JP6656132B2 - Imaging management device and imaging management program - Google Patents

Description

  The present invention relates to a technique for determining a set value to be set in an imaging device.

  Optical imaging systems are used not only in consumer equipment such as digital cameras, but also in a wide range of fields.

For example, in the field of remote sensing, an optical imaging system is used. Specifically, an optical imaging system is mounted on an artificial satellite to observe the ground surface or outer space. Artificial satellites are equipped with sensors other than visible light (such as infrared light) as well as visible light sensors.
In the field of remote sensing, an image obtained by photographing the ground from an imaging system mounted on an artificial satellite is called a satellite image.

  GSD (Ground Sampling Distance) indicates a resolution equivalent to one pixel so that an object reflected in the satellite image can be analogized.

  The value indicated by the GSD is a value obtained by processing such as the performance of the imaging system, the altitude of the artificial satellite, the imaging angle of the imaging system, or resampling. If the numerical value is unknown, the numerical value may be estimated based on the satellite image, but usually, a design value designed in advance is used.

  On the other hand, there is an index value obtained by evaluating a satellite image.

  For example, three white lines called Tri-bar are photographed as a calibration pattern, and the photographed image is evaluated based on whether or not the photographed Tri-bar appears to be separated into three lines. Then, a GRD (Ground Resolved Distance) indicating the resolution is obtained.

  GRD evaluation does not require special knowledge and training, and GRD evaluation is relatively easy. It is relatively easy to photograph a Tri-bar in a laboratory or the like.

  However, it is not easy to photograph the Tri-bar drawn at the calibration point on the ground from an artificial satellite in a satellite orbit because the photographing points (latitude and longitude) are limited.

  Further, as an evaluation in terms of what information can be obtained from a satellite image, there is a concept of readability (Interpretability).

  Regarding readability, an index called NIIRS (National Imagery Interpretability Rating Scale) has been established and widely used in the United States. In general, NIRS is translated as a US Image Readability Index.

  Non-Patent Document 1 discloses a description of NIIRS.

  The evaluation by the NIIRS is performed from the viewpoint of whether an object serving as a reference (Criteria) can be detected, distinguished, or identified from an image.

  The NIIRS evaluation requires knowledge and training because the evaluator needs to understand the criteria, so the NIIRS evaluation requires knowledge and training.

  Since the information obtained from an image is defined and quantified, the NIRS is often used to indicate the characteristics of an image.

  Patent Literature 1 discloses an example in which, in a method in which an unmanned aerial vehicle automatically collects information, an NIIRS is used as one of information required for determining a route for collecting information.

  In addition to the evaluation using criteria, a subjective evaluation that asks the evaluator's preference can be considered.

  When an image is evaluated subjectively, it may be affected by a difference in preference, and thus it is considered that the evaluation result varies depending on the evaluator.

  For example, when an image displayed on a display device such as a television or a monitor is evaluated, some evaluators prefer an image with a vivid color (that is, an image with high saturation). On the other hand, as a result of the vivid color, the color of the subject shown in the image is different from the memory color, and some evaluators do not like the image. The memory color is a hue imaged for a subject.

  For these reasons, the setting values of the parameters related to the image can often be adjusted by the user himself according to his or her individual preference. In display devices and imaging devices, there are many parameters whose setting values can be adjusted.

  In addition, parameters are initially set for a user who does not adjust the set values. For example, a standard mode in which a recommended value is used as a set value is provided.

  When subjective evaluations are used in examining recommended values, setting values preferred by many evaluators are often recommended values. In the subjective evaluation, it is desirable that the evaluation be performed by a sufficient number of people. As the number of evaluators increases, the effect of the difference in preference decreases, and reproducible evaluation results can be obtained.

  ITU (International Telecommunication Union), which is one of the international standardization organizations, recommends a methodology relating to subjective quality evaluation of video.

  In the recommendation “Subjective evaluation method of BT.500 TV video quality” regarding the subjective evaluation of video, it is recommended that the evaluation experiment be performed by at least 15 or more non-experts. A non-specialist is a person who is not engaged in tasks related to the quality of TV images as daily tasks.

  Thus, many subjects are required for the subjective evaluation. In addition, resources related to evaluation tend to increase.

  Extensive equipment and planning are required to obtain satellite images. Therefore, in a situation where it is difficult to obtain a satellite image, or in a stage before launch, evaluation is often performed using a simulation image simulating a satellite image. The same applies to the evaluation of NIIRS and GRD.

  As described above, there is a demand for a method capable of examining a setting value for photographing based on a satellite image or a simulation image in an efficient manner.

  Since GRD and NIIRS are generally positioned as a scale for evaluating an image, few attempts have been made to reflect the GRD and NIIRS values in an imaging system.

JP 2007-526175 A

John M. Irvine, "National Imagery Interpretability Rating Scales (NIRS): Overview and Methodology", in Proc. SPIE 3128, Airborne Reconnanceance XXI

  An object of the present invention is to be able to determine a preferable setting value as a value to be set in an imaging device.

The imaging management device of the present invention includes:
Based on a plurality of readability evaluation values obtained by evaluating a plurality of readability evaluation images which are a plurality of images evaluated for readability and a plurality of images having different readability parameter values, readability evaluation is performed. A first relational expression generation unit that generates a first relational expression that indicates a relation between the value and the value of the legibility parameter;
Based on a plurality of resolution evaluation values obtained by evaluating a plurality of resolution evaluation images that are a plurality of images evaluated for resolution and a plurality of images having different resolution parameter values, a resolution evaluation value and a resolution parameter A second relational expression generation unit that generates a second relational expression indicating a relation with the value,
A setting value determination unit that determines a setting value to be set for an imaging parameter based on the first relational expression and the second relational expression.

  According to the present invention, it is possible to determine a preferable setting value as a value to be set in the imaging device.

FIG. 1 is a configuration diagram of an imaging management apparatus 100 according to Embodiment 1. 5 is a flowchart of an imaging management method according to the first embodiment. FIG. 4 is a diagram showing the relationship between legibility evaluation images Is according to the first embodiment. 5 is a relation table between legibility evaluation value Nd and representative value Ns according to the first embodiment. FIG. 4 is a diagram illustrating a relationship between the legibility evaluation image Is and a first relational expression Fn according to the first embodiment. FIG. 3 is a diagram showing a white line pattern Tb according to the first embodiment. 6 is a table showing a relationship between a resolution evaluation value Gd and a representative value Gs according to the first embodiment. FIG. 4 is a diagram illustrating a relationship between a resolution evaluation image Gs and a second relational expression Fg according to the first embodiment. 9 is a flowchart of a set value determination process (S130) according to the first embodiment. FIG. 4 is an explanatory diagram illustrating a method for calculating a first candidate TiN according to the first embodiment. FIG. 4 is an explanatory diagram illustrating a method for calculating a second candidate TiG according to the first embodiment. 5 is a graph showing a relationship between a first candidate TiN, a second candidate TiG, and a set value Pti according to the first embodiment. 5 is a graph showing a relationship between a first candidate TiN, a second candidate TiG, and a set value Pti according to the first embodiment. FIG. 2 is a hardware configuration diagram of the imaging management apparatus 100 according to the embodiment.

  In the embodiments and the drawings, the same reference numerals are given to the same elements or the elements corresponding to each other. The description of the elements denoted by the same reference numerals will be omitted or simplified as appropriate. The arrows in the figure mainly indicate the flow of data or processing.

Embodiment 1 FIG.
A mode for determining a set value set in the imaging device will be described with reference to FIGS.
*** Configuration description ***
The configuration of the imaging management device 100 will be described based on FIG.

  The imaging management device 100 is a computer that determines a setting value set in the imaging device.

  The imaging management device 100 is a computer including hardware such as a processor 901, a memory 902, an auxiliary storage device 903, an input device 904, an output device 905, and a communication device 906. These pieces of hardware are connected to each other via signal lines.

  The processor 901 is an IC (Integrated Circuit) that performs processing, and controls other hardware. Specifically, the processor 901 is a CPU, a DSP, or a GPU. CPU is an abbreviation for Central Processing Unit, DSP is an abbreviation for Digital Signal Processor, and GPU is an abbreviation for Graphics Processing Unit.

  The memory 902 is a volatile storage device. The memory 902 is also called a main storage device or a main memory. Specifically, the memory 902 is a RAM (Random Access Memory).

  The auxiliary storage device 903 is a nonvolatile storage device. Specifically, the auxiliary storage device 903 is a ROM, a HDD, or a flash memory. ROM is an abbreviation for Read Only Memory, and HDD is an abbreviation for Hard Disk Drive.

  Hardware in which the processor 901, the memory 902, and the auxiliary storage device 903 are combined is referred to as “processing circuitry”.

  The input device 904 is an interface that receives an input. Specifically, the input device 904 is a keyboard, a mouse, a numeric keypad, or a touch panel.

  The output device 905 is an interface that outputs data. Specifically, the output device 905 is a display device that displays an image or the like. The display device is called a display or a monitor.

  The communication device 906 is a device that performs communication, and includes a receiver and a transmitter. Specifically, the communication device 906 is a communication chip or a NIC (Network Interface Card).

  The imaging management device 100 includes a first image generation unit 111, a first evaluation value acquisition unit 112, a first relational expression generation unit 113, a second image generation unit 121, a second evaluation value acquisition unit 122, and a second relational expression generation unit. “Units” such as 123 and a set value determination unit 130 are provided as elements of the functional configuration. The function of the “section” is realized by software. The function of the “section” will be described later.

  The auxiliary storage device 903 stores a program for realizing the function of the “unit”. A program for realizing the function of the “unit” is loaded into the memory 902 and executed by the processor 901.

  Further, the auxiliary storage device 903 stores an OS (Operating System). At least a part of the OS is loaded into the memory 902 and executed by the processor 901.

  That is, the processor 901 executes a program that realizes the function of the “unit” while executing the OS.

  Data obtained by executing a program realizing the function of the “unit” is stored in a storage device such as the memory 902, the auxiliary storage device 903, a register in the processor 901 or a cache memory in the processor 901.

  The memory 902 functions as a storage unit 191 that stores data used by the imaging management apparatus 100. However, another storage device may function as the storage unit 191.

  The communication device 906 functions as a communication unit that communicates data. In the communication device 906, the receiver functions as a receiving unit that receives data, and the transmitter functions as a transmitting unit that transmits data.

  The input device 904 functions as a receiving unit that receives an input.

  The output device 905 functions as an output unit that outputs data. A display serving as the output device 905 functions as a display unit that displays an image or the like.

  The imaging management device 100 may include a plurality of processors instead of the processor 901. The plurality of processors share execution of a program that implements the function of the “unit”.

  The program for realizing the function of the “unit” can be stored in a non-volatile storage medium such as a magnetic disk, an optical disk or a flash memory in a computer-readable manner. Non-volatile storage media are non-transitory tangible media.

“Part” may be read as “processing” or “step”. The function of the “unit” may be realized by firmware.
*** Explanation of operation ***
The operation of the imaging management apparatus 100 corresponds to an imaging management method. The procedure of the imaging management method corresponds to the procedure of the imaging management program.

  An imaging management method will be described based on FIG.

  Step S111 is a first image generation process.

  In step S111, the first image generation unit 111 generates a plurality of legibility evaluation images by processing the first original image based on the imaging condition information.

  The imaging condition information is information indicating conditions at the time of imaging. Specifically, the imaging condition information indicates a plurality of sets of the total integration time and the solar altitude as imaging conditions. The total integration time and the solar altitude will be described later. In addition, the imaging condition information includes various information for generating an image, such as characteristics of the optical system, the presence or absence of image correction processing, and the presence or absence of compression processing. The characteristics of the optical system include noise characteristics or MTF (Modulation Transfer Function) characteristics.

  The first original image is an image that is a source of a plurality of legibility evaluation images. The first original image is preferably a high-resolution and high-definition image. A simulation image or an aerial image can be used as the first original image. The simulation image is an image created from three-dimensional model data of the ground and the object. An aerial image is an image obtained by imaging from an aircraft.

  The plurality of readability evaluation images are a plurality of images that are evaluated for readability and have different readability parameter values. A specific index for evaluating readability is NIIRS.

  The legibility parameter is a parameter related to legibility. Specific legibility parameters will be described later.

  Specifically, the first image generation unit 111 operates as follows.

  First, the first image generation unit 111 extracts imaging condition information from the generation condition information. The generation condition information is information including imaging condition information, parameter condition information, and the like. The parameter condition information will be described later.

  Then, for each set of the total integration time and the sun altitude indicated in the imaging condition information, the first image generation unit 111 processes the first original image according to the total integration time and the sun altitude of the set. , And generates a legibility evaluation image corresponding to the set.

  The generation condition information and the first original image are prepared by the administrator and stored in the storage unit 191 in advance via the input device 904 or the communication device 906.

  The relationship among the total integration time Ti, the solar altitude Se, and the legibility evaluation image Is will be described with reference to FIG.

  a, b, c and d indicate the total integration time Ti, and A and B indicate the solar altitude Se. Is_Xy indicates the readability evaluation image Is corresponding to the set of the total integration time y and the solar altitude X.

  The total integration time Ti is a time for capturing light into the image sensor.

  The longer the total integration time Ti is, the longer the light enters the image sensor, and the shorter the total integration time is, the shorter the light enters the image sensor.

  If the total integration time Ti is longer, more light is incident on the image sensor. Therefore, an image obtained when the total integration time Ti is longer is brighter than an image obtained when the total integration time Ti is shorter. As a result, as the total integration time Ti increases, the SNR (signal-to-noise ratio), which is the ratio between the signal amount and the noise amount, increases, and the image contrast improves.

  On the other hand, since the subject and the image sensor have movement, if the total integration time Ti becomes longer, the influence of blurring becomes stronger. As a result, the longer the total integration time Ti, the smaller the REL (Relative Edge Response) representing the sharpness of the contour of the subject in the image.

  As described above, when the total integration time Ti increases, the SNR tends to improve, while the RR tends to deteriorate. When the total integration time Ti decreases, the RR tends to improve while the SNR deteriorates.

  Therefore, it is important that the total integration time Ti set in the imaging device is determined so that the balance between SNR and RER is improved.

  SNR and RER corresponding to the total integration time Ti are values that can be calculated by a known method based on the characteristics of the optical system described above. The SNR and the RER are calculated for each evaluation image having different imaging conditions.

  The legibility evaluation image Is_Aa having a short total integration time Ti has better contour sharpness and lower brightness than the legibility evaluation images Is_Ab, Is_Ac, and Is_Ad. That is, RER is large and SNR is small.

  The legibility evaluation image Is_Ad having a long total integration time Ti has poorer contour sharpness and higher brightness than the legibility evaluation images Is_Aa, Is_Ab, and Is_Ac. That is, RER is small and SNR is large.

  The solar altitude Se is the altitude of the sun at the point where imaging is performed.

  When the solar altitude is high, such as in the middle of the day or the summer solstice in a year, the sun's irradiation brightens the ground surface. As a result, the amount of light entering the image sensor increases.

  Conversely, when the solar altitude is low, such as during the winter solstice in a year, the amount of light entering the image sensor decreases.

  The readability evaluation image Is_nd having a low solar altitude Se has lower brightness than the readability evaluation images Is_Ad and Is_Bd. That is, the SNR is small.

  The readability evaluation image Is_Ad having a high solar altitude Se has higher brightness than the readability evaluation images Is_Bd and Is_nd. That is, the SNR is large.

  In the first original image and the plurality of legibility evaluation images, an object serving as a reference (Criteria) for evaluating NIIRS is shown.

  The target object may be an object reflected in a normal aerial image, such as a building, a car, a railway, and the like.

  On the other hand, it is difficult to determine an image that is composed only of a landscape such as a desert or the sea and does not include much criteria for determining NIIRS. Such an image is not suitable as a first original image and a plurality of legibility evaluation images.

  Note that, together with the first original image, information generally included as metadata in the image, such as a file format, the number of pixels, and the number of bits, is stored in the storage unit 191 as information about the first original image. Further, analysis information obtained by analyzing the first original image may be stored in the storage unit 191 together with the first original image.

  Returning to FIG. 2, step S112 will be described.

  Step S112 is a first evaluation value acquisition process.

  In step S112, the first evaluation value acquisition unit 112 acquires a plurality of legibility evaluation values for a plurality of legibility evaluation images.

  Specifically, the first evaluation value acquisition unit 112 displays a plurality of legibility evaluation images on a display, and receives a plurality of legibility evaluation values for the plurality of legibility images. The display on which the plurality of readability evaluation images are displayed may be either the display of the imaging management device 100 or an external display.

  The legibility evaluation value is a value obtained by evaluating a legibility evaluation image for legibility. A specific legibility evaluation value is an NIIRS value. The NIIRS value is a value obtained by evaluating a legibility evaluation image for NIIRS. The NIIRS value is an integer in increments of 1 in the range of 0 to 9. However, the NIIRS value may be a value in increments of 0.5 or in increments of 0.1. That is, the NIIRS value may have a value after the decimal point.

  More specifically, the first evaluation value acquisition unit 112 operates as follows for each legibility evaluation image.

  First, the first evaluation value acquisition unit 112 displays a legibility evaluation image on a display.

  When the readability evaluation image is displayed on the display, the evaluator evaluates the displayed readability evaluation image for readability, and inputs a readability evaluation value via the input device 904 or the communication device 906.

  Next, the first evaluation value acquisition unit 112 receives the input legibility evaluation value.

  Then, the first evaluation value acquisition unit 112 stores the readability evaluation value in the storage unit 191 in association with the readability evaluation image.

  It is desirable to have multiple evaluators. Although the evaluation result can be quantified by using the NIIRS scale, the evaluation result is considered to be different depending on individual differences.

  In order to evaluate NIIRS, it is necessary to have sufficient knowledge about NIIRS.

  When there are a plurality of evaluators, the first evaluation value acquisition unit 112 operates as follows for each legibility evaluation image.

  First, the first evaluation value acquisition unit 112 receives a plurality of legibility evaluation values obtained by a plurality of evaluators who have evaluated the legibility evaluation image.

  Next, the first evaluation value acquisition unit 112 calculates a value representative of the plurality of readability evaluation values as a readability evaluation value for the readability evaluation image.

  Then, the first evaluation value acquisition unit 112 stores the readability evaluation value for each readability evaluation image in the storage unit 191.

  When there are a plurality of evaluators, it is desirable that the displays used by each evaluator are arranged in the same model and the settings of each display are arranged identically.

  When evaluators with poor visual acuity are included, there is a possibility that evaluation values vary among evaluators. In such a case, it is desirable to perform evaluation after correcting the evaluator's visual acuity using glasses or the like.

  The relationship among the legibility evaluation image Is, the evaluator P, the legibility evaluation value Nd, and the representative value Ns will be described based on FIG.

  Is_X indicates the X-th legibility evaluation image Is. PY indicates the Y-th evaluator P. Nd_X (PY) indicates the legibility evaluation value Nd obtained by evaluating the legibility evaluation image Is_X by the evaluator PY. Ns_X indicates a representative value of the legibility evaluation value Nd_X (PY).

  The specific representative value Ns_X is an average value of the legibility evaluation value Nd_X (PY).

  When the representative value Ns_X is the average value of the legibility evaluation values Nd_X (PY), the representative value Ns_X can be represented by the following equation (1).

図２に戻り、ステップＳ１１３を説明する。

Returning to FIG. 2, step S113 will be described.

  Step S113 is a first relational expression generation process.

  In step S113, the first relational expression generation unit 113 generates a first relational expression based on a plurality of readability evaluation values obtained by evaluating a plurality of readability evaluation images.

  The first relational expression is an expression indicating the relationship between the legibility evaluation value and the value of the legibility parameter.

  Specifically, the legibility evaluation value is an NIIRS value, and the first relational expression is an expression for predicting the NIIRS value. As an equation for estimating the NIIRS value, for example, there is GIQE (General Image Quality Equation). In this example, a method of creating the first relational expression using the same elements as the five elements included in the GIQE as readability parameters will be described. In this case, the legibility parameters are five elements (GSD, RR, SNR, H, G) included in GIQE. GIQE is a known mathematical formula, and a methodology for creating a prediction formula is also known. Therefore, description of the details of GIQE is omitted.

  Specifically, the first relational expression generation unit 113 operates as follows.

  First, the first relational expression generation unit 113 extracts parameter condition information from the generation condition information. The parameter condition information indicates the value of the legibility parameter for each set of the total integration time and the solar altitude. That is, the parameter condition information indicates a plurality of readability parameter values corresponding to the plurality of readability evaluation images.

  Next, the first relational expression generation unit 113 performs a multiple regression analysis using the plurality of readability evaluation values and the plurality of readability parameter values. Thereby, the coefficient included in the first relational expression is calculated. In the multiple regression analysis, the objective variable is a legibility evaluation value, and the explanatory variable is a legibility parameter value. A specific method for performing multiple regression analysis is a stepwise method.

  Next, the first relational expression generation unit 113 generates a first relational expression using the calculated coefficients.

  Then, the first relational expression generation unit 113 stores the first relational expression in the storage unit 191.

  The multiple regression analysis and the first relational expression will be described.

  In the multiple regression analysis, the first relational expression generation unit 113 extracts an explanatory variable whose P value (significance probability) is equal to or less than a specified value as a correlated explanatory variable.

  Next, the first relational expression generation unit 113 adds the partial regression coefficients of the extracted explanatory variables.

  Then, the first relational expression generation unit 113 generates a first relational expression for predicting the target variable.

  When five elements (GSD, RR, SNR, H, G) included in GIQE are used as readability parameters of the first relational expression Fn, the first relational expression Fn can be expressed by the following expression (2). it can. The predicted value Ne is a legibility evaluation value calculated by calculating the first relational expression Fn.

ｋ_１からｋ_５は、重回帰分析によって得られた係数である。上記の式（２）において、演算子が加算（プラス）ではなく減算（マイナス）である場合、係数はマイナスになる。

from k ₁ k ₅ is a coefficient obtained by multiple regression analysis. In the above equation (2), when the operator is subtraction (minus) instead of addition (plus), the coefficient becomes negative.

  log10 is a common logarithm. In the multiple regression analysis, the correlation is strong when the explanatory variables are expressed in a linear relationship. Therefore, an explanatory variable having a logarithmic distribution such as a common logarithm or a natural logarithm is represented by a logarithm.

  The relationship among the legibility evaluation image Is, the explanatory variable (Sc), the objective variable (Ns), and the first relational expression Fn will be described based on FIG.

  One first relational expression Fn is generated using the value of the explanatory variable (Sc) and the value of the objective variable (Ns) for each legibility evaluation image Is.

  The value of the explanatory variable (Sc) is a legibility parameter value indicated by the parameter condition information in the generation condition information.

  The value of the objective variable (Ns) is a legibility evaluation value.

  Returning to FIG. 2, step S121 will be described.

  Step S121 is a second image generation process.

  In step S121, the second image generation unit 121 generates a plurality of resolution evaluation images by adjusting the second original image based on the imaging condition information.

  The second original image is an image that is a source of a plurality of resolution evaluation images. The second original image is preferably a high-resolution and high-definition image. As the second original image, an image of an evaluation pattern or an aerial image of a scene including an evaluation pattern such as Tri-bar can be used.

  The plurality of resolution evaluation images are a plurality of images evaluated for the resolution and have different resolution parameter values. A specific index for evaluating the resolution is GRD.

  The resolution parameter is a parameter related to the resolution. Specific resolution parameters will be described later.

  Specifically, the second image generation unit 121 operates as follows.

  First, the second image generation unit 121 extracts imaging condition information from the generation condition information.

  Then, for each set of the total integration time and the sun altitude indicated in the imaging condition information, the second image generation unit 121 processes the second original image according to the total integration time and the sun altitude of the set. , And generates a resolution evaluation image corresponding to the set.

  Note that the second original image is prepared by the administrator and stored in the storage unit 191 in advance via the input device 904 or the communication device 906.

  The relationship between the total integration time, the sun height, and the resolution evaluation image is the same as the relationship between the total integration time, the sun height, and the readability evaluation image described with reference to FIG.

  In the second original image and the plurality of resolution evaluation images, a plurality of white line patterns having different sizes and line directions are reflected in order to evaluate GRD.

  The white line pattern is a pattern in which three white lines (Tri-bar) are written on a black background.

  The three white lines are arranged in parallel and have the same length and thickness. The interval between the white lines is equal to the thickness of the white lines.

  In addition, together with the second original image, information generally included as metadata in the image, such as a file format, the number of pixels, and the number of bits, is stored in the storage unit 191 as information about the second original image. Further, analysis information obtained by analyzing the second original image may be stored in the storage unit 191 together with the second original image.

  In the GRD evaluation, a white line pattern in which three white lines appear to be separated is extracted from the plurality of white line patterns. Then, from the extracted white line patterns, a white line pattern having the smallest white line interval is selected. The interval between the white lines in the selected white line pattern is the GRD value. The GRD value is a value obtained by evaluating a resolution evaluation image for GRD.

  Based on FIG. 6, four white line patterns Tb having different sizes and line directions will be described.

  The white line patterns Tb_Ly and Tb_Lx are larger than the white line patterns Tb_Sy and Tb_Sx.

  The direction of the white lines in the white line patterns Tb_Ly and Tb_Sy is the vertical direction, and the direction of the white lines in the white line patterns Tb_Lx and Tb_Sx is the horizontal direction.

  In the white line pattern Tb_Ly, three white lines are arranged in parallel, and have the same length Ls and thickness Lw. The interval Lb between the white lines is equal to the thickness Lw of the white line, and the length Ls of the white line is equal to five times the thickness Lw of the white line. The same applies to other white line patterns.

  When three white lines appear to be separated in all four white line patterns, the distance between the white lines of the small white line patterns Tb_Sy and Tb_Sx is the GRD value.

  When three white lines of the small white line patterns Tb_Sy and Tb_Sx cannot be seen separately and three white lines of the large white line patterns Tb_Ly and Tb_Lx appear separately, the distance between the white lines of the white line patterns Tb_Ly and Tb_Lx becomes the GRD value. .

  The white line pattern for measuring the GRD value includes a white line and a black background, and when preparing the second original image, the contrast between white and black may be changed. When the second original image is an 8-bit grayscale digital image, the range of values that can be taken as pixel brightness is 0 to 255, the value indicating black is 0, and the value indicating white is 255. is there. For example, the value indicating black is changed to 30, and the value indicating white is changed to 225. When the contrast of the second original image is narrowed, the boundary between white and black is difficult to resolve, so that the GRD value tends to be low.

  This tendency is remarkable when the solar altitude Se is low and the total integration time Ti is short. On the other hand, when the brightness is sufficiently obtained, such as when the solar altitude Se is high and the total integration time Ti is long, there is no large difference in the GRD values.

  Returning to FIG. 2, step S122 will be described.

  Step S122 is a second evaluation value acquisition process.

  In step S122, the second evaluation value acquisition unit 122 acquires a plurality of resolution evaluation values for a plurality of resolution evaluation images. The resolution evaluation value is a GRD value.

  Specifically, the second evaluation value acquisition unit 122 displays a plurality of resolution evaluation images on a display and receives a plurality of resolution evaluation values for the plurality of resolution evaluation images. The display on which the plurality of resolution evaluation images are displayed may be either the display of the imaging management device 100 or an external display.

  More specifically, the second evaluation value acquisition unit 122 operates as follows for each resolution evaluation image.

  First, the second evaluation value acquisition unit 122 displays a resolution evaluation image on a display.

  When the resolution evaluation image is displayed on the display, the evaluator evaluates the displayed resolution evaluation image for resolution, and inputs a resolution evaluation value via the input device 904 or the communication device 906.

  Next, the second evaluation value acquisition unit 122 receives the input resolution evaluation value.

  Then, the second evaluation value acquisition unit 122 stores the resolution evaluation value in the storage unit 191 in association with the resolution evaluation image.

  It is desirable to have multiple evaluators. Although the evaluation result can be quantified by using the GRD scale, the evaluation result is considered to be different depending on individual differences.

  In addition, in order to evaluate GRD, specialized knowledge about GRD is not required.

  When there are a plurality of evaluators, the second evaluation value acquisition unit 122 operates as follows for each resolution evaluation image.

  First, the second evaluation value acquisition unit 122 receives a plurality of resolution evaluation values obtained by a plurality of evaluators who have evaluated the resolution evaluation image.

  Next, the second evaluation value acquisition unit 122 calculates a value representative of the plurality of resolution evaluation values as a resolution evaluation value for the resolution evaluation image.

  Then, the second evaluation value acquisition unit 122 stores the resolution evaluation value for each resolution evaluation image in the storage unit 191.

  When there are a plurality of evaluators, it is desirable that the displays used by each evaluator are arranged in the same model and the settings of each display are arranged identically.

  When evaluators with poor visual acuity are included, there is a possibility that evaluation values vary among evaluators. In such a case, it is desirable to perform evaluation after correcting the evaluator's visual acuity using glasses or the like.

  The relationship among the resolution evaluation image Ip, the evaluator P, the resolution evaluation value Gd, and the representative value Gs will be described with reference to FIG.

  Ip_X indicates the X-th resolution evaluation image Ip. PY indicates the Y-th evaluator P. Gd_X (PY) indicates a resolution evaluation value Gd obtained by evaluating the resolution evaluation image Ip_X by the evaluator PY. Gs_X indicates a representative value of the resolution evaluation value Gd_X (PY).

  The specific representative value Gs_X is an average value of the resolution evaluation values Gd_X (PY).

  When the representative value Gs_X is the average value of the resolution evaluation values Gd_X (PY), the representative value Gs_X can be represented by the following equation (3).

図２に戻り、ステップＳ１２３を説明する。

Returning to FIG. 2, step S123 will be described.

  Step S123 is a second relational expression generation process.

  In step S123, the second relational expression generation unit 123 generates a second relational expression based on a plurality of resolution evaluation values obtained by evaluating the plurality of resolution evaluation images.

  The second relational expression is an expression indicating the relationship between the resolution evaluation value and the value of the resolution parameter.

  Specifically, the resolution evaluation value is a GRD value, and the second relational expression is an expression for predicting the GRD value. As an equation for predicting the GRD value, for example, there is GIQE. In this example, a method of creating the second relational expression using the same elements as the five elements included in the GIQE as resolution parameters will be described. In this case, the resolution parameters are five elements (GSD, RR, SNR, H, G) included in GIQE. GIQE is a known mathematical formula, and a methodology for creating a prediction formula is also known. Therefore, description of the details of GIQE is omitted.

  Specifically, the second relational expression generation unit 123 operates as follows.

  First, the second relational expression generation unit 123 extracts parameter condition information from the generation condition information. The parameter condition information indicates the value of the resolution parameter for each set of the total integration time and the solar altitude. That is, the parameter condition information indicates a plurality of resolution parameter values corresponding to the plurality of resolution evaluation images.

  Next, the second relational expression generation unit 123 performs a multiple regression analysis using the plurality of resolution evaluation values and the plurality of resolution parameter values. Thereby, the coefficient included in the second relational expression is calculated. In the multiple regression analysis, the objective variable is a resolution evaluation value, and the explanatory variable is a resolution parameter value. A specific method for performing multiple regression analysis is a stepwise method.

  Next, the second relational expression generation unit 123 generates a second relational expression using the calculated coefficients.

  Then, the second relational expression generation unit 123 stores the second relational expression in the storage unit 191.

  The multiple regression analysis and the second relational expression will be described.

  In the multiple regression analysis, the second relational expression generation unit 123 extracts an explanatory variable whose P value (significance probability) is equal to or less than a specified value as a correlated explanatory variable.

  Next, the second relational expression generation unit 123 adds the partial regression coefficients of the extracted explanatory variables.

  Then, the second relational expression generation unit 123 generates a second relational expression for predicting the target variable.

  When five elements (GSD, RR, SNR, H, G) included in GIQE are used as the resolution parameters of the second relational expression Fg, the second relational expression Fg can be expressed by the following expression (4). . The predicted value Ge is a resolution evaluation value calculated by calculating the second relational expression Fg.

ｋ_６からｋ_１０は、重回帰分析によって得られた係数である。上記の式（４）において、演算子が加算（プラス）ではなく減算（マイナス）である場合、係数はマイナスになる。

_{k 10} from k ₆ are coefficients obtained by multiple regression analysis. In the above equation (4), when the operator is subtraction (minus) instead of addition (plus), the coefficient becomes negative.

  log10 is a common logarithm. In the multiple regression analysis, the correlation is strong when the explanatory variables are expressed in a linear relationship. Therefore, an explanatory variable having a logarithmic distribution such as a common logarithm or a natural logarithm is represented by a logarithm.

  The relationship among the resolution image Ip, the explanatory variable Sc, the objective variable (Gs), and the second relational expression Fg will be described with reference to FIG.

  One second relational expression Fg is generated using the value of the explanatory variable Sc and the value of the objective variable (Gs) for each resolution evaluation image Gs.

  The value of the explanatory variable Sc is a resolution parameter value indicated by the parameter condition information in the generation condition information.

  The value of the objective variable (Gs) is a resolution evaluation value.

  If there is no difference between the GRD value and the NIIRS value even if the total integration time Ti changes, it is difficult to obtain a relational expression by multiple regression analysis. This is because the changed total integration time Ti and the image that changes with the total integration time Ti do not affect the target variable. Therefore, when it is difficult to calculate the second relational expression because there is no difference in the evaluation based on the GRD value, the second original image may be adjusted. Specifically, it is conceivable to change the black and white contrast of the white line pattern, or to prepare a large number of white line patterns having a small difference in size.

  Returning to FIG. 2, step S130 will be described.

  Step S130 is a set value determination process.

  In step S130, the set value determination unit 130 determines a set value based on the first relational expression and the second relational expression.

  The set value is a value set in the imaging parameter. The imaging parameter is a parameter included in the imaging device or the imaging system. A specific imaging parameter is the total integration time.

  The procedure of the set value determination process (S130) will be described based on FIG.

  In step S131, the set value determination unit 130 calculates a first set value candidate based on the first relational expression.

  When the first relational expression is GIQE for predicting the NIIRS value and the imaging parameter is the total integration time, the first candidate is the total integration time when the NIIRS value is maximum.

  A method for calculating the first candidate TiN will be specifically described based on FIG.

  FIG. 10 is a graph showing the relationship between the NIIRS value and the total integration time Ti.

  The total integration times Ti_1 to Ti_n are the total integration times indicated by the imaging parameters in the generation condition information.

  The total integration times Ti_2a and Ti_ (n-1) a are the total integration times indicated by the evaluation condition information. The evaluation condition information is information for supplementing the total integration time. One or more total integration times may be inserted between each of the total integration times Ti. Further, the total integration time does not necessarily have to be inserted between the total integration times Ti. Specifically, the evaluation condition information includes the imaging condition information and the parameter information, like the generation condition information. The evaluation condition information is prepared by an administrator and stored in advance in the storage unit 191 via the input device 904 or the communication device 906. By using the evaluation condition information, it is possible to reduce the number of generated legibility evaluation images.

  The predicted values Ne_1 to Ne_n are legibility evaluation values corresponding to the total integration times Ti_1 to Ti_n. The predicted values Ne_2a and Ne_ (n-1) a are legibility evaluation values corresponding to the total integration times Ti_2a and Ti_ (n-1) a. Each predicted value is calculated by calculating a first relational expression Fn.

  The set value determination unit 130 calculates the graph shown in FIG. 10 using the first relational expression Fn, the generation condition information, and the evaluation condition information, and selects the total integration time Ti_3 corresponding to the maximum predicted value Ne_3. The selected total integration time Ti_3 is the first candidate TiN.

  Returning to FIG. 9, step S132 will be described.

  In step S132, the setting value determination unit 130 calculates a second candidate for the setting value based on the second relational expression.

  When the second relational expression is GIQE for predicting the GRD value and the imaging parameter is the total integration time, the second candidate is the total integration time when the GRD value is minimum.

  A method of calculating the second candidate TiG will be specifically described based on FIG.

  FIG. 11 is a graph showing the relationship between the GRD value and the total integration time Ti.

  The total integration times Ti_1 to Ti_n are the total integration times indicated by the imaging parameters in the generation condition information.

  The total integration times Ti_2a and Ti_ (n-1) a are the total integration times indicated by the evaluation condition information. One or more total integration times may be inserted between each of the total integration times Ti. Further, the total integration time does not necessarily have to be inserted between the total integration times Ti. By using the evaluation condition information, the number of generated resolution evaluation images can be reduced.

  The predicted values Ge_1 to Ge_n are resolution evaluation values corresponding to the total integration times Ti_1 to Ti_n. The predicted values Ge_2a and Ge_ (n-1) a are resolution evaluation values corresponding to the total integration times Ti_2a and Ti_ (n-1) a. Each predicted value is calculated by calculating a second relational expression Fg.

  The setting value determination unit 130 calculates the graph shown in FIG. 11 using the second relational expression Fg, the generation condition information, and the evaluation condition information, and selects the total integration time Ti_3 corresponding to the minimum predicted value Ge_3. The selected total integration time Ti_3 is the second candidate TiG.

  Returning to FIG. 9, step S133 will be described.

  In step S133, the setting value determination unit 130 calculates a setting value using the first candidate and the second candidate.

  Specifically, the setting value determination unit 130 calculates a setting value by performing weighting evaluation using the first candidate and the second candidate.

  That is, the setting value determination unit 130 weights the first candidate by multiplying the weighting coefficient for legibility evaluation value by the first candidate, and multiplies the second candidate by weighting the second candidate by the weighting coefficient for resolution evaluation value. Weight the candidates. Then, the set value determination unit 130 calculates a set value using the weighted first candidate and the weighted second candidate.

  When the weighting coefficient for the legibility evaluation value is equal to the weighting coefficient for the resolution evaluation value, the set value Pti can be expressed by the following equation (5) using the first candidate TiN and the second candidate TiG. That is, the set value Pti is an average value of the first candidate TiN and the second candidate TiG.

判読性評価値用の重み付け係数Ｗｔが解像度評価値用の重み付け係数（１−Ｗｔ）と異なる場合、設定値Ｐｔｉは以下の式（６）で表すことができる。但し、Ｗｔは０より大きく１より小さい値である。Ｗｔが０．５あれば、以下の式（６）は上記の式（５）と等しい。Ｗｔが０または１である場合には第１候補と第２候補とのいずれかが利用されないことになるため、Ｗｔの値として０および１は適当でない。

When the weighting coefficient Wt for legibility evaluation value is different from the weighting coefficient (1-Wt) for resolution evaluation value, the set value Pti can be expressed by the following equation (6). However, Wt is a value larger than 0 and smaller than 1. If Wt is 0.5, the following equation (6) is equal to the above equation (5). When Wt is 0 or 1, it means that either the first candidate or the second candidate is not used, and 0 and 1 are not appropriate as values of Wt.

そして、設定値決定部１３０は、算出された設定値を記憶部１９１に記憶する。

Then, the setting value determination unit 130 stores the calculated setting value in the storage unit 191.

  In addition, the set value determining unit 130 displays the calculated set value on a display. The display on which the set value is displayed may be either the display of the imaging management device 100 or an external display.

  The relationship between the first candidate TiN, the second candidate TiG, and the set value Pti will be described with reference to FIGS.

  “Fn” is a graph showing the predicted value Ne of the NIIRS, and “Fg” is a graph showing the predicted value Ge of the GRD.

  In FIG. 12, the first candidate TiN based on the predicted value Ne is the total integration time Ti_3, and the second candidate TiG based on the predicted value Ge is the total integration time Ti_3. That is, both the first candidate TiN and the second candidate TiG have the total integration time Ti_3. In this case, the total integration time Ti_3 is calculated as the set value Pti.

In FIG. 13, the first candidate TiN based on the predicted value Ne is the total integration time Ti_3, and the second candidate TiG based on the predicted value Ge is the total integration time Ti_2. In this case, the total integration time Ti larger than Ti_2 and smaller than Ti_3 is calculated as the set value Pti.
*** Effect of Embodiment 1 ***
It is possible to quantitatively calculate a preferable setting value of the imaging device based on an evaluation result of a smaller number of evaluators than before.

  Since the calculated set value reflects the evaluation result by the evaluator, an image with excellent legibility and resolution can be obtained by imaging using this set value.

  Further, the number of evaluators and images for evaluation can be reduced as compared with the conventional evaluation, so that the cost for evaluation can be reduced.

  Further, by using NIIRS and GRD as indices, it is possible to more quantitatively evaluate the readability and the resolution.

  The calculated set value is excellent from the viewpoint of NIIRS indicating readability and the viewpoint of GRD indicating resolution. By applying this set value to an optical imaging device (or imaging system), a high-quality image with excellent legibility and resolution can be obtained.

*** Other configuration ***
The same image may be used as the first original image and the second original image. In this case, an original image in which a criterion for evaluating NIIRS and a Tri-bar for evaluating GSD are included in the image is used.

  A set of plural images may be used as plural legibility evaluation images and plural resolution evaluation images.

  A plurality of first original images having different imaging points and subjects may be prepared, and a plurality of legibility evaluation images may be generated for each first original image. Specifically, the plurality of first original images are images in which various landscapes such as a city, a suburb, a bay, or a forest are reflected.

  In the evaluation of readability and the evaluation of resolution, the evaluator may be the same person or a different person.

  The number of evaluators may be the same or different in the evaluation of readability and the evaluation of resolution.

  When calculating the representative value of the legibility evaluation value and the representative value of the resolution evaluation value, the standard deviation or the variance of the evaluation value may be used to exclude an image having a large variation in the evaluation value. An image having a large variation in the evaluation value is likely to include an unexpected factor. Specifically, an image in which the standard deviation of the evaluation value is larger than the threshold may be excluded.

  Further, when calculating the representative value of the legibility evaluation value and the representative value of the resolution evaluation value, the representative value may be calculated again excluding the evaluation value whose difference from the representative value exceeds the threshold value.

  The average value as the representative value of the legibility evaluation value and the representative value of the resolution evaluation value may be either an arithmetic average or a geometric average.

  Further, the representative value of the legibility evaluation value and the representative value of the resolution evaluation value may be values other than the average value. Specifically, the representative value of the legibility evaluation value and the representative value of the resolution evaluation value may be intermediate values.

  The administrator calculates a representative value of the legibility evaluation value and a representative value of the resolution evaluation value using a computer or the like, and inputs the calculated representative value to the imaging management apparatus 100 via the input device 904 or the communication device 906. Is also good. In this case, the first evaluation value acquisition unit 112 need only receive the input representative value, does not need to receive the legibility evaluation value and the resolution evaluation value, and needs to perform an operation for calculating the representative value. Nor.

  In the first relational expression of the legibility evaluation value and the second relational expression of the resolution evaluation value, the explanatory variables may not be the same.

  An explanatory variable correlated with the first relational expression of the legibility evaluation value and the second relational expression of the resolution evaluation value may be added.

  In the first relational expression of the legibility evaluation value and the second relational expression of the resolution evaluation value, SNR and G may be one explanatory variable of G / SNR.

The method of the multiple regression analysis for generating the first relational expression of the legibility evaluation value and the second relational expression of the resolution evaluation value may be a method other than the stepwise method.
*** Supplement to the embodiment ***
In the embodiment, the function of the imaging management apparatus 100 may be realized by hardware.

  FIG. 14 illustrates a configuration in a case where the functions of the imaging management apparatus 100 are realized by hardware.

  The imaging management device 100 includes a processing circuit 990. The processing circuit 990 is also called a processing circuit.

  The processing circuit 990 includes a first image generation unit 111, a first evaluation value acquisition unit 112, a first relational expression generation unit 113, a second image generation unit 121, a second evaluation value acquisition unit 122, and a second relational expression generation unit 123. And a dedicated electronic circuit for realizing the functions of “units” such as the setting value determination unit 130 and the storage unit 191.

  Specifically, the processing circuit 990 is a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, a logic IC, a GA, an ASIC, an FPGA, or a combination thereof. GA is an abbreviation of Gate Array, ASIC is an abbreviation of Application Specific Integrated Circuit, and FPGA is an abbreviation of Field Programmable Gate Array.

  The imaging management apparatus 100 may include a plurality of processing circuits replacing the processing circuit 990. The plurality of processing circuits share the function of the “unit”.

  The function of the imaging management apparatus 100 may be realized by a combination of software and hardware. That is, a part of the function of the “unit” may be realized by software, and the rest of the function of the “unit” may be realized by hardware.

  The embodiment is an exemplification of a preferred embodiment, and is not intended to limit the technical scope of the present invention. Embodiments may be implemented partially or in combination with other embodiments. The procedure described using the flowchart and the like may be appropriately changed.

  Reference Signs List 100 imaging management device, 111 first image generation unit, 112 first evaluation value acquisition unit, 113 first relational expression generation unit, 121 second image generation unit, 122 second evaluation value acquisition unit, 123 second relational expression generation unit , 130 setting value determination unit, 191 storage unit, 901 processor, 902 memory, 903 auxiliary storage device, 904 input device, 905 output device, 906 communication device, 990 processing circuit.

Claims (8)

Based on a plurality of readability evaluation values obtained by evaluating a plurality of readability evaluation images which are a plurality of images evaluated for readability and a plurality of images having different readability parameter values, readability evaluation is performed. A first relational expression generation unit that generates a first relational expression that indicates a relation between the value and the value of the legibility parameter;
Based on a plurality of resolution evaluation values obtained by evaluating a plurality of resolution evaluation images that are a plurality of images evaluated for resolution and a plurality of images having different resolution parameter values, a resolution evaluation value and a resolution parameter A second relational expression generation unit that generates a second relational expression indicating a relation with the value,
An imaging management device, comprising: a setting value determination unit that determines a setting value to be set for an imaging parameter based on the first relational expression and the second relational expression. The setting value determination unit calculates a first candidate of the setting value based on the first relational expression, calculates a second candidate of the setting value based on the second relational expression, and The imaging management device according to claim 1, wherein the setting value is calculated using the second candidate. The readability evaluation value is a value of National Imagery InterPretability Rating Scale,
The first candidate is a value of the imaging parameter when the legibility evaluation value is maximized,
The resolution evaluation value is a value of Ground Resolved Distance,
The imaging management device according to claim 2, wherein the second candidate is a value of the imaging parameter when the resolution evaluation value is minimum. A first evaluation value acquisition unit that displays the plurality of readability evaluation images on a display and receives the plurality of readability evaluation values for the plurality of readability evaluation images;
4. The apparatus according to claim 1, further comprising: a second evaluation value acquisition unit configured to display the plurality of resolution evaluation images on a display and receive the plurality of resolution evaluation values for the plurality of resolution evaluation images. 5. The imaging management device according to the above. The first evaluation value acquisition unit receives, for each readability evaluation image, a plurality of readability evaluation values obtained by a plurality of evaluators who have evaluated the readability evaluation image, and receives the received plurality of readability evaluation values. Calculate a value representing the value as a legibility evaluation value for the legibility evaluation image,
The second evaluation value acquisition unit receives, for each resolution evaluation image, a plurality of resolution evaluation values obtained by a plurality of evaluators who have evaluated the resolution evaluation image, and represents the received plurality of resolution evaluation values. The imaging management apparatus according to claim 4, wherein the value is calculated as a resolution evaluation value for the resolution evaluation image. A first image generation unit configured to generate the plurality of readability evaluation images by processing a first original image based on imaging condition information indicating conditions at the time of imaging;
The imaging apparatus according to claim 1, further comprising: a second image generation unit configured to generate the plurality of resolution evaluation images by processing a second original image based on the imaging condition information. Management device. The imaging condition information indicates a plurality of sets of a total integration time and a solar altitude as conditions at the time of the imaging,
The first image generation unit, for each set of the total integration time and the solar altitude indicated in the imaging condition information, processes the first original image according to the total integration time and the solar altitude of the set. Generating a legibility evaluation image corresponding to the set,
The second image generation unit, for each set of the total integration time and the sun altitude indicated in the imaging condition information, processes the second original image according to the total integration time and the sun altitude of the set. The imaging management apparatus according to claim 6, wherein a resolution evaluation image corresponding to the set is generated. Based on a plurality of readability evaluation values obtained by evaluating a plurality of readability evaluation images which are a plurality of images evaluated for readability and a plurality of images having different readability parameter values, readability evaluation is performed. A first relational expression generation process for generating a first relational expression indicating a relation between the value and the value of the legibility parameter;
Based on a plurality of resolution evaluation values obtained by evaluating a plurality of resolution evaluation images that are a plurality of images evaluated for resolution and a plurality of images having different resolution parameter values, a resolution evaluation value and a resolution parameter A second relational expression generation process for generating a second relational expression indicating a relation with the value,
An imaging management program for causing a computer to execute setting value determination processing for determining a setting value to be set for an imaging parameter based on the first relational expression and the second relational expression.

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