averaged multiplication image, and outputs the generated image as the output image (corrected NDVI image)  53  to the image displaying section  103 . 
     A process that is executed by the multiplication image averaging section  125  will be explained with reference to  FIG.  16   . 
       FIG.  16    illustrates a (5a) multiplication image. 
     This is a multiplication image that is generated by the multiplication section  124 . 
     The multiplication image averaging section  125  performs the averaging process on the (5a) multiplication image excluding pixel values (NDVI pixel values)=0 in soil regions. 
     It is to be noted that pixel values (NDVI values)=0 are set in all the soil portion regions in the (5a) multiplication image. The multiplication image averaging section  125  performs the averaging process on regions excluding the soil regions where a pixel value=0 is set. 
     Specifically, the following process of calculating an average pixel value is performed for each pixel in the (5a) multiplication image. 
       Average pixel value=(total pixel value in the averaging process range)/(the number of pixels having a pixel value&gt;0 in the averaging process range) 
     A specific process sequence will be explained. First, the multiplication image averaging section  125  acquires the vegetation portion direction  71  and the vegetation portion interval  72  from the (5a) multiplication image in  FIG.  16   . In the example depicted in  FIG.  16   , the vegetation portion direction  71  corresponds to the up-down direction in the drawing. 
     Next, the multiplication image averaging section  125  performs the averaging process on the pixel values (NDVI values) set for respective pixels in the (5a) multiplication image in  FIG.  16    on the basis of the acquired vegetation portion direction  71  and the acquired vegetation portion interval  72 . 
     A process that is performed on a process target pixel  91  in (5a) of  FIG.  16    will be explained. For the process target pixel  91 , a plurality of pixels that is arranged in a direction perpendicular to the vegetation portion direction  71  and included in the vegetation portion interval  72  centered on the process target pixel  91  are selected, and the averaging process is performed on the pixel values (multiplication pixel values (multiplication NDVI values)) of the selected pixels. 
     The average pixel value which is obtained by the averaging process is calculated in accordance with the following expression, as previously explained. 
       Average pixel value=(total pixel values of the pixels in the averaging process range)/(the number of pixels having a pixel value&gt;0 in the averaging process range) 
     This pixel-based averaging process is performed on each of all the pixels constituting the (5a) multiplication image in  FIG.  16   . That is, the pixel-based averaging process is performed while a process target pixel is sequentially changed from the upper left end to the lower right end of the (5a) multiplication image in  FIG.  16   . Through what is called a moving average pixel value calculating process, an average pixel value is calculated for each pixel. 
     It is to be noted that, for a region where pixels cannot be selected in a vegetation portion interval centered on a process target pixel because the process target pixel is in an end region of the image, a process that is similar to that previously explained with reference to  FIG.  11    is performed. That is, the process target pixel is not set at the center, and pixels disposed in a range which includes the process target pixel and within which a number of pixels corresponding to the vegetation portion interval are included are selected as averaging target pixels, and the averaging process is performed thereon. 
     In the abovementioned manner, an average pixel value of the pixel values (NDVI values) of a plurality of pixels that is arranged in a direction perpendicular to the vegetation portion direction and is included in a vegetation portion interval with respect to a process target pixel is calculated, and the calculated pixel value is set as a pixel value of the process target pixel. 
     The multiplication image averaging section  125  calculates the averaged multiplication pixel value for each of all the pixels in the (5a) multiplication image in  FIG.  16   , and generates an averaged multiplication image in (6b) of  FIG.  16   . 
     The multiplication image averaging section  125  outputs the (6b) averaged multiplication image in  FIG.  16    as the output image (corrected NDVI image)  53  to the image displaying section  103 . 
       FIG.  17    depicts an example of an averaged multiplication image that is generated by the multiplication image averaging section  125 . 
     An image in (6b) of  FIG.  17    is identical to the (6b) averaged multiplication image in  FIG.  16   , and is generated as a result of the averaging process performed on the multiplication image generated by the multiplication section  124 . 
     It is to be noted that (6c) of  FIG.  17    indicates an NDVI value of the lowermost pixel line AB of the (6b) averaged multiplication image in  FIG.  17   , that is, the averaged multiplication pixel value (averaged multiplication NDVI value), for reference. The horizontal axis indicates a pixel position on the pixel line AB. The vertical axis indicates the NDVI value of each pixel. 
     A graph indicated by a solid line indicates an averaged multiplication pixel value (averaged multiplication NDVI value). 
     A dotted line indicates an NDVI value in the inputted original NDVI image  52 . 
     The (6b) averaged multiplication image in  FIG.  17    includes index values indicating plant activities of vegetation portions only without any soil portion, that is, NDVI values corresponding to vegetation portions only. The plant activity of each vegetation portion region can be surely discerned without the necessity of considering the existence of soil portions. 
     4. Sequence of Processes that are Executed by Image Processing Device According to Present Disclosure 
     Next, a sequence of processes that are executed by an image processing device according to the present disclosure will be explained. 
       FIG.  18    depicts a flowchart for explaining a sequence of processes that are executed by the image processing device according to the present disclosure. 
     It is to be noted that processes based on the flowchart in  FIG.  18    can be executed in accordance with a program stored in a storage unit of the image processing device  100 , for example. The processes are executed under control of a data processing unit (control unit) including a CPU or the like having a program executing function, for example. 
     Hereinafter, steps in the flowchart in  FIG.  18    will be explained in order. 
     (Step S 101 ) 
     First, at step S 101 , the image processing device receives an input of a captured image. 
     The captured image is an image captured by the camera  11  mounted on the drone  10  depicted in  FIG.  1   , for example. The camera  11  is a multi-spectral camera. From the captured image  51 , the intensity (pixel value) of a RED (infrared) wavelength (approximately 0.63 to 0.69 μm) and the intensity (pixel value) of a NIR (near infrared) wavelength (approximately 0.76 to 0.90 μm) can be acquired. 
     (Step S 102 ) 
     Next, at step S 102 , the image processing device  100  calculates an NDVI value corresponding to each pixel in the captured image, and generates an NDVI image. 
     This step is executed by the NDVI image generating section  101  depicted in  FIG.  7   . 
     The NDVI image generating section  101  receives an input of the captured image  51 , and calculates an NDVI value of each pixel in the captured image  51  according to the abovementioned (Expression 1), that is, 
       NDVI=( NIR−RED )/( NIR+RED )  (Expression 1)
 
     in which RED (infrared) and NIR (near infrared) represent the intensity (pixel value) of a RED (infrared) wavelength (approximately 0.63 to 0.69 μm) and the intensity of an NIR (near infrared) wavelength (approximately 0.76 to 0.90 μm), respectively. 
     The NDVI image generating section  101  calculates an NDVI value of each pixel in the captured image, and generates an NDVI image in which the calculated pixel value (NDVI value) is set for each pixel. 
     The NDVI image is the NDVI image  52  which has been explained with reference to (1a) in  FIG.  9   , for example. 
     It is to be noted that an example of the NDVI image generated at step S 102  and a series of images that are generated by the sections in the NDVI image correcting section  102  that corrects the NDVI image are depicted in  FIG.  19   . 
     Hereinafter, steps S 103  and later will be explained with reference to  FIG.  19   . 
     (Step S 103 ) 
     Next, at step S 103 , the image processing device  100  averages the pixel values of pixels corresponding to the width of a vegetation portion line sequentially to a direction perpendicular to the vegetation portion line in the NDVI image, and generates an averaged image. 
     This step is executed by the averaging section  121  of the HDVI image correcting section  102  depicted in  FIG.  19   . 
     The NDVI image generated by the NDVI image generating section  101  is inputted to the averaging section  121  of the NDVI image correcting section  102 , and the averaging section  121  generates an averaged image of the inputted NDVI image. 
     This step is the process that has been explained with reference to  FIGS.  10  and  12   . For each of all pixels in the NDVI image, a plurality of pixels that is arranged in a direction perpendicular to the vegetation portion direction and is included in a vegetation portion interval is selected, and an average pixel value of the pixel values (NDVI values) of the selected pixels is calculated, and then, an averaged image in which the calculated pixel values are set as average pixel values (average NDVI values) is generated. 
     The averaged image is an output of the averaging section  121  depicted in  FIG.  19   . 
     (Step S 104 ) 
     Next, at step S 104 , the image processing device  100  subtracts a pixel value in the averaged image from the corresponding pixel value in the NDVI image generated at step S 102 , and generates a difference image including the difference pixel values (differential NDVI values). 
     This step is executed by the subtraction section  122  of the NDVI image correcting section  102  depicted in  FIG.  19   . 
     The following two images are inputted to the subtraction section  122 . 
     (1) the inputted original NDVI image before executing the averaging process, and 
     (2) the averaged image (=(2a) averaged image in  FIG.  12   ) generated by the averaging section 
     By using these two inputted images, the subtraction section  122  subtracts a pixel value in the averaged image from the corresponding pixel value in the NDVI image, and generates a difference image. 
     A differential pixel value (differential NDVI value) which is the pixel value of each pixel constituting the difference image is as follows. 
       Differential pixel value (differential NDVI value) in the difference image=(pixel value (NDVI value) in the inputted NDVI image)−(average pixel value (average NDVI value) in the averaged image)
 
     It is to be noted that a differential pixel value (differential NDVI value) in the difference image ranges from a minus value to a plus value, as previously explained with reference to  FIG.  13   . 
     (Step S 105 ) 
     Next, at step S 105 , the image processing device  100  binarizes pixel values, that is, differential pixel values (differential NDVI values) of pixels constituting the difference image, and generates a binarized image. 
     This step is executed by the binarization section  123  of the NDVI image correcting section  102  depicted in  FIG.  19   . 
     The binarization section  123  binarizes the pixel values of the pixels constituting the difference image generated by the subtraction section  122 . That is, the binarization process of setting a pixel value=1 for a differential pixel value (differential NDVI value) that is positive (plus) and setting a pixel value=0 for a differential pixel value that is equal to 0 or is negative (minus) is performed, and a binarized image including the binarized pixel values (binarized NDVI values) which are 0 or 1 is generated. 
     A binarized pixel value (binarized NDVI value) in the binarized image is 0 or 1, as previously explained with reference to (4b) in  FIG.  14   . 
     In the binarized image generated by the binarization section  123 , a portion having a binarized pixel value (binarized NDVI value)=1 can be assessed as a vegetation portion. On the other hand, a portion having a binarized pixel value (binarized NDVI value)=0 can be assessed as a soil portion. 
     (Step S 106 ) 
     Next, at step S 106 , by using two inputted images which are the NDVI image generated at step S 102  and the binarized image generated at step S 105  by the binarization section  123 , the image processing device  100  multiplies a pixel value in the NDVI image and a pixel value in the binarized image, and generates a multiplication image including the multiplication pixel value. 
     This step is executed by the multiplication section  124  of the NDVI image correcting section  102  depicted in  FIG.  19   . 
     By using two inputted images which are the NDVI image generated at step S 102  and the binarized image generated at step S 105  by the binarization section  123 , the multiplication section  124  multiplies a pixel value in the NDVI image and a pixel value in the binarized image, and generates a multiplication image. 
     A multiplied pixel value (multiplication NDVI value) which is a pixel value of each pixel constituting the multiplication image is as follows. 
       Multiplication pixel value (multiplication NDVI value) in the multiplication image=(pixel value (NDVI value) in the inputted NDVI image)×(binarized pixel value (binarized NDVI value) in the binarized image)
 
     One example of the multiplication image generated as a result of the multiplication process at the multiplication section  124  is the (5a) multiplication image in  FIG.  15    previously explained with reference to  FIG.  15   . 
     As previously explained with reference to (5b) in  FIG.  15   , a multiplication pixel value (multiplication NDVI value), in the multiplication image indicated by the solid line reflects a pixel value (NDVI value) of a peak portion (=vegetation portion) in the inputted original NDVI image  52  indicated by the dotted line, and a pixel value of 0 is set for a valley portion (soil portion). 
     That is, regarding each vegetation portion in the multiplication image, a pixel value (NDVI value) in the inputted original NDVI image  52  is reflected. Regarding each soil portion in the multiplication image, a pixel value (NDVI value)=0 is uniformly set. 
     The (5a) multiplication image in  FIG.  15    is outputted as the output image (corrected NDVI image)  53  depicted in  FIGS.  7  and  8    to the image displaying section  103 , and is displayed. 
     In the (5a) multiplication image in  FIG.  15   , all the pixel values (NDVI values) in each soil portion are uniformly set to 0 (black which indicates the minimum pixel value). A user can easily discern that the black regions indicate soil portions and non-black regions indicate vegetation portions. Furthermore, if the pixel value (NDVI value) setting states in the non-black regions are observed, the plant activities in the respective regions can be analyzed. 
     The vegetation region portion in the CD region on the lower right side of the (5a) multiplication image in  FIG.  15    can be determined to have lower pixel values (NDVI values) and lower plant activities than the other vegetation portions. 
     (Step S 107 ) 
     Step S 107  is executed by the multiplication image averaging section  125  of the NDVI image correcting section  102  depicted in  FIG.  19   , and can be skipped because this step is optional. 
     At step S 107 , the image processing device  100  performs the averaging process on the multiplication image generated at step S 106 , and generates an averaged multiplication image. 
     This step is executed by the multiplication image averaging section  125 , as previously explained with reference to  FIGS.  16  and  17   . 
     The multiplication image averaging section  125  performs the averaging process on the multiplication image generated at step S 106 , excluding soil portions where a pixel value (NDVI pixel value)=0. 
     It is to be noted that, in the (5a) multiplication image in  FIG.  16   , a pixel value (NDVI value)=0 is uniformly set in each soil portion region, as previously explained with reference to  FIG.  16   . The multiplication image averaging section  125  performs the averaging process on the image excluding the soil regions where a pixel value=0. 
     Specifically, the following average pixel value calculating process is performed on each of the pixels in the (5a) multiplication image. 
       Average pixel value=(total pixel value of the pixels in the averaging process region)/(the number of pixels having a pixel value&gt;0 in the averaging process region) 
     A specific process sequence thereof will be explained. First, the multiplication image averaging section  125  acquires the vegetation portion direction  71  and the vegetation portion interval  72  from the (5a) multiplication image in  FIG.  16   . In the example depicted in  FIG.  16   , the vegetation portion direction  71  corresponds to the up-down direction in the drawing. 
     Next, the multiplication image averaging section  125  performs the averaging process on pixel values (NDVI values) set for respective pixels in the (5a) multiplication image in  FIG.  16    on the basis of the acquired vegetation portion direction  71  and the acquired vegetation portion interval  72 . 
     The average pixel value which is obtained by the averaging process is calculated in accordance with the following expression, as previously explained. 
       Average pixel value=(total pixel values of the pixels in the averaging process range)/(the number of pixels having a pixel value&gt;0 in the averaging process range) 
     This pixel-based averaging process is performed on each of all the pixels constituting the (5a) multiplication image in  FIG.  16   . That is, the pixel-based averaging process is performed while a process target pixel is sequentially changed from the upper left end to the lower right end of the (5a) multiplication image of  FIG.  16   . Through what is called a moving average pixel value calculating process, an average pixel value is calculated for each pixel. 
     It is to be noted that, for a region where pixels cannot be selected in a vegetation portion interval centered on a process target pixel because the process target pixel is in an end region of the image, a process that is similar to that previously explained with reference to  FIG.  11    is performed. That is, the process target pixel is not set at the center, and pixels disposed in a range which includes the process target pixel and within which a number of pixels corresponding to the vegetation portion interval are included are selected as averaging target pixels, and the averaging process is performed thereon. 
     In the abovementioned manner, an average pixel value of the pixel values (NDVI values) of a plurality of pixels that is arranged in a direction perpendicular to the vegetation portion direction and is included in a vegetation portion interval with respect to a process target pixel is calculated, and the calculated pixel value is set as a pixel value of the process target pixel. 
     The multiplication image averaging section  125  calculates an averaged multiplication pixel value of each of all the pixels in the (5a) multiplication image of  FIG.  16   , generates the (6b) averaged multiplication image in  FIG.  16   , and outputs the averaged multiplication image as the output image (corrected NDVI image)  53  to the image displaying section  103 . 
     The averaged multiplication image generated by the multiplication image averaging section  125  includes index values indicating plant activities of vegetation portions only without any soil portion, that is, including NDVI values corresponding to vegetation portions only. The plant activity of each vegetation portion region can be surely discerned without the necessity of considering the existence of soil portions. 
     5. Hardware Configuration Example of Image Processing Device 
     Next, a hardware configuration example of an image processing device according to the present disclosure will be explained with reference to  FIG.  20   . The hardware depicted in  FIG.  20    is one specific hardware configuration example of an image processing device according to the present disclosure. 
     A CPU (Central Processing Unit)  301  functions as a control section or a data processing section that executes various processes in accordance with a program stored in a ROM (Read Only Memory)  302  or a storage section  308 . For example, the CPU  301  executes processes in accordance with the sequences that have been explained in the above embodiment. Data and a program to be executed by the CPU  301  are stored in a RAM (Random Access Memory)  303 . The CPU  301 , the ROM  302 , and the RAM  303  are mutually connected via a bus  304 . 
     The CPU  301  is connected to the input/output interface  305  via the bus  304 . An input section  306  which includes switches, a keyboard, a mouse, a microphone, a sensor, or the like, and an output section  307  which includes a display, a loud speaker, or the like are connected to the input/output interface  305 . 
     The CPU  301  executes various processes in response to commands inputted from the input section  306 , and outputs the process results to the output section  307 , for example. 
     A storage section  308  is connected to the input/output interface  305 , and includes a hard disk, for example. Various types of data and a program to be executed by the CPU  301  are stored in the storage section  308 . A communication section  309  functions as a transmission/reception section for Wi-Fi communication, Bluetooth (registered trademark) (BT) communication, or data communication over a network such as the Internet or a local area network, and communication with an external device. 
     A drive  310  which is connected to the input/output interface  305 , drives a removable medium  311  such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory such as a memory card, and executes data recording or data reading. 
     6. Conclusion of Configuration According to Present Disclosure 
     An embodiment of the present disclosure has been explained above in detail with reference to the particular embodiment. However, it is obvious that a person skilled in the art can make modification or substitution on the embodiment within the gist of the present disclosure. That is, the present invention has been disclosed in a form of exemplifications, and thus, should not be limitedly interpreted. In order to assess the gist of the present disclosure, the claims should be considered. 
     It is to be noted that the technology disclosed herein can have the following configurations. 
     (1) An image processing device including: 
     a vegetation index value set image correcting section that receives an input of a vegetation index value set image in which a vegetation index value is set as a pixel value and that generates a corrected image of the vegetation index value set image, the vegetation index value indicating a plant activity, in which 
     the vegetation index value set image correcting section
         calculates, for each of pixels constituting the vegetation index value set image, an average pixel value of the pixel and neighboring pixels, and generates an averaged image in which the calculated average pixel values are set,   generates a binarized image by binarizing a difference image between the vegetation index value set image and the averaged image in accordance with a specified threshold, and   generates, as the corrected image of the vegetation index value set image, a multiplication image by multiplying the vegetation index value set image and the binarized image.       

     (2) The image processing device according to (1), in which 
     the vegetation index value set image is an NDVI (Normalized Difference Vegetation Index) image in which an NDVI value is set as a pixel value. 
     (3) The image processing device according to (1) or (2), in which 
     the vegetation index value set image is generated on the basis of a camera image that includes a vegetation portion and a soil portion, 
     the vegetation index value set image correcting section includes an averaging section that generates the averaged image, and 
     the averaging section
         acquires a vegetation portion direction and a vegetation portion interval of the vegetation portion included in the vegetation index value set image,   calculates, as the average pixel value of a process target pixel, an average value of pixel values of pixels that are arranged in a direction perpendicular to the vegetation portion direction and are disposed within the vegetation portion interval including the process target pixel, and   generates the averaged image in which the average pixel values calculated for the respective pixels constituting the vegetation index value set image are set.       

     (4) The image processing device according to (3), in which 
     the vegetation portion interval is a pixel interval within which pixels corresponding to one vegetation portion line and pixels corresponding to one soil portion line are disposed, and 
     the averaging section calculates, as the average pixel value of the process target pixel, an average value of pixel values of pixels that are disposed within the vegetation portion interval including the process target pixel and that include pixels corresponding to one vegetation portion line and pixels corresponding to one soil portion line. 
     (5) The image processing device according to (3) or (4), in which 
     by performing image analysis on the vegetation index value set image, the averaging section acquires the vegetation portion direction and the vegetation portion interval of a vegetation portion included in the vegetation index value set image. 
     (6) The image processing device according to any one of (3) to (5), in which 
     from data inputted by a user, the averaging section acquires at least any of the vegetation portion direction or the vegetation portion interval. 
     (7) The image processing device according to any one of (1) to (6), in which 
     the vegetation index value set image correcting section includes a subtraction section that receives an input of the averaged image, and generates a difference image between the vegetation index value set image and the averaged image, and 
     the subtraction section subtracts a pixel value of each pixel in the averaged image from a pixel value of the corresponding pixel in the vegetation index value set image, and generates the difference image including pixel values obtained as the subtraction result. 
     (8) The image processing device according to any one of (1) to (7), in which 
     the vegetation index value set image is an NDVI (Normalized Difference Vegetation Index) image in which an NDVI value is set as a pixel value, 
     the NDVI value in the NDVI image ranges from 0.0 to 1.0, and 
     the difference image is a difference image between the NDVI image and the averaged image, and includes a pixel having a pixel value of 0 or greater and a pixel having a pixel value of 0 or less. 
     (9) The image processing device according to any one of (1) to (8), in which 
     the vegetation index value set image correcting section includes a binarization section that binarizes the difference image in accordance with a specified threshold, and generates a binarized image, and 
     the binarization section
         defines the specified threshold=0, and   generates the binarized image in which a pixel value=1 is set for each pixel constituting the difference image and having a pixel value that is positive, and a pixel value=0 is set for each pixel constituting the difference image and having a pixel value that is equal to 0 or is negative.       

     (10) The image processing device according to any one of (1) to (9), in which 
     the vegetation index value set image correcting section includes a binarization section that binarizes the difference image in accordance with a specified threshold, and generates a binarized image, and 
     the binarization section generates the binarized image by using a value other than “0” as the prescribed threshold. 
     (11) The image processing device according to any one of (1) to (10), in which 
     the vegetation index value set image correcting section includes a multiplication section that generates the multiplication image by multiplying the vegetation index value set image and the binarized image, and 
     the multiplication section multiplies a pixel value of each pixel in the vegetation index value set image with a pixel value of the corresponding pixel in the binarized image, and generates a multiplication image including pixel values obtained as the multiplication result. 
     (12) The image processing device according to (11), in which 
     each pixel value in the binarized image is set to 0 or 1, and 
     the multiplication section multiplies a pixel value of each pixel in the vegetation index value set image with a pixel value of the corresponding pixel set to 0 or 1 in the binarized image, and generates the multiplication image including a pixel value that is equal to 0 and a pixel value reflecting the pixel value in the vegetation index value set image as the multiplication result. 
     (13) The image processing device according to (11) or (12), in which 
     the vegetation index value set image is generated on the basis of a camera image that includes a vegetation portion and a soil portion, and 
     the multiplication section generates the multiplication image in which a pixel value=0 is set in a soil portion region. 
     (14) The image processing device according to any one of (1) to (13), in which 
     the vegetation index value set image correcting section includes a multiplication image averaging section that performs an averaging process on the multiplication image, and 
     the multiplication image averaging section calculates, for each of pixels constituting the multiplication image, an average pixel value of the pixel and neighboring pixels, generates an averaged multiplication image in which the calculated average pixel values are set, and uses the generated averaged multiplication image as the corrected image of the vegetation index value set image. 
     (15) The image processing device according to (14), in which 
     the multiplication image averaging section generates the averaged multiplication image by
         generating an extracted vegetation portion image obtained by extracting, from the multiplication image, a vegetation portion region that is assessed as a vegetation portion only,   acquiring a vegetation portion direction and a vegetation portion interval in the generated extracted vegetation portion image,   calculating, as an average pixel value of a process target pixel, an average value of pixel values of pixels that are arranged in a direction perpendicular to the vegetation portion direction and are disposed within the vegetation portion interval including the process target pixel, and   enlarging the extracted vegetation portion image to an image size of the vegetation index value set image after calculating the average pixel values of respective pixels constituting the multiplication image.       

     (16) An image processing method that is executed in an image processing device, the image processing device including a vegetation index value set image correcting section that receives an input of a vegetation index value set image in which a vegetation index value indicating a plant activity is set as a pixel value and that generates a corrected image of the vegetation index value set image, the method including: 
     causing the vegetation index value set image correcting section to
         calculate, for each of pixels constituting the vegetation index value set image, an average pixel value of the pixel and neighboring pixels, and generate an averaged image in which the calculated average pixel values are set,   generate a binarized image by binarizing a difference image between the vegetation index value set image and the averaged image in accordance with a specified threshold, and   generate, as the corrected image of the vegetation index value set image, a multiplication image by multiplying the vegetation index value set image and the binarized image.       

     (17) A program for causing an image processing device to execute image processing, the image processing device including a vegetation index value set image correcting section that receives an input of a vegetation index value set image in which a vegetation index value indicating a plant activity is set as a pixel value and that generates a corrected image of the vegetation index value set image, the program being configured to cause the vegetation index value set image correcting section to perform: 
     a process of calculating, for each of pixels constituting the vegetation index value set image, an average pixel value of the pixel and neighboring pixels, and generating an averaged image in which the calculated average pixel values are set; 
     a process of generating a binarized image by binarizing a difference image between the vegetation index value set image and the averaged image in accordance with a specified threshold; and 
     a process of generating, as the corrected image of the vegetation index value set image, a multiplication image by multiplying the vegetation index value set image and the binarized image. 
     Further, a series of the processes explained herein can be executed by hardware, software, or a composite structure thereof. In a case where the processes are executed by software, a program having a sequence of the processes recorded therein can be executed after being installed into a memory of a computer incorporated in dedicated hardware, or can be executed after being installed into a general-purpose computer capable of various processes. For example, such a program may be previously recorded in a recording medium. The program can be installed into the computer from the recording medium. Alternatively, the program can be received over a network such as a LAN (Local Area Network) or the Internet, and can be installed into a recording medium such as an internal hard disk. 
     It is to be noted that the processes described herein are not necessarily executed in the described time-series order, and the processes may be executed parallelly or separately, as needed or in accordance with the processing capacity of a device to execute the processes. Further, in the present description, a system refers to a logical set structure including a plurality of devices, and the devices in the structure are not necessarily included in the same casing. 
     INDUSTRIAL APPLICABILITY 
     According to the configuration of one embodiment of the present disclosure, a device and a method of generating and outputting a corrected image including a high-precision vegetation index value such as an NDVI value in a vegetation portion region on the basis of an image in which a vegetation portion and a soil portion coexist are implemented, as explained so far. 
     Specifically, the device includes a vegetation index value set image correcting section that generates a corrected image of a vegetation index value set image in which a vegetation index value such as an NDVI value is set as a pixel value, for example. The vegetation index value set image correcting section calculates, for each of pixels constituting the vegetation index value set image, an average pixel value of the pixel and neighboring pixels, generates an averaged image in which the average pixel value is set, generates a binarized image by binarizing a difference image between the vegetation index value set image and the averaged image in accordance with a specified threshold, and generates, as the corrected image of the vegetation index value set image, a multiplication image of the vegetation index value set image and the binarized image. 
     With this configuration, a device and a method of generating and outputting a corrected image including a high-precision vegetation index value such as an NDVI value in a vegetation portion region on the basis of an image in which the vegetation portion and a soil portion coexist, are implemented. 
     REFERENCE SIGNS LIST 
     
         
         
           
               10 : Drone 
               11 : Camera 
               20 : Poor growth region 
               51 : Captured image 
               52 : NDVI image 
               53 : Output image (corrected NDVI image) 
               71 : Vegetation portion direction 
               72 : Vegetation portion interval 
               81 ,  91 : Averaging process target pixel 
               100 : Image processing device 
               101 : NDVI image generating section 
               102 : NDVI image correcting section 
               103 : Image displaying section 
               121 : Averaging section 
               122 : Subtraction section 
               123 : Binarization section 
               124 : Multiplication section 
               125 : Multiplication image averaging section 
               301 : CPU 
               302 : ROM 
               303 : RAM 
               304 : Bus 
               305 : Input/output interface 
               306 : Input section 
               307 : Output section 
               308 : Storage section 
               309 : Communication section 
               310 : Drive 
               311 : Removable medium