KR102410124B1 - Apparatus and method for Vegetation index detection using multispectral image - Google Patents

Abstract

The present invention relates to an apparatus and method for detecting a vegetation index using a multi-spectral image, comprising: an optical module for separating light entering through one or more lenses into image signals of each wavelength band using an image sensor for each wavelength band; a solar radiation measurement module that measures the intensity of sunlight incident from the outside and provides a solar radiation value; an exposure compensation module for adjusting an exposure value of the image sensor for each wavelength band based on the insolation value; When an image signal of each wavelength band is input through an image sensor for each wavelength band to which an exposure value corrected through the exposure compensation module is applied, an inter-pixel correction value of an image of each wavelength band is calculated, and the calculated correction value is used to an image processing module for storing the corrected pixel data and then synthesizing the pixel data to provide a multi-spectral image; and a detection module for calculating a Vegetation Index using the multi-spectral image, and monitoring the type and biophysical state of vegetation in the corresponding area using the calculated vegetation index.

Description

Apparatus and method for Vegetation index detection using multispectral image}

The present invention relates to a technique for detecting a vegetation index using a multi-spectral image obtained using a single optical system.

The content described in this section merely provides background information on an embodiment of the present invention and does not constitute the prior art.

Among the analysis methods using satellite images, there is a method using various optical indices using the spectral characteristics of satellite images. Here, the spectral characteristics are the characteristics of electromagnetic waves, such as visible light, infrared light, and ultraviolet light, which we commonly know.

Various indices for analyzing various conditions of vegetation, water resources, snowfall, soil, fire and other characteristics have been developed in various optical indices using the spectral characteristics of satellite images. Compared to the advantage of acquiring spatial information in a wide area, the analysis method using satellite images is difficult to acquire cloud-free images due to the restrictions of the weather conditions. Therefore, it is difficult to obtain high-resolution image data, and there is a problem in that it takes a lot of money to obtain a desired time and region image.

Since there are problems such as spatial resolution and temporal resolution in acquiring information through satellite images, a method of using images acquired by using a multi-spectral sensor on an unmanned aerial vehicle to calculate the vegetation index should be used in parallel.

In the multi-spectral band image data observed using artificial satellites or aircraft, objects on the ground exhibit unique characteristics for each wavelength band, so by using this characteristic, desired information can be extracted. In particular, since more than 95% of the image data of the land surface, which is the main area of interest for ground observation satellites such as Landsat, contains information about soil and vegetation, it is possible to estimate the vegetation distribution or density of vegetation on the surface using this image data. do. For example, in the case of vegetation colored green by chlorophyll, it generally shows a slightly high reflectance in the green wavelength region, almost no reflection in the red wavelength region, and shows a high reflectance close to 50% in the near-infrared region. On the other hand, in the case of vegetation without chlorophyll due to death, it shows high reflectance in the visible light region, but shows a lower reflectance than living healthy vegetation in the near infrared region. In the case of soil, the reflectance is lower than that of withered vegetation in the visible light region, but higher than that of green plants, and the reflectance is lower than that of both dead vegetation and green plants in the near infrared region.

In this way, it is possible to create an equation to calculate the density of vegetation by combining the characteristics between the spectral bands based on the reflection characteristics according to each wavelength band, which is called the vegetation index. The vegetation index was developed so that it can be used as a measure that can quantitatively represent leaf area, vegetation distribution area, tree height, and species, etc.

Existing methods for calculating the vegetation index based on remote sensing use an RGB camera for human reading, a near-infrared wavelength camera for calculating the vegetation index, and a spectral radiometer for irradiating observation wavelengths of multiple bands. If remote sensing is performed on six wavelength bands, at least one lens and an optical system must be separately configured for each of the six wavelength bands, and an image of an observation object must be captured for each wavelength band. Therefore, since the existing remote sensing-based vegetation index calculation method cannot acquire images for each wavelength band at the same time, it is necessary to correct the images acquired for each wavelength band by reflecting the spatiotemporal change, and the wavelength band to be observed. There is a problem in that the volume of the observation device is inevitably increased because an optical system must be separately configured.

In order to solve the above problems, according to an embodiment of the present invention, image signals for each wavelength band can be simultaneously photographed using a single optical module, and multi-spectral images can be corrected according to the amount of insolation. There is this.

However, the technical task to be achieved by the present embodiment is not limited to the technical task as described above, and other technical tasks may exist.

As a technical means for achieving the above technical problem, the apparatus for detecting vegetation index using a multi-spectral image according to an embodiment of the present invention uses an image sensor for each wavelength band to detect light entering through one or more lenses of each wavelength band. an optical module that separates the video signal; a solar radiation measurement module that measures the intensity of sunlight incident from the outside and provides a solar radiation value; an exposure compensation module for adjusting an exposure value of the image sensor for each wavelength band based on the insolation value; When an image signal of each wavelength band is input through an image sensor for each wavelength band to which an exposure value corrected through the exposure compensation module is applied, an inter-pixel correction value of an image of each wavelength band is calculated, and the calculated correction value is used to an image processing module for storing the corrected pixel data and then synthesizing the pixel data to provide a multi-spectral image; and a detection module for calculating a Vegetation Index using the multi-spectral image, and monitoring the type of vegetation and the biophysical state of the area using the calculated vegetation index.

The solar radiation measurement module, characterized in that it includes at least one photodiode and a filter.

The optical module may include: a lens unit for condensing light on an image of a target target incident at a single angle of view to a preset position; a prism arranged at different angles based on a direction in which the light passing through the lens unit is incident, and including a plurality of reflective surfaces for reflecting light of different wavelength bands to separate light for each wavelength band; and an image sensor for each wavelength band that converts light of each wavelength band passing through each reflective surface of the prism into an electrical image signal and outputs the converted light.

The prism reflects light of any one wavelength band different from each other among the first wavelength band, the second wavelength band, the third wavelength band, and the fourth wavelength band at each reflective surface at each reflective surface at a predetermined angle, The image sensor for each wavelength band is disposed at an end of an angle reflected through each reflective surface of the prism.

On the other hand, the method for detecting a vegetation index using a multi-spectral image according to an embodiment of the present invention is a method of detecting a vegetation index through an optical module for obtaining a multi-spectral image, a) each wavelength band within the optical module separating an image signal for a target object by wavelength band through an image sensor; b) providing an insolation value for each wavelength band by measuring the intensity of sunlight incident from the outside; c) adjusting the exposure value of the image sensor for each wavelength band based on the insolation value for each wavelength band; d) When an image signal of each wavelength band is input through the image sensor for each wavelength band to which the adjusted exposure value is applied, an inter-pixel correction value of the image of each wavelength band is calculated, and the corrected pixel is performed using the calculated correction value. providing a multi-spectral image by synthesizing the pixel data after storing the data; and e) calculating a Vegetation Index using the multi-spectral image, and monitoring the type of vegetation and the biophysical state of the area using the calculated vegetation index. .

In this case, in step a), the image sensor for each wavelength band is different from one of a first wavelength band (λ1), a second wavelength band (λ2), a third wavelength band (λ3), and a fourth wavelength band (λ4). It is characterized in that the image signal of the wavelength band of each is separated.

In the method for detecting vegetation index using a multi-spectral image according to another embodiment of the present invention, in the method for detecting a vegetation index through an optical module for obtaining a multi-spectral image, a) an image for each wavelength band within the optical module separating the image signal for the target object by wavelength band through a sensor; b) providing an insolation value of a preset wavelength band by measuring the intensity of sunlight incident from the outside; c) adjusting the exposure value of the image sensor for each wavelength band based on the insolation value of the preset wavelength band; d) When an image signal of each wavelength band is input through the image sensor for each wavelength band to which the adjusted exposure value is applied, an inter-pixel correction value of the image of each wavelength band is calculated, and the corrected pixel is performed using the calculated correction value. providing a multi-spectral image by synthesizing the pixel data after storing the data; and e) calculating a Vegetation Index using the multi-spectral image, and monitoring the type of vegetation and the biophysical state of the area using the calculated vegetation index. .

Here, in step a), the image sensor for each wavelength band separates an image signal of any one wavelength band different from each other among a near-infrared wavelength band, a red wavelength band, a green wavelength band, and a blue wavelength band, and the step b) includes The insolation value of the wavelength band including all wavelength bands of the image sensor for each wavelength band is measured.

According to the above-described problem solving means of the present invention, the present invention can simultaneously shoot image signals for each wavelength band using a single optical module, thereby reducing the volume of the optical system compared to the existing multi-spectral image acquisition device, and In order to reflect only light of a specific wavelength band, the selective configuration of the wavelength band to be filtered through a prism having a plurality of reflective surfaces or the wavelength selection for each purpose is easy, and the effect of enabling the correction of multi-spectral images according to the amount of insolation have.

1 is a block diagram illustrating the configuration of a vegetation index detection apparatus using a multi-spectral image according to an embodiment of the present invention.
2 is a view showing an optical system in the apparatus for detecting vegetation index using a multi-spectral image according to the first embodiment of the present invention.
3 is a view showing an optical system in the apparatus for detecting vegetation index using a multi-spectral image according to a second embodiment of the present invention.
4 is a view showing the configuration of a prism in the optical module according to the first embodiment of the present invention.
5 is a diagram illustrating a configuration of a prism in an optical module according to a second embodiment of the present invention.
6 is a view for explaining the configuration of a vegetation index detection apparatus using a multi-spectral image according to the first embodiment of the present invention.
7 is a view for explaining the configuration of a vegetation index detection apparatus using a multi-spectral image according to a second embodiment of the present invention.
8 is a view for explaining the configuration of a vegetation index detection apparatus using a multi-spectral image according to a third embodiment of the present invention.
9 is a view for explaining the configuration of a vegetation index detection apparatus using a multi-spectral image according to a fourth embodiment of the present invention.
10 is a flowchart illustrating a method for detecting a vegetation index using a multi-spectral image according to a first embodiment of the present invention.
11 is a flowchart illustrating a method for detecting a vegetation index using a multi-spectral image according to a second embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art can easily implement them. However, the present invention may be embodied in several different forms and is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a part is "connected" with another part, this includes not only the case of being "directly connected" but also the case of being "electrically connected" with another element interposed therebetween. . In addition, when a part "includes" a certain component, it means that other components may be further included, rather than excluding other components, unless otherwise stated, and one or more other features However, it is to be understood that the existence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded in advance.

In the present specification, a 'terminal' may be a wireless communication device with guaranteed portability and mobility, for example, any type of handheld-based wireless communication device such as a smart phone, tablet PC, or notebook computer. In addition, the 'terminal' may be a wired communication device such as a PC that can connect to another terminal or server through a network. In addition, the network refers to a connection structure capable of exchanging information between each node, such as terminals and servers, and includes a local area network (LAN), a wide area network (WAN), and the Internet (WWW). : World Wide Web), wired and wireless data networks, telephone networks, and wired and wireless television networks.

Examples of wireless data communication networks include 3G, 4G, 5G, 3rd Generation Partnership Project (3GPP), Long Term Evolution (LTE), World Interoperability for Microwave Access (WIMAX), Wi-Fi, Bluetooth communication, infrared communication, ultrasound Communication, Visible Light Communication (VLC), LiFi, and the like are included, but are not limited thereto.

The following examples are detailed descriptions to help the understanding of the present invention, and do not limit the scope of the present invention. Accordingly, an invention of the same scope performing the same function as the present invention will also fall within the scope of the present invention.

Hereinafter, an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a block diagram illustrating the configuration of a vegetation index detection apparatus using a multi-spectral image according to an embodiment of the present invention.

Referring to FIG. 1 , the apparatus 100 for detecting vegetation index using a multi-spectral image includes an optical module 110 , a solar radiation measurement module 120 , an exposure compensation module 130 , an image processing module 140 , and a detection module 150 . ), but is not limited thereto.

The optical module 110 separates the light entering through one or more lenses into image signals of each wavelength band using an image sensor for each wavelength band. The image sensor for each wavelength band serves as a multi-spectral camera.

The insolation measurement module 120 measures the intensity of sunlight incident from the outside and provides an insolation value.

The exposure compensation module 130 adjusts the exposure value of the image sensor for each wavelength band based on the insolation value provided from the insolation measurement module 120 , and provides each adjusted exposure value to the image sensor for each wavelength band, respectively. In this case, the exposure compensation module 130 may be embedded in the image sensor for each wavelength band.

The image processing module 140 receives an image signal of a first wavelength band λ1 provided from the first image sensor 240a through a first channel (Channel 1), and receives a second image signal through a second channel (Channel 2). 2 The image signal of the second wavelength band λ2 provided by the image sensor 240b is input, and the image signal of the third wavelength band λ3 provided by the third image sensor 240c is input through the third channel (Channel 3). A video signal is input. In this way, when the corrected exposure value is applied to the image sensor for each wavelength band and a raw image signal for each wavelength band for the target object is input to the image processing module 140 , the image processing module 140 generates the raw image for each wavelength band A signal is stored, pixel data corrected by calculating an inter-pixel correction value of each raw image signal is stored, and a multi-spectral image is provided by synthesizing the stored pixel data into an image.

The detection module 150 calculates a vegetation index using the multi-spectral image, and monitors the type of vegetation and the biophysical state using the calculated vegetation index. Here, the detection module 150 may be implemented in a computing device including a communication module (not shown), a memory (not shown), a processor (not shown), and a database (not shown), and may be implemented in a smartphone, tablet PC, or PC. , a notebook PC and other user terminal devices may be implemented. Alternatively, the detection module 150 may be implemented as various types of devices capable of performing a server role.

In general, the reflection characteristics of vegetation have different characteristics according to crops and wavelength bands, unlike water and soil. That is, in the visible light region, the pigment contained in crops affects the reflectance in the wavelength band, and in the near infrared region, the reflection greatly increases because the green leaves of vegetation absorb very little energy. This is a unique spectral reflection characteristic of chlorophyll, and in the case of vegetation that is green by chlorophyll, the reflectance is slightly higher in the green wavelength region (500-600 nm), and the reflectance is lowered in the red wavelength region (600-700 nm), and near-infrared In the wavelength range (800-1000 nm), it shows a high reflectance of about 40-50%. In addition, since moisture absorbs a lot of energy in the mid-infrared region, the moisture content of crops dominates the reaction in this region. As such, if the change characteristics of the spectral reflection curve slope are known, the vegetation information of the crop can be grasped.

In particular, spectral reflectance in the near-infrared (NIR) region other than visible light is the most important photosynthesis-related factor for crop growth, which is directly related to the chlorophyll content and nutritional status of crops, which is a biophysical factor, canopy area and height, and the like, indicating the growth and nutritional status of crops. Previously, in Spain and the United States, there have been research cases on the potential productivity prediction model of crops using the vegetation index and biophysical factors such as height and canopy area, which combine the spectral reflectance of the near-infrared region and the visible region in corn or cotton cultivation. .

SR (Simpel Ratio, SR) can be expressed as in Equation 1 below using that healthy vegetation has low red reflection due to absorption by chlorophyll and large NIR reflection due to sponge breakfast.

[Equation 1]

Plants need water to grow, and the leaves receive water absorbed from the roots through the stem, and most of the water is in the sponge tissue. Therefore, it is possible to know what the moisture content of plants is through remote sensing in the mid-infrared, thermal-infrared, and passive microwave regions. At this time, if the wavelength of the moisture contained in the plant is long, the absorption also increases proportionally, and the maximum reflection is shown at 1.6㎛ and 2.2 in the mid-infrared wavelength band.

The Normalized Difference Vegetation Index (NDVI) normalizes SR as shown in Equation 2 below to have a value of -1 < NDVI < 1, but in the case of vegetation, it has a positive value.

[Equation 2]

As shown in Equation 3, the infrared index (II) is a normal moisture index, and when there is enough moisture in the vegetation, the mid-infrared (MIR) becomes small and II becomes large.

[Equation 3]

Moisture Stress Index (MSI) is expressed as in Equation 4 below, and when the vegetation lacks moisture, mid-infrared (MIR) increases and MSI increases.

[Equation 4]

The Soil Adjusted Vegetation Index (SAVI) corrects the spectral response of the soil in the pixel, and is expressed as in Equation 5 below. If L = 0, it is the same as NDVI, but usually L = 0.5 is used. depends on

[Equation 5]

The Soil and Atmospherically Adjusted Vegetation Index (SARVI) is expressed as Equation 6, and the atmospheric effect is reduced by using the difference in radiation amount between the blue region and the red region. The meaning of P ^* means that the amount of molecular scattering and the amount of ozone absorption must be corrected in advance.

[Equation 6]

이다. In Equation 6,

to be.

값을 6.0, 7.5, 1.0으로 결정할 수 있다.The Enhanced Vegetation Index (EVI), as suggested by the MODIS Land Discipline Group, is expressed as in Equation 7 below, and experimentally

Values can be determined as 6.0, 7.5, or 1.0.

[Equation 7]

The detection module 150 analyzes the correlation for plants in a specific area for a plurality of vegetation indices including NDVI, II, MSI, SAVI, SARVI, and EVI, and based on the analysis result, the spatial distribution of plant types and communities By extracting information on types, changes in growth cycle, physiological and behavioral changes of plant growth, etc., it is used as data to understand the climate, soil, geology, and geographical characteristics of the area.

2 is a view showing an optical system in the apparatus for detecting vegetation index using a multi-spectral image according to a first embodiment of the present invention, and FIG. 3 is a vegetation index detection apparatus using a multi-spectral image according to a second embodiment of the present invention. It is a diagram showing my optical system.

2 and 3 , the optical system 120 includes a first lens 210 , a second lens 220 , a prism 230 , and image sensors 240a , 240b and 240c for each wavelength band.

The first lens 210 focuses the light on the target to a specific position, and the second lens 220 is disposed between the first lens 210 and the prism 230 , and forms the first lens 210 with the first lens 210 . All of the light condensed through the prism 230 is completely incident on the prism 230 . The second lens 220 may be implemented as a collimator that transforms scattered light into parallel light, or may be implemented as a lens that condenses to a specific focus. The second lens 220 prevents light from being dispersed so that all light can be incident on the prism 230 .

The prism 230 separates light for each wavelength band, and includes a plurality of reflective surfaces having a dichroic filter on each surface, and whenever light incident on the prism 230 passes through each reflective surface, Allows light of a specific wavelength band to be reflected in a specific direction. A specific structure and operation of the prism 230 will be described with reference to FIGS. 4 or 5 . In this case, the prism uses a prism structure such as the Phillips prism 230 or the cross dichroic prism 231 , but various optical separation media capable of separating signals for each wavelength band may be used.

4 is a view showing the configuration of a prism in the optical module according to the first embodiment of the present invention.

Referring to FIG. 4 , the prism 230 includes a plurality of reflective surfaces 310 to 330 disposed at different angles with respect to the direction in which the light is incident. Each of the reflective surfaces 310 to 330 reflects different wavelength bands and reflects different wavelength bands for each region even within one reflective surface.

The reflective surface 310 reflects the light of the first wavelength band among the light passing through the second lens 220 at a preset angle. The reflective surface 310 includes a dichroic filter that reflects only the light of the first wavelength band to the surface, and reflects only the light of the first wavelength band among the incident light at a preset angle. A fourth image sensor 240d is disposed at the end of the angle at which light is reflected through the reflective surface 310 , senses the amount of light in the corresponding wavelength band, converts it into an electrical image signal, and outputs it.

The reflective surface 320 reflects light of the second wavelength band and the third wavelength band among the light passing through the reflective surface 310 , respectively. Unlike the reflective surface 310 , the reflective surface 320 includes a dichroic filter that reflects light of different wavelength bands depending on regions. The lower end of the reflective surface 320, which is the region where the light passing through the reflective surface 310 is incident, reflects only the light of the second wavelength band, so that the first image sensor 240a measures the amount of light in the second wavelength band among the emitted light. It can be sensed and converted into an electrical image signal. In addition, the upper end of the reflective surface 320 includes a wavelength band to be reflected by the reflective surface 330 and a dichroic filter to reflect light in the third wavelength band, and is reflected from the reflective surface 330 in the third wavelength band. The light is re-reflected to be incident on the second image sensor 240b.

Due to the structure in which the reflective surfaces are formed, it is difficult for all of the light reflected from each reflective surface to be directly incident on each sensor. Therefore, a specific reflective surface must include both a dichroic filter for reflecting light of a wavelength band to be reflected and a dichroic filter for re-reflecting light reflected from another reflective surface in the direction of the sensor. The reflective surface 320 includes a dichroic filter that reflects light of a second wavelength band (for reflection by itself) and a dichroic filter that reflects light of a third wavelength band (reflected by the reflective surface 330). are separated according to the area and include all of them on the surface.

4 shows that the lower end of the reflective surface 320 includes a dichroic filter that reflects the light of the second wavelength band and the upper end of the light of the third wavelength band, but the present invention is not limited thereto. may vary depending on the case.

The reflective surface 330 reflects the light of the third wavelength band among the light passing through the reflective surface 320 . The reflective surface 330 includes a dichroic filter that reflects only the light of the third wavelength band, and reflects only the light of the third wavelength band among the light passing through the reflective surface 310 and the reflective surface 320 . Since it is difficult for the reflective surface 330 to directly reflect the light of the third wavelength band to the sensor 240b for sensing the light of the third wavelength band due to the structure of the reflective surfaces, the reflective surface 330 reflects the light of the third wavelength band to the reflective surface 320 . By reflecting it to a specific region of , light of the third wavelength band is incident on the fourth image sensor 240b through the reflective surface 320 .

Since each of the reflective surfaces 310 to 330 reflects light of each wavelength band, only light of the fourth wavelength band passes through the reflective surface 330 . The light of the fourth wavelength band passing through the reflective surface 330 is sensed by the third image sensor 240c.

Here, each of the first to fourth wavelength bands may be any one of a near-infrared wavelength band, a red wavelength band, a green wavelength band, and a blue wavelength band, but is not limited thereto.

5 is a diagram illustrating a configuration of a prism in an optical module according to a second embodiment of the present invention.

Referring to FIG. 5 , the prism 230 includes a plurality of reflective surfaces 410 and 420 disposed at different angles with respect to the direction in which the light is incident. Each of the reflective surfaces 410 and 420 reflects different wavelength bands and reflects different wavelength bands for each region even within one reflective surface.

The reflective surface 410 reflects the light of the first wavelength band and the light of the second wavelength band, respectively. Like the reflective surface 320 , the reflective surface 410 also reflects light of different wavelength bands depending on the region. First, the reflective surface 410 includes a dichroic filter that reflects the light of the first wavelength band on the lower surface of the reflective surface 410, and transmits the light of the first wavelength band among the light incident through the second lens 220 at a preset angle. reflected by The light of the first wavelength band reflected from the reflective surface 410 is incident on the third image sensor 240c. On the other hand, the reflective surface 410 includes a dichroic filter for re-reflecting the light reflected from the reflective surface 420 on the upper surface of the first image, It is reflected back to the sensor 240a. Accordingly, light of the second wavelength band reflected from the reflective surface 420 may be incident on the first image sensor 240a. Similarly, in FIG. 5 , the lower end of the reflective surface 410 includes a dichroic filter that reflects light of the first wavelength band and the upper end reflects light of the second wavelength band, but is not limited thereto. The position of may be changed depending on the case.

The reflective surface 420 reflects only the light of the second wavelength band among the light passing through the reflective surface 410 . The reflective surface 420 includes a dichroic filter for reflecting the light of the second wavelength band on the surface, and reflects only the light of the second wavelength band among the light passing through the reflective surface 410 . The light of the second wavelength band reflected by the reflective surface 420 is re-reflected from the reflective surface 410 and is incident on the first image sensor 240a.

The light of the third wavelength band passing through the reflective surface 420 is incident on the second image sensor 240b. It passes through the reflective surface 410 and the reflective surface 420 , and only light of the third wavelength band passes through the reflective surface 420 . The prism 230 does not additionally include a separate reflective surface, and allows light passing through the reflective surface 420 to be directly incident on the fourth image sensor 240b.

As in the case of FIG. 4 , each of the first to third wavelength bands may be any one of a red wavelength band, a green wavelength band, and a blue wavelength band, but is not limited thereto.

The prisms described with reference to FIGS. 4 and 5 have been described for convenience in that the reflective surfaces arranged in a specific order reflect a specific wavelength band, but if the reflective surfaces in the prism 230 reflect light of different wavelength bands, it is arranged The wavelength bands reflected in the order may be different from those described with reference to FIGS. 4 and 5 .

Referring back to FIGS. 2 and 3 , the first to fourth image sensors 240a to 240c or 240a to 240d receive and sense light in each wavelength band reflected from the prism 230 in various directions to obtain an electrical image. It is converted into a signal and output. Each image sensor is arranged in such a way that each reflective surface in the prism reflects the light of each wavelength band, and each senses the light of each wavelength band separated through the prism and converts it into an electrical image signal image processing module 140 forward to

6 is a view for explaining the configuration of a vegetation index detection apparatus using a multi-spectral image according to a first embodiment of the present invention, Figure 7 is a vegetation index detection apparatus using a multi-spectral image according to a second embodiment of the present invention 8 is a view for explaining the configuration of a vegetation index detection apparatus using a multi-spectral image according to a third embodiment of the present invention, and FIG. It is a diagram explaining the configuration of a vegetation index detection device using a spectral image.

6 to 9 , the solar radiation measurement module 120 includes at least one silicon photodiode 121 and a filter 122 , and measures the amount of solar radiation through the silicon photodiode 121 and the filter 122 . The measured insolation value is provided to the image processing module 140 .

The silicon photodiode 121 has a strong wavelength dependence in light reception sensitivity, and is suitable for photodetection from visible light to a wavelength of 1 μm. The filter 122 transmits light of a set wavelength band.

The insolation measurement module 120 may detect and provide insolation for the entire wavelength band that may include all of the third wavelength bands from the first wavelength band, and may detect and provide the insolation amount of sunlight for each wavelength band. .

That is, as shown in FIGS. 6 and 7 , when the insolation measurement module 120 includes one silicon photodiode 121 and a filter 122 , the entire wavelength of the third wavelength band from the first wavelength band Detects the amount of insolation for the band. The optical module 110 using the Phillips prism 230 or the cross dichroic prism 231 has an exposure value adjusted according to the amount of insolation, and separates the image signal for the target object by wavelength band and provides it to the image processing module 140 do.

8 and 9, the solar radiation measurement module 120 includes a first silicon photodiode 121a, a filter 122a, and a second wavelength band ( It consists of a second silicon photodiode 121b and a filter 122b for measuring the amount of insolation of λ2, and a third silicon photodiode 121c and a filter 122c for measuring the amount of insolation in the third wavelength band 3 . .

The insolation measurement module 120 provides the measured insolation value to the image processing module 140, and the optical module 110 using the Phillips prism 230 or the cross dichroic prism 231 has an exposure value according to the insolation. The adjusted image signal for the target object is separated for each wavelength band and provided to the image processing module 140 . The image processing module 140 may correct the multi-spectral image according to the insolation value. Accordingly, the image processing module 140 corrects the exposure value of the image sensor for each wavelength band according to the insolation value transmitted through the insolation measurement module 120 , and image signals for each wavelength band simultaneously photographed from the image sensor to which the corrected exposure value is applied. Receive and store

10 is a flowchart illustrating a method for detecting a vegetation index using a multi-spectral image according to a first embodiment of the present invention.

Referring to FIG. 10 , when the image processing module 140 transmits an image capturing command for a target object (S11), the image sensors 240a, 240b, and 240c of each wavelength band are enabled (Enable) ( S12).

When sunlight is incident, the solar radiation measurement module 120 detects solar radiation for the first wavelength band, the second wavelength band, and the third wavelength band, and outputs a solar radiation value for each wavelength band (S13, S14).

The exposure value of the image sensor 240a of the first wavelength band is adjusted according to the insolation value of the first wavelength band, and the exposure value of the image sensor 240b of the second wavelength band is adjusted according to the insolation value of the second wavelength band, The exposure value of the image sensor 240c of the third wavelength band is adjusted according to the insolation value of the third wavelength band (S15).

After the exposure values of the image sensors 240a, 240b, and 240c of each wavelength band are corrected, the image sensors 240a, 240b, and 240c use the corrected exposure values to take an image of the target object to obtain a raw image for each wavelength band. The signal is transmitted to the image processing module 140 (S16).

The image processing module 140 stores the raw image signal of the first wavelength band, the raw image signal of the second wavelength band, and the raw image signal of the third wavelength band, calculates an inter-pixel correction value of each image, and calculates the calculated The pixel data corrected according to the correction value is stored (S17, S18). In this case, various pixel correction methods may be applied, such as calculating the inter-pixel correction value using the average brightness of pixel values of the image or calculating the average value of pixel values adjacent to each other in the upper, lower, left, and right directions.

The image processing module 140 generates a multi-spectral image by image synthesizing pixel data for each wavelength band and provides it to the detection module 150 ( S19 and S20 ). Accordingly, the detection module 150 may detect the vegetation index using the multi-spectral image, and monitor the type of vegetation and the biophysical state of the specific area through the detected vegetation index.

11 is a flowchart illustrating a method for detecting a vegetation index using a multi-spectral image according to a second embodiment of the present invention.

11, when the image processing module 140 transmits an image capturing command for a target object (S21), the image sensors 240a, 240b, and 240c of each wavelength band are in an Enable state ( S22).

When sunlight is incident on the solar radiation measurement module 120, the solar radiation value is output by detecting the amount of insolation for a predetermined wavelength band including all of the first wavelength band, the second wavelength band, and the third wavelength band (S23, S24).

The exposure compensation module 130 sets the exposure value of the image sensor 240a of the first wavelength band, the exposure value of the image sensor 240b of the second wavelength band, and the exposure value of the image sensor 240c of the third wavelength band, based on the insolation value. are adjusted respectively (S25).

After the exposure values of the image sensors 240a, 240b, and 240c of each wavelength band are corrected, the image sensors 240a, 240b, and 240c use the corrected exposure values to capture an image of the target object and obtain a raw image for each wavelength band. The signal is transmitted to the image processing module 140 (S26).

The image processing module 140 provides a multi-spectral image to the detection module 150 by using an image signal for each wavelength band in the same manner as in steps S17 to S20 of FIG. 10 , and the detection module 150 uses the multi-spectral image Thus, it is possible to monitor the type of vegetation and the biophysical state of a specific area by detecting the vegetation index (S27 to S30).

Meanwhile, steps S11 to S20 of FIG. 10 and steps S21 and S30 of FIG. 11 may be divided into additional steps or combined into fewer steps according to an embodiment of the present invention. In addition, some steps may be omitted if necessary, and the order between the steps may be changed.

The method for detecting vegetation index using a multi-spectral image according to an embodiment of the present invention described above may be implemented in the form of a recording medium including instructions executable by a computer, such as a program module executed by a computer. Such recording media includes computer-readable media, and computer-readable media can be any available media that can be accessed by a computer, and includes both volatile and nonvolatile media, removable and non-removable media. Computer readable media also includes computer storage media, which include volatile and nonvolatile embodied in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data. , including both removable and non-removable media.

The description of the present invention described above is for illustration, and those of ordinary skill in the art to which the present invention pertains can understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. For example, each component described as a single type may be implemented in a dispersed form, and likewise components described as distributed may also be implemented in a combined form.

The scope of the present invention is indicated by the following claims rather than the above detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be interpreted as being included in the scope of the present invention. do.

100: Vegetation index detection device using multi-spectral image
110: optical module
120: solar radiation measurement module
130: exposure compensation module
140: image processing module
150: detection module

Claims (8)

an optical module that separates light entering through one or more lenses into image signals of a plurality of wavelength bands using image sensors for each wavelength band;
a solar radiation measurement module that measures the intensity of sunlight incident from the outside and provides a solar radiation value;
an exposure compensation module for adjusting exposure values of the image sensors for each wavelength band based on the insolation value;
When an image signal of a plurality of wavelength bands is input through the image sensors for each wavelength band to which the corrected exposure value is applied, an inter-pixel correction value of an image of each wavelength band is calculated, and the correction is performed using the calculated correction value. an image processing module for storing the pixel data and then synthesizing the pixel data to provide a multi-spectral image; and
A plurality of vegetation indices are calculated using the characteristics of each wavelength band of the plurality of wavelength bands of the multi-spectral image, and the type and growth of vegetation for a corresponding area using the calculated plurality of vegetation indices. A detection module for monitoring the physical state; includes,
The plurality of wavelength bands include a visible ray wavelength band, an infrared wavelength band including near-infrared and mid-infrared rays, and an ultraviolet wavelength band,
The plurality of vegetation indices are,
a regular expression index based on the near-infrared and visible wavelength bands;
an infrared index and moisture stress index based on the near-infrared and mid-infrared wavelength bands;
a soil correction vegetation index based on a first regional value set according to the near-infrared and visible light wavelength bands and regions;
Soil Atmospheric Corrected Vegetation Index based on molecular scattering amount, ozone absorption amount, and the second regional value; and
Vegetation index detection apparatus using multi-spectral image, characterized in that it includes; improved vegetation index based on experimentally set values. According to claim 1,
The solar radiation measurement module,
Vegetation index detection apparatus using a multi-spectral image, characterized in that it includes at least one photodiode and a filter. According to claim 1,
The optical module is
a lens unit for condensing light on an image of a target target incident at a single angle of view to a preset position;
a prism arranged at different angles based on a direction in which the light passing through the lens unit is incident, and including a plurality of reflective surfaces for reflecting light of different wavelength bands to separate light for each wavelength band;
Vegetation index detection apparatus using a multi-spectral image, characterized in that it includes an image sensor for each wavelength band that converts the light of each wavelength band passing through each reflective surface of the prism into an electrical image signal and outputs it. 4. The method of claim 3,
The prism reflects light of any one wavelength band different from the visible light wavelength band, the near-infrared wavelength band, the mid-infrared wavelength band, and the ultraviolet wavelength band at a predetermined angle on each reflective surface,
The image sensor for each wavelength band is a vegetation index detection device using a multi-spectral image, characterized in that it is disposed at the end of the angle reflected through each reflective surface of the prism. In the method of detecting a vegetation index through an optical module for obtaining a multi-spectral image,
a) separating an image signal of a target object into image signals of a plurality of wavelength bands through a plurality of image sensors for each wavelength band in the optical module;
b) providing an insolation value for each wavelength band by measuring the intensity of sunlight incident from the outside;
c) adjusting exposure values of the image sensors for each wavelength band based on the insolation values for each wavelength band;
d) When an image signal of a plurality of wavelength bands is input through the image sensors for each wavelength band to which the adjusted exposure value is applied, an inter-pixel correction value of an image of each wavelength band is calculated, and the calculated correction value is used providing a multi-spectral image by synthesizing the pixel data after storing the corrected pixel data; and
e) Calculate a plurality of Vegetation Indexes using the characteristics of each of the wavelength bands of the plurality of wavelength bands of the multi-spectral image, and the type of vegetation for the corresponding area using the calculated plurality of vegetation indices and monitoring the biophysical state;
The plurality of wavelength bands include a visible ray wavelength band, an infrared wavelength band including near infrared and mid-infrared and an ultraviolet wavelength band,
The plurality of vegetation indices are,
a regular expression index based on the near-infrared and visible wavelength bands;
an infrared index and moisture stress index based on the near-infrared and mid-infrared wavelength bands;
a soil correction vegetation index based on a first regional value set according to the near-infrared and visible light wavelength bands and regions;
Soil Atmospheric Corrected Vegetation Index based on molecular scattering amount, ozone absorption amount, and the second regional value; and
A vegetation index detection method using a multi-spectral image, comprising: an improved vegetation index based on an experimentally set value. 6. The method of claim 5,
In step a), the image sensor for each wavelength band separates the image signals of different one of the visible ray wavelength band, the near infrared wavelength band, the mid-infrared wavelength band, and the ultraviolet wavelength band, respectively. Vegetation index detection method using multi-spectral images. In the method of detecting a vegetation index through an optical module for obtaining a multi-spectral image,
a) separating an image signal of a target object into image signals of a plurality of wavelength bands through a plurality of image sensors for each wavelength band in the optical module;
b) providing an insolation value of a preset wavelength band by measuring the intensity of sunlight incident from the outside;
c) adjusting exposure values of the image sensors for each wavelength band based on the insolation value of the preset wavelength band;
d) When an image signal of a plurality of wavelength bands is input through the image sensors for each wavelength band to which the adjusted exposure value is applied, an inter-pixel correction value of an image of each wavelength band is calculated, and the calculated correction value is used providing a multi-spectral image by synthesizing the pixel data after storing the corrected pixel data; and
e) Calculate a plurality of Vegetation Indexes using the characteristics of each of the wavelength bands of the plurality of wavelength bands of the multi-spectral image, and the type of vegetation for the corresponding area using the calculated plurality of vegetation indices and monitoring the biophysical state;
The plurality of wavelength bands include a visible ray wavelength band, an infrared wavelength band including near-infrared and mid-infrared rays, and an ultraviolet wavelength band,
The plurality of vegetation indices are,
a regular expression index based on the near-infrared and visible wavelength bands;
an infrared index and moisture stress index based on the near-infrared and mid-infrared wavelength bands;
a soil correction vegetation index based on a first local value set according to the near-infrared and visible light wavelength bands and regions;
Soil Atmospheric Corrected Vegetation Index based on molecular scattering amount, ozone absorption amount, and second regional value; and
A vegetation index detection method using a multi-spectral image, comprising: an improved vegetation index based on an experimentally set value. 8. The method of claim 7,
In step a), the image sensor for each wavelength band separates the image signal of any one wavelength band different from each other among the near-infrared wavelength band, the red wavelength band, the green wavelength band, and the blue wavelength band,
The step b) is a vegetation index detection method using a multi-spectral image, characterized in that measuring the insolation value of the wavelength band including all wavelength bands of the image sensor for each wavelength band.

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