JP5523427B2 - Image generation method for interpretation of feature information - Google Patents

Description

  The present invention is an image for interpreting feature information using radar image data obtained by a radar device mounted on a flying object such as an artificial satellite and capturing a wide range of the ground surface of a region to be imaged to obtain the surface condition. The present invention relates to an image generation method for interpreting feature information.

  Conventionally, there is a radar apparatus as an active sensor for measuring a reflected wave of a radio wave (microwave pulse) irradiated on the ground surface. As an example of the radar apparatus, for example, there is a synthetic aperture radar (SAR). Synthetic Aperture Radar can capture a wide area, day or night, regardless of the weather, using the characteristics of microwaves. The latest artificial satellite-borne synthetic aperture radars have a ground resolution of 1 m. In general, it is considered that a synthetic aperture radar image (hereinafter referred to as “SAR image”) taken from a platform such as an artificial satellite or an aircraft is difficult to interpret a feature due to a complicated scattering mechanism or the influence of noise.

  In a satellite with a synthetic aperture radar currently being launched, when acquiring a SAR image with multiple polarizations (dual polarization to quadrupolar polarization), for example, there are many that are restricted by, for example, resolution and imaging range. In the case of a single polarization image, there is little such restriction. However, even if a high-resolution SAR image can be obtained, the SAR image is less visible than the optical image due to the influence of a complicated scattering mechanism, etc. as described above. It is difficult to make it visible.

  On the other hand, since the optical image uses wavelengths in the visible range, the same information as that seen by the human eye can be obtained, and it has the advantage that the features can be easily read. Many optical images are color images.

  Therefore, an attempt has been made to accurately grasp the feature information by data fusion by combining the single-polarized SAR image and the optical image (see, for example, Non-Patent Document 1).

“Research on commercialization of remote sensing using synthetic aperture radar (summary)”, Research and development of system technology 17-R-6, Association for Promotion of Mechanical Systems (contractor: Research and Development Organization for Observation System for Resource Exploration), March 2006, p. 11-12

  By the way, a multi-polarized SAR image (corresponding to a multispectral image) contains more information on the features and shapes of features and helps to interpret the image. In SAR), it is generally difficult to obtain a high ground resolution because of the relationship between the data amount and the shooting range. Although a single-polarized SAR image has a high spatial resolution, the visibility is low due to the influence of a complicated scattering mechanism and the like, and it is difficult to form an image so that it can be seen by human eyes without correction.

  Up to now, a single-polarized SAR image and a multi-polarized SAR image have hardly been used as an image for interpreting feature information. The reason for this is that when a composite image is created by combining a single-polarization (high-resolution) SAR image and a multi-polarization (low-resolution) SAR image, the HSI conversion method, principal component analysis, Brovey conversion method, etc. are generally used. The lightness (I and DN values) of the multi-polarized SAR image is replaced with the lightness of the single-polarized SAR image. It is mentioned that it did not become a natural image.

  For example, it is dark in a captured image when the transmission / reception mode is HH polarization (transmission with horizontal polarization and reception with horizontal polarization), but bright with a captured image in VV polarization (transmission with vertical polarization and reception with vertical polarization). It is considered that the pixel is preferably set to an intermediate brightness. However, when the polarization mode of the unipolar SAR image is HH polarization, the brightness of the multipolarized SAR image is set to the HH polarization. If it is replaced only with the information, it becomes a dark pixel and the color (polarization information) becomes difficult to read.

  In view of such a point, an object of the present invention is to combine a high-resolution single-polarization radar image and a low-resolution multi-polarization radar image into a composite image that can easily read feature information. It is to generate.

  In order to solve the above-described problems, in the first aspect of the present invention, an image for interpreting feature information is obtained based on radar image data obtained using a polarized wave obtained from a radar device mounted on a flying object. When generating, first, color information is assigned to each of the low-resolution multi-polarization radar image data of the area photographed by the radar device. Next, the low-resolution multi-polarization radar image data to which the color information is assigned and the high-resolution single-polarization radar image data of the area photographed by the radar device are combined to produce the high-resolution color radar image data. obtain.

  According to the first aspect, color information is assigned to the low-resolution multipolarization radar image data of the area captured by the radar device, and the low-resolution multipolarization radar image data to which the color information is assigned; By synthesizing the high-resolution single-polarization radar image data of the area photographed by the radar apparatus, high-resolution synthetic radar image data having color information and easy to read is generated.

  In the second aspect of the present invention, when generating a feature information interpretation image based on radar image data obtained by using polarized waves obtained from a radar device mounted on a flying object, first, a radar is used. Low-resolution dual-polarization radar image data of a region photographed by the device and having a different transmission / reception mode is converted into a high-resolution unipolar signal having a transmission / reception mode different from the dual-polarization of the region photographed by the radar device. Sampling is performed according to the resolution of the wave radar image data. Next, color information is assigned to the sampled low-resolution dual-polarization radar image data and high-resolution single-polarization radar image data. Then, the low-resolution multipolarization radar image data to which the color information is assigned and the high-resolution single-polarization radar image data are synthesized to obtain high-resolution color radar image data.

  According to the second aspect, color information is assigned to predetermined low-resolution double-polarization radar image data sampled in accordance with the resolution of the single-polarization radar image and the high-resolution single-polarization radar image data. High resolution combined radar image data with color information that is easy to read by combining low resolution multi-polarization radar image data and high resolution single polarization radar image data to which the color information is assigned Is generated.

In the third aspect of the present invention, when generating an image for interpreting feature information based on radar image data obtained using a polarized wave obtained from a radar device mounted on a flying object, first, a radar is used. Three types of low-resolution polarization radar image data of the region captured by the apparatus and different transmission / reception modes have the same transmission / reception mode as at least one of the three types of polarization of the region captured by the radar device Sampling is performed according to the resolution of high-resolution single-polarization radar image data. Then, to extract the first first Ingredients of principal component analysis and the sampled 3 polarimetric radar image data. Furthermore, a single polarization radar image data, extracts a second first Ingredients of principal component analysis of the different dual polarized radar image data to this. Then, the first first Ingredient of those substituted and inverse principal component analysis in the second first Ingredients of generating a color radar image data of high resolution.

According to the third aspect, the single polarization first first Ingredient radar image given three sampled in accordance with the resolution of the polarization radar image data is principal component analysis is extracted, also, a single polarization radar image data, different dual polarized radar image data is the second first Ingredients are principal component analysis are extracted from this. Then, the first first Ingredients of inverse principal component analysis obtained by replacing the second first Ingredients of color radar image data of high resolution is generated.

  In the fourth aspect of the present invention, when generating the feature information interpretation image based on the radar image data obtained using the polarization obtained from the radar device mounted on the flying object, first the radar is used. Three types of low-polarization radar image data of different resolutions in the transmission / reception mode photographed by the device, and the same transmission / reception mode as that of at least one of the three polarized waves in the region photographed by the radar device. Sampling is performed in accordance with the resolution of single-polarization radar image data of resolution. Next, the sampled three types of polarization radar image data are subjected to HSI conversion to extract a first brightness component. The second polarization component is extracted by HSI conversion of the single-polarization radar image data and the dual-polarization radar image data different from the single-polarization radar image data. Then, the one obtained by replacing the first lightness component with the second lightness component is subjected to inverse HSI conversion to generate high-resolution color radar image data.

  According to the fourth aspect, the predetermined three types of polarization radar image data sampled in accordance with the resolution of the single-polarization radar image are HSI-converted to extract the first brightness component, The radar image data and the dual polarization radar image data different from the radar image data are subjected to HSI conversion, and a second brightness component is extracted. Then, the one obtained by replacing the first lightness component with the second lightness component is subjected to inverse HSI conversion, and high-resolution color radar image data is generated.

  Since high-resolution color radar image data with color information can be obtained from low-resolution multi-polarization radar image data to which color information is assigned and high-resolution single-polarization radar image data, high resolution and color It is possible to acquire information including the feature and shape of the feature, and therefore, the feature information can be interpreted with high accuracy.

It is a block diagram which shows the outline | summary of the system which concerns on one Embodiment of this invention. It is a block diagram which shows the internal structural example of the computer which concerns on one Embodiment of this invention. It is explanatory drawing which shows the concept of the feature information interpretation image generation process. It is explanatory drawing which shows the example of a color data synthesis | combination by a polarization image. It is a flowchart which shows the production | generation process example (at the time of quadruple polarization image use) by the image superimposition of the image for feature information interpretation which concerns on one Embodiment of this invention. It is a flowchart which shows the production | generation processing example by the principal component conversion method of the feature information interpretation image which concerns on one Embodiment of this invention. It is a flowchart which shows the production | generation processing example by the HSI conversion method of the feature information interpretation image which concerns on one Embodiment of this invention.

Hereinafter, an example of an embodiment for carrying out the present invention will be described with reference to the accompanying drawings. The description will be given in the following order.
1. First embodiment (example of image composition processing by image superimposition)
2. Second embodiment (example of image composition processing by principal component conversion method)
3. Third Embodiment (Example of image composition processing by HSI conversion method)

<1. First Embodiment>
Hereinafter, an embodiment of the present invention will be described with reference to the accompanying drawings.

  Since the embodiments described below are preferred specific examples of the present invention, various technically preferable limitations are given. However, the scope of the present invention is particularly limited in the following description. Unless otherwise stated, the present invention is not limited to these forms. For example, the materials used in the following description, the amount used, the processing time, the processing order, and the numerical conditions of each parameter are only suitable examples, and the dimensions, shapes, and arrangement relationships in the drawings used for the description are also schematic. It is a thing.

  FIG. 1 shows an overview of a system according to an embodiment of the present invention. In this system, a synthetic aperture radar (SAR: Synthetic Aperture Radar) is mounted on an artificial satellite as an example of a radar device, and the ground surface is photographed (based on an instruction from the data analysis center 2) by the synthetic aperture radar. is there. Hereinafter, the synthetic aperture radar mounted on the artificial satellite is referred to as “satellite SAR”.

  In FIG. 1, the satellite SAR1 shoots the ground surface 3 periodically or while following a predetermined orbit and transmits the photographic data (SAR image data) to the data analysis center 2 at any time according to an instruction from the data analysis center 2. To do.

  The data analysis center 2 makes a shooting plan and transmits a radio signal of a shooting instruction based on the shooting plan to the satellite SAR1. Also, SAR image data captured by the satellite SAR1 is received via an antenna. A reproduced image is generated by performing synthetic aperture processing on the feature information interpretation image generating apparatus 10 described later. Then, synthesis processing of high-resolution single-polarized SAR image data and low-resolution multi-polarized SAR image data is performed. At this time, color information of red (R), green (G), and blue (B) is appropriately assigned to the low-resolution multi-polarization SAR image data. As a result, high-resolution color SAR image data is obtained as image data after the synthesis process.

  A series of processing by the feature information interpretation image generating apparatus 10 can be executed by hardware or can be executed by software. When a series of processing is executed by software, a program constituting the software executes various functions by installing a computer incorporated in dedicated hardware or various programs. For example, the program is installed in a general-purpose computer from a program recording medium.

  FIG. 2 is a block diagram illustrating a configuration example of the feature information interpretation image generating apparatus 10 that executes the above-described series of processing by a program. The feature information interpretation image generation apparatus 10 may be, for example, a personal computer having a certain performance in addition to a dedicated computer with high performance for executing a series of processes.

  A CPU (Central Processing Unit) 11 of the feature information interpretation image generation apparatus 10 performs various processes in addition to the above-described series of processes according to a program recorded in a ROM (Read Only Memory) 12 or a recording unit 18. Run. A RAM (Random Access Memory) 13 appropriately stores programs executed by the CPU 11 and data. The CPU 11, ROM 12, and RAM 13 are connected to each other by a bus 14.

  An input / output interface 15 is also connected to the CPU 11 via the bus 14. The input / output interface 15 is connected to an input unit 16 including a keyboard, a mouse, and a microphone, and an output unit 17 including a display and a speaker. The CPU 11 executes various processes in response to commands input from the input unit 16. Then, the CPU 11 outputs the processing result to the output unit 17.

  The recording unit 18 connected to the input / output interface 15 includes, for example, a hard disk, and records programs executed by the CPU 11 and various data.

  The communication unit 19 communicates with an external device via a network such as the Internet or a local area network. A program may be acquired via the communication unit 19 and recorded in the recording unit 18.

  The drive 20 connected to the input / output interface 15 includes a magnetic disk (including a flexible disk), an optical disk (including a CD-ROM (Compact Disc-Read Only Memory), a DVD (Digital Versatile Disc), a magneto-optical disk, etc.). Alternatively, when a removable medium 31 such as a semiconductor memory is loaded, it is driven to acquire programs and data recorded therein. The acquired program and data are transferred to the recording unit 18 and recorded as necessary.

  As shown in FIG. 2, a program recording medium that stores a program that is installed in a computer and can be executed by the computer is a removable medium 31 that is a package medium made of a magnetic disk, an optical disk, a semiconductor memory, or the like. The ROM 12 stores the program temporarily or permanently, the hard disk constituting the recording unit 18, and the like. The program is stored in the program recording medium using a wired or wireless communication medium such as a local area network, the Internet, or digital satellite broadcasting via a communication unit 19 that is an interface such as a router or a modem as necessary. You may go.

  Here, with reference to FIG. 3, the high-resolution color SAR image composition processing, which is a basic concept of the feature information interpretation image generation processing example by the CPU 11 of the feature information interpretation image generation apparatus 10, will be described.

  The high-resolution color SAR image composition processing is monochrome (black and white), but image data obtained with fine spatial density (high resolution), and color information (for example, R, G, etc.) with a coarse spatial density (low resolution). , B) is a process of obtaining image data having color information with a high spatial density by synthesizing the image data acquired as B). In the feature information interpretation image generation method of the present invention, color composite image data in the high-resolution color SAR image composition processing is acquired by color image composition using a polarization image. Then, the color composite image data and the high-resolution single-polarized SAR image data are combined.

  The color image synthesis process using the polarization image will be described with reference to FIG. Four types of polarization images having different transmission / reception modes, that is, a quadruple polarization image of HH polarization, HV polarization, VH polarization, and VV polarization are acquired. These are simultaneously photographed as polarization images by photographing the polarization of the satellite SAR1 in this embodiment, and each is a monochrome image. By combining these layers (layer stack) and assigning color information (RGB color gun) to each layer, it is possible to obtain a color composite image in which the features of the ground surface state (feature state) are displayed in color.

  The selection / combination of polarization modes can be freely changed. For example, VV polarization is a single polarization image (high resolution), HH polarization (R), VV polarization (G) and VH polarization (B) are color composite images (low resolution), or HH The polarization is a single polarization image (high resolution), and the HV polarization (R), VH polarization (G), and HH polarization (B) are color composite images (low resolution).

  Next, an example of generation processing of the feature information interpretation image by the CPU 11 of the feature information interpretation image generation apparatus 10 will be described with reference to the flowchart of FIG. The feature information interpretation image generation processing example shown in FIG. 5 uses a quadrupolar polarization image (SAR image data of four different types of polarization modes), and image composition processing (pan sharpening processing) by image superposition. This is an example when

  First, the feature information interpretation image generation apparatus 10 acquires high-resolution single-polarization SAR image data of an arbitrary region photographed by the satellite SAR1. In this example, the single polarization mode is assumed to be HH polarization, that is, horizontal / horizontal polarization (step S1a).

  Further, low-resolution multipolarization SAR image data including a part or all of an arbitrary region photographed by the satellite SAR1 is acquired (step S1b). In this example, SAR images of four types of polarization modes, HH polarization, HV polarization, VH polarization, and VV polarization are acquired.

  In the processes of step S1a and step S1b, the image data may be received from the satellite SAR1 or a radio signal including the shooting data, or may be acquired from the removable medium 31 on which the shooting data is recorded. Moreover, the processing order of step S1a and step S1b is not ask | required. For example, when the satellite SAR1 cannot simultaneously capture a high-resolution single-polarization SAR image and a low-resolution multi-polarization SAR image, the high-resolution single-polarization SAR image is first captured, and the same orbit is observed several days later. Alternatively, a low-resolution multi-polarized SAR image is taken on substantially the same orbit. Of course, the reverse order may be used.

  Next, the low resolution multi-polarized SAR image obtained by the process of step S1b is resampled in accordance with the resolution of the single-polarized SAR image (step S2). At this time, it is preferable to exclude low-resolution SAR images taken in the same polarization mode (in this example, HH polarization) as the high-resolution single-polarization SAR image.

  Then, ortho images are respectively created (orthorectified) for the high-resolution single-polarized SAR image obtained by the process of step S1a and the low-resolution multi-polarized SAR image obtained by the process of step S1b (steps S3a and S3b). That is, the height of the ground surface and structure such as DEM (Digital Elevation Model) obtained from radar grammure processing or interferometry processing using a plurality of (for example, two) SAR images or obtained from the Geographical Survey Institute, etc. Based on the information, an orthographic projection image (ortho image) of the SAR image is created. By creating a DEM from the SAR image, distortion correction of the SAR image can be performed accurately. In addition, if the high-resolution single-polarized SAR image and the low-resolution multi-polarized SAR image are taken from the same position on the same orbit, the incident angle with respect to the photographing region is the same, so it is not always orthorectified. May be.

  Subsequently, a filtering process is performed on each SAR image to remove noise (steps S4a and S4b). Note that the processing order of steps S3a and S4a or steps S3b and S4b is not limited to this example, and may be reversed. Further, since the filtering process is a known technique, the description thereof is omitted here.

  After the noise removal processing is completed, the low resolution multi-polarized SAR image is assigned to the RGB color gun to generate a low resolution color SAR image (step S5). In this embodiment, first, a quadruple-polarized SAR image is resampled in accordance with the resolution of a single-polarized SAR image to increase the resolution. At this time, as described above, it is preferable to exclude the same layer as the single-polarization SAR image (in this example, the SAR image in the HH polarization mode). Alternatively, three polarization modes may be selected by principal component analysis or the like. The obtained three polarization modes (for example, HH polarization, VV polarization, and HV polarization) are assigned to RGB color guns to generate a low-resolution color SAR image.

  Next, the high-resolution single-polarized SAR image obtained by the process of step S4a and the low-resolution color SAR image obtained by the process of step S5 are aligned (step S6). The alignment can be performed, for example, by correcting geometric information (geometry) at the same ground control point (GCP). Finally, these images are pan-sharpened (synthesized) (step S7) to obtain a high-resolution color SAR image (step S8).

  Here, a case has been described in which SAR images of four types of polarization modes, HH polarization, HV polarization, VH polarization, and VV polarization are acquired as low-resolution multi-polarization SAR image data. Single-polarization SAR image data and image data (SAR image) of two different polarization modes (for example, VH polarization and VV polarization) are assigned to RGB color guns, respectively, and pan-sharpening processing is performed. It is also possible.

  As described above, when a high-resolution single-polarization SAR image and a low-resolution dual-polarization SAR image are combined, a quadruple-polarization SAR image can be obtained without photographing in the quadrupolarization mode. Polarization information similar to that used is obtained. That is, a high-resolution SAR image can be obtained simultaneously with a plurality of polarization information.

<2. Second Embodiment>
As described above, the pan sharpening process by superimposing two SAR images having different resolutions has been described. However, the pan sharpening process can also be performed by the principal component conversion method.
Hereinafter, the pan sharpening process by the principal component conversion method will be described with reference to FIG. First, the feature information interpretation image generation apparatus 10 acquires high-resolution single-polarization SAR image data of an arbitrary region photographed by the satellite SAR1. In this example, it is assumed that the polarization mode of single polarization is HH polarization, that is, horizontal / horizontal polarization (step S11a).

  Further, low-resolution multipolarized SAR image data including a part or all of an arbitrary region photographed by the satellite SAR1 is acquired (step S11b). In this example, SAR images of four polarization modes, HH polarization, HV polarization, VH polarization, and VV polarization are acquired.

  In the processing of step S11a and step S11b, the image data may be received from the satellite SAR1 or a radio signal including shooting data, or may be acquired from the removable medium 31 on which shooting data is recorded. Moreover, the processing order of step S11a and step S11b is not ask | required. For example, when the satellite SAR1 cannot simultaneously capture a high-resolution single-polarized SAR image and a low-resolution multi-polarized SAR image, the high-resolution single-polarized SAR image is first captured, and a few days later. A low-resolution multi-polarized SAR image is taken on the same or substantially the same orbit. Of course, the reverse order may be used.

  Next, the low resolution multi-polarized SAR image obtained by the process of step S11b is resampled in accordance with the resolution of the single-polarized SAR image (step S12). At this time, it is preferable to exclude the SAR image captured in the same polarization mode (HH polarization in this example) as the high-resolution single-polarization SAR image. Then, the single-polarization SAR image data obtained in step S11a and the low-resolution multi-polarization SAR image obtained in step S12 are orthorectified (step S13a, step S13b) and noise-removed (step S14a), respectively. After performing step S14b), the two are aligned to synthesize an image (step S15).

  Next, a principal component analysis is performed on the composite image obtained by the process of step S15, and a first component (PC1) is extracted (step S16). The first component (PC1) and the low-resolution SAR image obtained by the processing in step S14b are pan-sharpened by the principal component conversion method (step S17). That is, as a hue extraction process, a low-resolution SAR image is subjected to principal component analysis, and the obtained first component (PC1 ') is replaced with the PC1. At this time, it is preferable to perform histogram conversion so that the histogram of PC1 matches the histogram of PC1 '. This is subjected to inverse principal component analysis to obtain a high-resolution color SAR image (step S18).

<3. Third Embodiment>
In the processing of step S16 and step S17 in the second embodiment, principal component analysis and inverse principal component analysis are performed, but an HSI (Hue Saturation-Intensity) conversion method may be used instead. In HSI conversion, the color monitor of an image is changed from the RGB color space of red, green and blue (RGB: three primary colors) to Hue (Hue), Saturation (S), and Intensity (I). To the HSI space. Further, after adjusting the hue, saturation, and brightness of the output image in the HSI space, it can be returned to the RGB space by inverse transformation, and a color composite image can be displayed.

  In this case, as a lightness extraction process, three polarization modes (VV polarization mode and HV polarization mode) that are different from high-resolution single polarization (HH polarization mode) in the SAR image of quadrupolar polarization first. , VH polarization mode) is resampled according to the high resolution of single polarization (HH polarization mode). Next, SAR images of two polarization modes (VV polarization mode, HV polarization mode) and high resolution single polarization (HH polarization mode) SAR images that have been resampled to increase the resolution are HSI converted. Then, the brightness of each is extracted. Next, the brightness (I ′) obtained from the SAR images in the two polarization modes is replaced with the brightness (I) of the high-resolution single-polarization SAR image, and this is subjected to inverse HSI conversion, thereby performing pan-sharpening processing. A high resolution color SAR image is obtained. On the other hand, three polarization modes (HH polarization, VV polarization, and HV polarization) obtained by inverse HSI conversion are assigned to RGB color guns to generate a high-resolution color SAR image. At this time, it is preferable to perform histogram conversion so that the histogram of I matches the histogram of I ′.

  Hereinafter, pan-sharpening processing by the HSI conversion method will be described with reference to FIG. FIG. 7 is a flowchart illustrating an example of processing for generating a feature information interpretation image by the CPU 11 of the feature information interpretation image generation apparatus 10. In FIG. 7, detailed description of the same processing steps as those in FIG. 6 is omitted.

  First, the feature information interpretation image generation apparatus 10 acquires high-resolution single-polarization SAR image data of an arbitrary region photographed by the satellite SAR1. In this example, it is assumed that the polarization mode of single polarization is HH polarization, that is, horizontal / horizontal polarization (step S21a).

  Further, low-resolution multipolarized SAR image data including a part or all of an arbitrary region photographed by the satellite SAR1 is acquired (step S21b). In this example, it is assumed that the SAR image is acquired in four types of polarization modes of HH polarization, HV polarization, VH polarization, and VV polarization.

  The processing in step S21a and step S21b may be performed by receiving a radio signal including shooting data from the satellite SAR1 or acquiring it from the removable medium 31 on which shooting data is recorded. Moreover, the processing order of step S21a and step S21b is not ask | required.

  Next, four types of low-resolution polarization (HH polarization, HV polarization, VH polarization, VV polarization) SAR images obtained by the processing in step S21b are converted into single polarization (HH polarization). Resampling is performed to obtain the same resolution as that of the SAR image, and four types of high-resolution polarization SAR images are generated (step S22). At this time, it is preferable to exclude the SAR image captured in the same polarization mode (HH polarization in this example) as the high-resolution single-polarization SAR image.

  Next, an ortho image is created (orthorectified) for each of the high-resolution single-polarized SAR image obtained in step S21a and the low-resolution multi-polarized SAR image obtained in step S22 (steps S23a and S23b). . As in the above-described embodiment, if the high-resolution single-polarized SAR image and the low-resolution dual-polarized SAR image are taken from the same position on the same trajectory, the incident angle with respect to the shooting area is also set. Since it becomes the same, it does not necessarily need to be orthorectified.

  Subsequently, noise removal is performed on each SAR image by filtering processing (steps S24a and S24b). Note that the processing order of steps S23a and S24a and steps S23b and S24b is not limited to this example, and may be reversed.

  Then, the single-polarized SAR image obtained in step S24a and the low-resolution multi-polarized SAR image obtained by the processing in step S24b are aligned, and the images are synthesized (step S25). Next, HSI conversion is performed on the composite image obtained by the process of step S25, and brightness (I) is extracted (step S26). A pan-sharpening process is performed using this and the low-resolution SAR image obtained by the process of step S24b (step S27). That is, the low-resolution SAR image obtained in the process of step S24b is HSI-converted, the obtained brightness (I ′) is replaced with the above I, and this is inverse-HSI-converted to convert the high-resolution color SAR image. Obtain (step S28).

  According to the embodiment described above, since a high-resolution single-polarized SAR image and a quadruple-polarized SAR image having a slightly lower resolution are obtained and a color composite image is obtained, the ground can be more easily obtained. Interpretation of object information becomes possible. Furthermore, instead of using only a high-resolution single-polarized SAR image, a low-resolution multi-polarized (quadruplex) SAR image is used together to create a high-resolution brightness layer. It is used for pan sharpening. In this way, a color composite image can be created by combining polarization information obtained from a low-resolution multi-polarization (quad-polarization) SAR image based on a high-resolution single-polarization SAR image. As a result, it is possible to obtain a color image including information with high resolution and including features and shapes of features. Therefore, the feature information can be read more accurately.

  As an application example, for example, a high-resolution single-polarization SAR image and a low-resolution multi-polarization SAR image taken on different orbits are orthorectified, and image synthesis is performed using these, thereby, for example, occlusion of a building. Can be reduced.

  DESCRIPTION OF SYMBOLS 1 ... Satellite SAR, 2 ... Data analysis processing center, 3 ... Ground surface (photographing object), 4, 5 ... Accumulated pixel number, 10 ... Image generating apparatus for interpretation of feature information, 11 ... CPU, 12 ... ROM, 13 ... RAM, 14 ... bus, 15 ... input / output interface, 16 ... input unit, 17 ... output unit, 18 ... recording unit, 19 ... communication unit, 20 ... drive, 31 ... removable media

Claims (3)

In a feature information interpretation image generation method for generating a feature information interpretation image based on radar image data obtained using a polarized wave obtained from a radar device mounted on a flying object,
Low resolution dual polarization radar image data of a region photographed by the radar device and having a different transmission / reception mode is a high resolution that is a transmission / reception mode different from the dual polarization of the region photographed by the radar device. Sampling according to the resolution of the single polarization radar image data of
Assigning color information to the sampled low resolution dual polarization radar image data and the high resolution single polarization radar image data;
A feature information interpretation image generation method comprising: synthesizing low-resolution dual- polarization radar image data to which the color information is assigned and high-resolution single-polarization radar image data. In a feature information interpretation image generation method for generating a feature information interpretation image based on radar image data obtained using a polarized wave obtained from a radar device mounted on a flying object,
Three types of low-resolution polarization radar image data in different transmission / reception modes in the area photographed by the radar device, and at least one of the three types of polarization / transmission mode in the area photographed by the radar device. Sampling to match the resolution of the same high resolution single polarization radar image data;
Extracting a first first Ingredients of principal component analysis three polarization radar image data said sampling,
Wherein the single polarization radar image data, extracting a first Ingredient second principal component analysis of the different dual polarized radar image data thereto,
Wherein the first first Ingredients of inverse principal component analysis obtained by substituting in the second first Ingredients of feature information reading image producing method comprising the step of generating image data. In a feature information interpretation image generation method for generating a feature information interpretation image based on radar image data obtained using a polarized wave obtained from a radar device mounted on a flying object,
Three types of low-resolution polarization radar image data in different transmission / reception modes in the area photographed by the radar device, and at least one of the three types of polarization / transmission mode in the area photographed by the radar device. Sampling to match the resolution of the same high resolution single polarization radar image data;
Extracting the first brightness component by performing HSI conversion on the three types of sampled polarization radar image data;
HSI conversion of the single polarization radar image data and the dual polarization radar image data different from the single polarization radar image data to extract a second brightness component;
A feature information interpretation image generation method comprising: performing inverse HSI conversion on the first lightness component replaced with the second lightness component and generating image data.

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