A borehole inner wall image robust splicing method under multiple interference imaging conditions

Abstract

This invention relates to a robust stitching method for borehole inner wall images under multi-interference imaging conditions, specifically including the following steps: S1, unfolding the acquired forward-looking borehole inner wall image into a narrow-band image; S2, registering the unfolded two consecutive narrow-band images, and using a grid-accelerated template matching method to determine the vertical and horizontal offsets of the reference image and the image to be stitched; S3, determining the overlapping area of ​​the reference image and the image to be stitched based on the offsets, and fusing the pixels in the overlapping area to obtain the stitched borehole inner wall image; S4, repeating steps S1 to S3, stitching frame by frame until logging is completed, to obtain a panoramic image of the borehole inner wall. This invention effectively solves the image stitching problems encountered in actual logging operations due to poor lighting conditions, loss or inaccuracy of electronic compass and depth counter readings, and lens rotation disturbances, and can stably obtain smooth panoramic borehole inner wall image stitching results.

Description

Technical Field

[0001] This invention relates to the field of image processing, and more specifically, to a robust stitching method for borehole inner wall images under multi-interference imaging conditions. Background Technology

[0002] Borehole wall images are widely used to detect underground geological structures and assess rock strata stability. Traditional borehole image stitching methods are based on the stacking of scan lines or scan line-like structures. This involves continuously generating single or multiple scan lines for each frame of video image, relying entirely on or indirectly referencing the azimuth angle of an electronic compass or compass and the depth information from an encoder. These scan lines are then stacked sequentially to form the corresponding borehole image, or a simple, ordered comparison and accumulation of multiple scan lines (rectangular window-like images) is performed to generate a panoramic image of the borehole. Although these traditional methods have seen algorithmic improvements, they become ineffective if magnetic rock formations exist in the borehole, causing distortion in readings from depth sensors and electronic compasses, or if excessively long cable runs cause interference from minor airflow or water currents, resulting in rotational disturbances in the camera's image. Therefore, borehole image stitching algorithms based on feature point matching have gradually emerged, such as image stitching algorithms based on SIFT / SURF and RANSAC. Although these algorithms have achieved the stitching of borehole inner wall images, the stitched images have a certain degree of geometric distortion due to homography transformation. As the stitching process continues, the accumulation of this distortion will lead to the interruption of stitching, that is, stable image stitching cannot be performed. Summary of the Invention

[0003] To overcome the limitations of existing technologies, this invention provides a robust stitching method for borehole inner wall images under multiple interference imaging conditions. This method can still automatically unfold, register, and fuse borehole images under various rock strata environmental interference conditions, and stably generate stitched images of the borehole inner wall.

[0004] Specifically, the present invention provides a robust stitching method for borehole inner wall images under multiple interference imaging conditions, comprising the following steps:

[0005] S1. Unfold the acquired forward-looking borehole wall image into a narrow-band image: including the center of the annular region to be unfolded from the borehole wall image. Detecting overexposed and underexposed interference areas to determine the outer diameter of the unfolded ring. and inner diameter The circular region image is expanded into a rectangular narrowband image through polar coordinate mapping and interpolation.

[0006] S2. Register the two unfolded narrowband images: the previous frame is called the reference image and denoted as . The next frame is called the image to be stitched together and is denoted as . First, the local image patch with the highest information entropy is automatically selected from the images to be stitched as a template. Then, a grid-accelerated template matching method is used to find the most similar local image patch in the reference image, quickly registering the two images and determining the coordinates of the matching points in the reference image and the images to be stitched. and Thus, the vertical and horizontal offsets of the image to be stitched relative to the reference image are respectively , ;

[0007] S3. Determine the overlapping area between the reference image and the image to be stitched, and fuse the pixels in the overlapping area to obtain the stitched image of the borehole inner wall: First, shift all columns of the image to be stitched to the left in a circular fashion. One pixel, that is, the horizontal offset obtained from image registration. Cyclicly translate until it is horizontally aligned with the reference image; the aligned image to be stitched is denoted as... Thus the image and images The overlapping region is: Then, the overlapping pixels of the two images are linearly fused row by row to obtain a new stitched image of the borehole inner wall.

[0008] S4. Repeat steps S1 to S3 above, stitching frame by frame until logging is complete, to obtain a panoramic view of the borehole wall.

[0009] In the above technical solution, step S1 specifically includes the following steps:

[0010] S11. For the borehole inner wall images acquired from the forward-looking camera, the Hough circle detection method is used to detect the halo formed by the forward-looking camera technique. The center of the detected halo is used as the center of the expanded circular region of the borehole inner wall image. And denote the radius of the halo as . ;

[0011] S12, Calculate the center of the circle. Distances to the top, bottom, left, and right sides of the borehole inner wall image captured by forward view. The shortest of the four distances was selected as the initial outer diameter for unfolding the annulus of the borehole inner wall image. ;

[0012] S13, with For step size, for... Center of the circle For outer diameter, Let the area of ​​the annular region with inner diameter be denoted as . The threshold method is used to detect overexposed and underexposed pixels in the annular region, and its total area is recorded as . When overexposed and underexposed pixels account for more than a certain proportion The annular region, i.e., the condition Upon establishment, update the outer diameter. That is, reduce the outer diameter; repeat the above process to select a new annular region until the condition is no longer met, and then use the latest... The value is used as the optimal outer diameter for unfolding the annulus in the borehole inner wall image; at the same time, As the inner diameter of the annulus unfolded from the borehole inner wall image, where It is an adjustable scaling factor;

[0013] S14. Unfold the determined annular region image into a rectangular narrow-band image through polar coordinate mapping and interpolation operations, and record the height of the unfolded image. ,Width .

[0014] Furthermore, step S2 specifically includes:

[0015] S21. From the image to be stitched The process automatically selects the local image patch with the highest information entropy as the template. Specifically, it involves selecting the image to be stitched... by Divided into several grids of size Based on the concept of entropy in information theory, the image block with the largest amount of information is selected as the template image, denoted as [image block name]. ;

[0016] S22. Employ a grid-accelerated template matching method in the reference image. To quickly register two images, the method involves finding the most similar local image patch to the template image. Specifically, in the coarse matching stage, a grid is used as the basic matching unit to search for the template image within the reference image. During the search, the grid moves horizontally or vertically by the width or height of one template image. After each movement, the similarity between the grid region in the current reference image and the template image is calculated. The grid position with the highest similarity (i.e., the smallest difference) is recorded as the optimal matching position for coarse matching. Then, in the fine matching stage, the optimal matching position obtained from coarse matching is used to perform a more refined search around it. At this stage, the search step size is reduced to half the height or width of the template image. Using the current optimal matching point as the center, the grid moves one step up / down and one step left / right. This process is repeated continuously, with the step size halved each time, and a new similarity is calculated and compared with the current optimal matching point. If a better matching point is found, the optimal matching position is updated. This process is repeated until the step size is reduced to a preset minimum value, i.e., the step size is reduced to 0. At this point, the reference image is obtained. and the image to be stitched The coordinates of the matching points are denoted as follows: and ;

[0017] S23. Calculate the vertical and horizontal offsets of the image to be stitched relative to the reference image, respectively. , .

[0018] Furthermore, step S3 specifically includes:

[0019] S31. Shift all columns of the image to be stitched to the left in a circular fashion. One pixel, that is, the horizontal offset obtained from image registration. Cyclic translation is performed until the image is horizontally aligned with the reference image. Cyclic translation means moving a column of pixels corresponding to a horizontal offset from one side to the other. The aligned image to be stitched is denoted as [image name missing]. ;

[0020] S32. For images that are already horizontally aligned and images , record the image The height is The overlapping area between the two was determined as: image From the middle Arrive at the The sub-images corresponding to all columns of a row are denoted as In image J, from row 1 to row 2 The sub-images corresponding to all columns of a row are denoted as The remaining parts of each image are non-overlapping regions;

[0021] S33, Regarding the image and images The images are stitched together, retaining the original pixel values ​​in the non-overlapping areas and linearly fusing the pixels in the overlapping areas row by row to obtain a new stitched image of the borehole inner wall. Specifically, linear weights are calculated for each row of pixels in the overlapping areas. row index The linear fusion formula is: ,in For the pixel values ​​of a certain row after merging, For reference image The pixel values ​​of a certain row in the overlapping region. Images to be stitched The overlapping region corresponds to the row pixel value. When it is close to the non-overlapping region of the reference image, the overlapping region of the reference image has a higher weight. When it is close to the non-overlapping region of the image to be stitched, the overlapping region of the image to be stitched has a higher weight. This allows for better image fusion and reduces stitching artifacts. The height of the stitched image obtained is [missing information]. .

[0022] The beneficial effects of this invention are:

[0023] 1. When determining the radius of the circular ring for unfolding the borehole inner wall image, this invention detects overexposed and underexposed pixels in the image and sets corresponding rules to avoid these low-quality image areas, effectively solving the problem that the borehole inner wall image stitching process may be interrupted due to poor lighting conditions in actual well logging operations.

[0024] 2. This invention employs a local image template matching method based on grid acceleration. Through coarse matching and fine matching, it improves the registration speed and accuracy of the reference image and the image to be stitched. At the same time, through pixel cyclic translation and line-by-line linear fusion, even when the electronic compass and depth counter readings are lost or inaccurate, or when there is lens rotation disturbance in actual well logging operations, it can stably obtain the registration results of the preceding and following frames and form a panoramic image stitching result of the borehole inner wall with a smooth transition in the overlapping area. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 A flowchart of the main steps of the method provided in this application;

[0027] Figure 2 This is a schematic diagram of the forward-looking camera drilling imaging system used in the embodiments of this application;

[0028] Figure 3 A diagram showing the overlapping regions of the registered images for this application; Detailed Implementation

[0029] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0030] In the following description, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the described elements without departing from the scope of this application. Various processes or components may be appropriately omitted, substituted, or added to the examples. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.

[0031] This application provides a robust stitching method for borehole inner wall images under multi-interference imaging conditions. This method can be applied to an image processing device, which can be a standalone device or integrated into an electronic terminal or other device with image processing capabilities. Optionally, the operating system of the device or electronic terminal integrating the image processing device can be Windows, Android, or other operating systems; no limitation is made here. Furthermore, the image registration algorithm used in this invention is not limited to the image registration algorithm provided in this method embodiment; other image registration algorithms with the same functionality can also be used.

[0032] See Figure 1 In this embodiment of the application, the method includes steps S1 to S4.

[0033] Before step S1 is executed, the method further includes: using a forward-looking borehole imaging system to photograph the rock formation downhole. The imaging system comprises a foreground camera, a system control box, a post-processing computer, cables, and other components. Figure 2 As shown. During exploration, the cable motor rotates to control the raising and lowering of the forward-looking camera in the borehole and to photograph the inner wall of the borehole. The images, along with depth and orientation information, are transmitted in real time to the system control box via cable. The system control box is used by the operator to control the motor speed and direction in real time and adjust the size according to different borehole environments. The system control box then forwards the images and other information to the post-processing computer.

[0034] Combination Figure 1 The specific steps S1 to S4 of the method can be described as follows:

[0035] S1. Unfold the acquired forward-looking borehole wall image into a narrow-band image: including the center of the annular region to be unfolded from the borehole wall image. Detecting overexposed and underexposed interference areas to determine the outer diameter of the unfolded ring. and inner diameter The circular region image is expanded into a rectangular narrowband image through polar coordinate mapping and interpolation.

[0036] S2. Register the two unfolded narrowband images: the previous frame is called the reference image and denoted as . The next frame is called the image to be stitched together and is denoted as . First, the local image patch with the highest information entropy is automatically selected from the images to be stitched as a template. Then, a grid-accelerated template matching method is used to find the most similar local image patch in the reference image, quickly registering the two images and determining the coordinates of the matching points in the reference image and the images to be stitched. and Thus, the vertical and horizontal offsets of the image to be stitched relative to the reference image are respectively ;

[0037] S3. Determine the overlapping area between the reference image and the image to be stitched, and fuse the pixels in the overlapping area to obtain the stitched image of the borehole inner wall: First, shift all columns of the image to be stitched to the left in a circular fashion. One pixel, that is, the horizontal offset obtained from image registration. Cyclicly translate until it is horizontally aligned with the reference image; the aligned image to be stitched is denoted as... Thus the image and images The overlapping region is: Then, the overlapping pixels of the two images are linearly fused row by row to obtain a new stitched image of the borehole inner wall, such as... Figure 3 As shown.

[0038] S4. Repeat steps S1 to S3 above, stitching frame by frame until logging is complete, to obtain a panoramic view of the borehole wall.

[0039] In the above technical solution, step S1 specifically includes the following steps:

[0040] S11. For the borehole inner wall images acquired from the forward-looking camera, the Hough circle detection method is used to detect the halo formed by the forward-looking camera technique. The center of the detected halo is used as the center of the expanded circular region of the borehole inner wall image. And denote the radius of the halo as . ;

[0041] S12, Calculate the center of the circle. Distances to the top, bottom, left, and right sides of the borehole inner wall image captured by forward view. The shortest of the four distances was selected as the initial outer diameter for unfolding the annulus of the borehole inner wall image. ;

[0042] S13, with For step size, for... Center of the circle For outer diameter, Let the area of ​​the annular region with inner diameter be denoted as . The threshold method is used to detect overexposed and underexposed pixels in the annular region, and its total area is recorded as . When overexposed and underexposed pixels account for more than a certain proportion The annular region, i.e., the condition Upon establishment, update the outer diameter. That is, reduce the outer diameter; repeat the above process to select a new annular region until the condition is no longer met, and then use the latest... The value is used as the optimal outer diameter for unfolding the annulus in the borehole inner wall image; at the same time, As the inner diameter of the annulus unfolded from the borehole inner wall image, where It is an adjustable scaling factor; it is generally recommended to set the area percentage as described above. The value ranges from 0.7 to 0.8, and the proportionality coefficient is... The value range is 0.6 to 0.8;

[0043] S14. Unfold the determined annular region image into a rectangular narrow-band image through polar coordinate mapping and interpolation operations, and record the height of the unfolded image. ,Width .

[0044] Furthermore, step S2 specifically includes:

[0045] S21. From the image to be stitched The process automatically selects the local image patch with the highest information entropy as the template. Specifically, it involves selecting the image to be stitched... by Divided into several grids of size Based on the concept of entropy in information theory, the image block with the largest amount of information is selected as the template image, denoted as [image block name]. ;

[0046] S22: Employing a grid-accelerated template matching method in the reference image To quickly register two images, the method involves finding the most similar local image patch to the template image. Specifically, in the coarse matching stage, a grid is used as the basic matching unit to search for the template image within the reference image. During the search, the grid moves horizontally or vertically by the width or height of one template image. After each movement, the similarity between the grid region in the current reference image and the template image is calculated. The grid position with the highest similarity (i.e., the smallest difference) is recorded as the optimal matching position for coarse matching. Then, in the fine matching stage, the optimal matching position obtained from coarse matching is used to perform a more refined search around it. At this stage, the search step size is reduced to half the height or width of the template image. Using the current optimal matching point as the center, the grid moves one step up / down and one step left / right. This process is repeated continuously, with the step size halved each time, and a new similarity is calculated and compared with the current optimal matching point. If a better matching point is found, the optimal matching position is updated. This process is repeated until the step size is reduced to a preset minimum value, i.e., the step size is reduced to 0. At this point, the reference image is obtained. and the image to be stitched The coordinates of the matching points are denoted as follows: and ;

[0047] S23. Calculate the vertical and horizontal offsets of the image to be stitched relative to the reference image, respectively. .

[0048] Furthermore, step S3 specifically includes:

[0049] S31. Shift all columns of the image to be stitched to the left in a circular fashion. One pixel, that is, the horizontal offset obtained from image registration. Cyclic translation is performed until the image is horizontally aligned with the reference image. Cyclic translation means moving a column of pixels corresponding to a horizontal offset from one side to the other. The aligned image to be stitched is denoted as [image name missing]. ;

[0050] S32. For images that are already horizontally aligned and images , record the image The height is The overlapping area between the two was determined as: image From the middle Arrive at the The sub-images corresponding to all columns of a row are denoted as ,image From the first line to the second line The sub-images corresponding to all columns of a row are denoted as The remaining parts of the two images are non-overlapping regions.

[0051] S33, Regarding the image and images The images are stitched together, retaining the original pixel values ​​in the non-overlapping areas and linearly fusing the pixels in the overlapping areas row by row to obtain a new stitched image of the borehole inner wall. Specifically, linear weights are calculated for each row of pixels in the overlapping areas. row index The linear fusion formula is: ,in For the pixel values ​​of a certain row after merging, For reference image The pixel values ​​of a certain row in the overlapping region. Images to be stitched The overlapping region corresponds to the row pixel value. When it is close to the non-overlapping region of the reference image, the overlapping region of the reference image has a higher weight. When it is close to the non-overlapping region of the image to be stitched, the overlapping region of the image to be stitched has a higher weight. This allows for better image fusion and reduces stitching artifacts. The height of the stitched image obtained is [missing information]. .

[0052] Furthermore, the algorithm used in this application tested videos with frame rates exceeding 20 frames per second and durations exceeding 10 minutes. The total number of video frames ranged from a minimum of 12,120 frames to a maximum of 17,325 frames. The recorded borehole data originated from a geological engineering survey. The processor used in the tests was an Intel(R) Core(TM) i5-10400 CPU with 6 cores. The stitched image quality analysis combined visual analysis with numerical image quality evaluation. SSIM and PSNR were used to calculate image similarity to measure the matching effect, and MI, NMI, SF, STD, and AG were used as image fusion quality evaluation indicators. Experiments showed that the stitching effect of the borehole inner wall images was good under various interference conditions such as changes in lighting, lens rotation, and missing or inaccurate orientation information.

[0053] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of embodiments of this disclosure upon considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A robust stitching method for borehole inner wall images under multi-interference imaging conditions, characterized in that, The process includes the following steps: S1, unfolding the acquired forward-looking borehole wall image into a narrow-band image: including locating the center of the annular region to be unfolded from the borehole wall image. Detect overexposed and underexposed interference areas to determine the outer diameter of the unfolded ring. and inner diameter The annular region image is unfolded into a rectangular narrow-band image through polar coordinate mapping and interpolation. The height of the unfolded image is denoted as... ,Width S2. Register the two consecutive narrowband images that have been unfolded: the previous frame is called the reference image and denoted as . , record the image The height is The next frame is called the image to be stitched together and is denoted as . First, the local image patch with the highest information entropy is automatically selected from the images to be stitched as a template. Then, a grid-accelerated template matching method is used to find the most similar local image patch in the reference image, quickly registering the two images and determining the coordinates of the matching points in the reference image and the images to be stitched. and Thus, the vertical and horizontal offsets of the image to be stitched relative to the reference image are respectively , S3. Determine the overlapping area between the reference image and the image to be stitched, and fuse the pixels in the overlapping area to obtain the stitched image of the borehole inner wall: First, shift all columns of the image to be stitched to the left in a circular fashion. Each pixel is aligned horizontally with the reference image; the aligned image to be stitched is denoted as [image name]. Thus the image and images The overlapping region is: image From the middle Arrive at the The sub-images corresponding to all columns of a row are denoted as ,image From the first line to the second line The sub-images corresponding to all columns of a row are denoted as Then, the overlapping pixels of the two images are linearly fused row by row to obtain a new stitched image of the borehole inner wall; S4, repeat the above steps S1 to S3, stitching frame by frame until logging is completed, to obtain a panoramic image of the borehole inner wall; Step S1 includes: S11, for the acquired forward-looking borehole inner wall image, the Hough circle detection method is used to detect the halo formed by the forward-looking camera technology, and the center of the detected halo is used as the center of the expanded circular area of ​​the borehole inner wall image. And denote the radius of the halo as . S12. Calculate the center of the circle. Distances to the top, bottom, left, and right sides of the borehole inner wall image captured by forward view. The shortest of the four distances was selected as the initial outer diameter for unfolding the annulus of the borehole inner wall image. S13, with For step size, for... Center of the circle For outer diameter, Let the area of ​​the annular region with inner diameter be denoted as . The threshold method is used to detect overexposed and underexposed pixels in the annular region, and its total area is recorded as . When overexposed and underexposed pixels occupy more than a certain proportion of the annular area, conditions Area percentage Upon establishment, update the outer diameter. Reduce the outer diameter; repeat the above process to select a new annular region until the condition is no longer met, then use the latest... The value is used as the optimal outer diameter for unfolding the annulus in the borehole inner wall image; at the same time, As the inner diameter of the annulus unfolded from the borehole inner wall image, where It is an adjustable scaling factor; S14, through polar coordinate mapping and interpolation, the determined annular region image is unfolded into a rectangular narrow-band image, and the height of the unfolded image is... ,Width .

2. The method according to claim 1, characterized in that, Step S2 includes: S21, from the image to be stitched The process automatically selects the local image patch with the highest information entropy as the template. Specifically, it involves selecting the image to be stitched... by Divided into several grids of size Based on the concept of entropy in information theory, the image patch with the largest information content is selected as the template image, denoted as [image patch]. S22. A template matching method based on grid acceleration is adopted in the reference image. To quickly register two images, the method involves finding the most similar local image patch to the template image. Specifically, in the coarse matching stage, a grid is used as the basic unit to search for the module image in the reference image. During the search, the grid moves horizontally or vertically by the width or height of one template image. After each movement, the grid region in the current reference image is calculated. With template image similarity Record the grid positions with the highest similarity and the smallest difference. The initial position is used as the optimal matching position for coarse matching. Then, in the fine matching stage, the optimal matching position obtained from coarse matching is used to perform a more refined search around it. At this stage, the search step size is reduced to half the height or width of the template image. Centered on the current optimal matching point, the grid moves one step up / down and one step left / right. This process is repeated continuously, with the step size halved each time, and a new similarity is calculated and compared with the current optimal matching point. If a better matching point is found, the optimal matching position is updated. This process is repeated until the step size is reduced to a preset minimum value of 0, thus obtaining the reference image. and the image to be stitched The coordinates of the matching points are denoted as follows: and S23. Calculate the vertical and horizontal offsets of the image to be stitched relative to the reference image, respectively. , .

3. The method according to claim 1, characterized in that, The steps include: S31, shifting all columns of the image to be stitched to the left in a circular manner. Each pixel is horizontally aligned with the reference image. Cyclic translation means moving a column of pixels from one side by a corresponding horizontal offset to the other side. The aligned image to be stitched is denoted as [image name missing]. S32. For images that are already horizontally aligned and images The overlapping area between the two was determined as: image From the middle Arrive at the The sub-images corresponding to all columns of a row are denoted as In image J, from row 1 to row 2 The sub-images corresponding to all columns of a row are denoted as The remaining parts of each image are non-overlapping regions; S33, for the images and images The images are stitched together, retaining the original pixel values ​​in the non-overlapping areas and linearly fusing the pixels in the overlapping areas row by row to obtain a new stitched image of the borehole inner wall. Specifically, linear weights are calculated row by row for the pixels in the overlapping areas. row index The linear fusion formula is: ,in For the pixel values ​​of a certain row after merging, For reference image The pixel values ​​of a certain row in the overlapping region. Images to be stitched The overlapping region corresponds to the row pixel value. When it is close to the non-overlapping region of the reference image, the overlapping region of the reference image has a higher weight. When it is close to the non-overlapping region of the image to be stitched, the overlapping region of the image to be stitched has a higher weight. This allows for better image fusion and reduces stitching artifacts. The height of the stitched image obtained is [missing information]. .

4. The robust stitching method for borehole inner wall images under multi-interference imaging conditions according to claim 2, wherein the implementation process of step S13 is characterized in that, The area ratio The value ranges from 0.7 to 0.8, and the proportionality coefficient is... The value range is 0.6 to 0.8.

Images