Image quality evaluation system and image quality evaluation method

Abstract

To solve such a problem that previous image quality evaluation often relied on experienced professionals.SOLUTION: An image calibration device is placed in a scene and used for displaying a calibration pattern. An image capturing device captures a first contrast image of the scene and the calibration pattern. A processing device is configured to obtain the first contrast image and a reference image containing the calibration pattern and compare the first contrast image and the calibration pattern in the reference image to generate calibration information. A positioning and calibrating operation of the image capturing device is executed on the basis of the calibration information. After the positioning and calibrating operation of the image capturing device is finished, the image capturing device captures a second contrast image of the scene and the calibration pattern, and the processing device compares the second contrast image and the calibration pattern in the reference image to generate an image quality evaluation result.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to an image processing system, method and device, and in particular to an image quality assessment system, an image quality assessment method and an image calibration device. [Background technology]

[0002] In order to accurately evaluate the quality of the image captured by the image capture device, a complex environmental background is usually set up, for example, various colorful dolls, portraits, and objects are arranged in the environmental background. After the environmental background is set up, the image capture device is set up to capture the environmental background.

[0003] In general, the quality evaluation items of an image captured by an image capture device usually include clarity, contrast, saturation, brightness, noise level, and white balance. Previously, image quality evaluation often relied on experienced experts. However, it takes time to train experts, and they may make subjective evaluations of image quality due to personal preferences. Summary of the Invention [Problem to be solved by the invention]

[0004] The technical problem that the present invention aims to solve is to address the shortcomings of existing techniques and provide an image quality assessment system, an image quality assessment method, and an image calibration device. [Means for solving the problem]

[0005] In order to solve the above technical problems, one technical solution according to the present invention is to provide an image quality assessment system, which includes an image calibration device, an image capture device, and a processing device. The image calibration device is located in a scene and is used to display a calibration pattern. The image capture device photographs the scene and the calibration pattern to capture a first contrast image. The processing device obtains a reference image including the first contrast image and the calibration pattern, compares the first contrast image with the calibration pattern in the reference image to generate a comparison result, and generates calibration information based on the comparison result. A positioning calibration operation of the image capture device is performed based on the calibration information. After completing the positioning calibration operation of the image capture device, the image capture device photographs the scene and the calibration pattern to capture a second contrast image. And the processing device is further configured to compare the second contrast image with the calibration pattern in the reference image to generate an image quality assessment result.

[0006] In order to solve the above technical problems, another technical solution according to the present invention provides an image quality assessment method, which includes: using an image capture device to capture a scene and a calibration pattern displayed by an image calibration device located in the scene to capture a first contrast image; using a processing device to obtain a reference image including the first contrast image and the calibration pattern, compare the first contrast image with the calibration pattern in the reference image to generate a comparison result, generate calibration information according to the comparison result, and perform a positioning calibration operation of the image capture device based on the calibration information; after completing the positioning calibration operation of the image capture device, using the image capture device to capture the scene and the calibration pattern to capture a second contrast image; and using a processing device to compare the second contrast image with the calibration pattern in the reference image to generate an image quality assessment result.

[0007] In order to solve the above technical problems, another technical solution according to the present invention is to provide an image calibration device, which includes a calibration pattern, which is composed of a background block, an analysis block and a positioning block, where the analysis block and the background block provide image quality information, and the positioning block provides position information, which is different from the analysis block.

[0008] One beneficial effect of the present invention is that the image quality assessment system, image quality assessment method and image calibration device provided by the present invention can generate precise positioning calibration operation and quantitative evaluation score for image quality for images captured by an image capture device in complex scenes, making the evaluation of image quality more objective and solving the problem of the camera development cycle being too long.

[0009] In order to further understand the characteristics and technical contents of the present invention, please refer to the following detailed description and illustrations of the present invention. However, the illustrations provided are only for reference and explanation, and are not intended to limit the present invention. [Brief description of the drawings]

[0010] [Figure 1] 1 is a functional block diagram of an embodiment of an image quality assessment system provided by the present invention. [Diagram 2] FIG. 2 is a schematic diagram showing the positional arrangement of the image calibration device, the reference image capture device, and the processing device of FIG. 1; [Diagram 3] FIG. 2 is a schematic diagram showing the positional arrangement of the image proofing device, the evaluation target image capture device, and the processing device shown in FIG. 1. [Figure 4] 1 is a schematic diagram of an embodiment of an image proofing device of the present invention; [Diagram 5] 5 is a flowchart of an embodiment of an image quality evaluation method for the image proofing device applied in FIG. 4. [Figure 6] 11 is a schematic diagram of calibration information regarding a center point displacement amount generated by the processing device. FIG. [Figure 7]FIG. 13 is a schematic diagram of calibration information regarding a rotation angle generated by the processing device. [Figure 8] FIG. 13 is a schematic diagram of calibration information regarding a scale ratio generated by the processing device. [Figure 9] FIG. 13 is a schematic diagram of calibration information regarding a camera tilt angle generated by the processing device. [Figure 10] 1 is a method flow diagram of one embodiment of a quantitative assessment of sharpness performed by a processor. [Figure 11] 4 is a method flow diagram of one embodiment of a quantitative assessment of white balance performed by a processing device. [Figure 12] 1 is a method flow diagram of one embodiment of a quantitative assessment of contrast performed by a processing device. [Figure 13] 1 is a method flow diagram of one embodiment of a quantitative assessment of saturation performed by a processing unit. [Figure 14] 4 is a method flow diagram of one embodiment of a quantitative assessment of image brightness performed by a processing device. [Figure 15] 4 is a method flow diagram of one embodiment of a quantitative assessment of noise level performed by a processing device. [Figure 16] This is a radar chart showing a quantitative evaluation of the image quality of two different cameras. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] The following describes the embodiments of the "image quality evaluation system and image quality evaluation method" disclosed in the present invention through specific examples. Those skilled in the art can understand the advantages and effects of the present invention from the disclosure of this specification. The present invention can be implemented or applied in other different embodiments. Each detail in this specification can be modified and changed equivalently based on various aspects or applications without departing from the spirit of the present invention. In addition, the drawings of the present invention are for simple and schematic illustration only and do not show actual dimensions. The following embodiments will further describe technical matters related to the present invention, but the disclosed contents do not limit the present invention.

[0012] In addition, although various components or signals may be described in this specification by terms such as "first", "second", "third", etc., these components or signals are not limited by these terms. It should be understood that these terms are mainly used to distinguish one component from another component or one signal from another signal. In addition, the term "or" used in this specification may include any one or more combinations of related items according to actual circumstances.

[0013] Figure 1 is a functional block diagram of an embodiment of an image quality assessment system provided by the present invention. Referring to Figure 1, the image quality assessment system includes an image proofing device 1, a reference image capture device 2, an evaluation target image capture device 3 and a processing device 4. The reference image capture device 2 and the evaluation target image capture device 3 are set to photograph the image proofing device 1, and the processing device 4 is electrically connected with the reference image capture device 2 and the evaluation target image capture device 3 at different time points.

[0014] The image calibration device 1 is, for example, a polygonal plate, the image capture devices 2, 3 are, for example, monocular cameras, binocular cameras, or depth cameras, and the processing device 4 is, for example, a personal computer, a server, or a mobile terminal, but the present invention is not limited thereto.

[0015] FIG. 2 is a schematic diagram showing the positional arrangement of the image calibration device, the reference image capture device, and the processing device in FIG. 1. Referring to FIG. 2, the image calibration device 1 is disposed approximately at the center of the scene A, and the image calibration device 1 is a rectangular plate, and a calibration pattern B is displayed on its surface. The calibration pattern B is composed of a background block 11, an analysis block 12, and a positioning block 13. The background block 11 and the analysis block 12 provide image quality information, which includes, for example, clarity, white balance, contrast, saturation, brightness, and noise level. At least one of the color, shape, and pattern of the positioning block 13 is different from the analysis block 12, and the positioning block 13 provides position information. The position information includes, for example, the coordinates and area of ​​the center point.

[0016] The reference image capture device 2 maintains a certain distance from the scene A and the image calibration device 1, and its lens is directed toward the scene A. The reference image capture device 2 is set to photograph the scene A and the calibration pattern B to capture a reference image, which includes the scene A, the image calibration device 1, and the calibration pattern B displayed on the image calibration device 1. The processing device 4 is set to acquire the reference image. It should be noted that the reference image capture device 2 is calibrated, and the image quality of the acquired reference image meets certain image quality evaluation items (e.g., sharpness, contrast, saturation, brightness, noise level, white balance) and can be used as a standard for image quality evaluation.

[0017] Fig. 3 is a schematic diagram showing the positional arrangement of the image calibration device, the evaluation target image capture device, and the processing device in Fig. 1. Referring to Fig. 3, the image calibration device 1 is a rectangular plate body, and is placed at approximately the center position of the scene A. The position, aperture setting, and shutter setting of the evaluation target image capture device 3 are the same as those of the reference image capture device 2, but since the image quality of the image captured by the evaluation target image capture device 3 may differ from the image quality of the image captured by the reference image capture device 2, it is necessary to perform image quality evaluation and calibrate the evaluation target image capture device 3 if necessary.

[0018] The lens of the evaluation target image capture device 3 is directed towards the scene A, and the evaluation target image capture device 3 is configured to photograph the scene A and the calibration pattern B to capture a first contrast image. The first contrast image includes the scene A, the image calibration device 1, and the calibration pattern B displayed on the image calibration device 1. The processing device 4 is configured to obtain the first contrast image.

[0019] The calibration pattern B is composed of a background block 11, an analysis block 12, and a positioning block 13, and the position of the analysis block 12 is approximately in the center of the calibration pattern B, and includes at least three different patterns. The positioning block 13 is located on the periphery of the calibration pattern B, and any color displayed in the positioning block 13 is different from the color displayed in the background block 11. With such a design of the calibration pattern B, after the processing device 4 acquires the reference image and the first contrast image, the processing device 4 compares the positioning block 13 of the calibration pattern B in the first contrast image with the positioning block 13 of the calibration pattern B in the reference image to generate a comparison result, and generates calibration information based on the comparison result. The calibration information may include a center translation, a rotation angle, a scaling ratio, and a camera tilt angle. Then, based on the calibration information provided by the processing device 4, the user manually performs a positioning calibration operation of the evaluation target image capture device 3.

[0020] After performing the positioning and calibration operation of the evaluation object image capture device 3, the evaluation object image capture device 3 again captures the scene A and the calibration pattern B to capture a second contrast image. The processing device 4 obtains the second contrast image.

[0021] After the processing device 4 acquires the second contrast image, the processing device 4 compares the calibration pattern B in the second contrast image with the calibration pattern B in the reference image to generate an image quality assessment result of the second contrast image.

[0022] If necessary, the image quality evaluation system may also include a movement mechanism 5. The movement mechanism 5 may include moving parts, rotating parts, or any combination thereof. The movement mechanism 5 is connected to the evaluation target image capture device 3. Based on the calibration information generated by the processing device 4, the processing device 4 controls the movement mechanism 5 to change the orientation and position of the evaluation target image capture device 3, and the movement mechanism 5 performs a positioning calibration operation of the evaluation target image capture device 3. This automates the positioning calibration operation and achieves higher accuracy than human operation.

[0023] If necessary, the number of the image calibration devices 1 may be multiple. For example, the number of the image calibration devices 1 may be five, and the image calibration devices 1 may be arranged at the four corners and the central position of the scene A, respectively. In this way, the accuracy of the positioning calibration operation and the image quality evaluation can be improved.

[0024] 4 is a schematic diagram of one embodiment of the image calibration device of the present invention. Referring to FIG. 4, the position of the analysis block 12 is near the center of the calibration pattern B, and any color displayed in the analysis block 12 is different from the color displayed in the background block 11. The analysis block 12 includes at least three different patterns, and different patterns means that at least one of the colors and shapes is different.

[0025] The analysis block 12 includes a first sub-analysis block 121, a second sub-analysis block 122, and a third sub-analysis block 123, and the first sub-analysis block 121, the second sub-analysis block 122, and the third sub-analysis block 123 differ in at least one of color and shape.

[0026] The first sub-analysis block 121 has an oblique angle and includes a pair of a first color block 1211 and a second color block 1212 of complementary colors. The first color block 1211 and the second color block 1212 are quadrilaterals. Different degrees of sharpness are generated on the oblique side of the first sub-analysis block 121. The alternating parts of the first color block 1211 and the second color block 1212 generate a frequency of jaggies, which allows the sharpness of the first sub-analysis block 121 to be calculated. The second sub-analysis block 122 includes third color blocks 1221A, 1221B, 1221C, 1221D of different grayscale values ​​and fourth color blocks 1222 and fifth color blocks 1223 of complementary colors. The third sub-analysis block 123 includes a sixth color block 1231A, 1231B, 1231C, 1231D, 1231E, and 1231F of at least six colors.

[0027] The first and second color blocks in the first sub-analysis block 121 are rectangular, and are black and white, respectively. The third, fourth and fifth color blocks in the second sub-analysis block 122 are also rectangular, and the third color blocks are different shades of gray, and the fourth and fifth color blocks are black and white, respectively. The sixth color block in the third sub-analysis block 123 is also rectangular, and the sixth color blocks are pink, blue, purple, green, yellow and orange, respectively.

[0028] Optionally, the first and second color blocks are circular, triangular, or other polygonal, and the first and second color blocks can be red and green, or yellow and purple, respectively. The fourth and fifth color blocks are also circular, triangular, or other polygonal, and the fourth and fifth color blocks can be red and green, or yellow and purple, respectively. The sixth color block may be six or more in number and six or more in color.

[0029] Through the design of the analysis block 12 in FIG. 4, image comparison of complex scenes can be realized.

[0030] The positioning block 13 is located around the calibration pattern B, and any color displayed in the positioning block 13 is different from the color displayed in the background block 11. The positioning block 13 includes a first sub-positioning block 131, a second sub-positioning block 132, a third sub-positioning block 133, and a fourth sub-positioning block 134, and the first sub-positioning block 131, the second sub-positioning block 132, the third sub-positioning block 133, and the fourth sub-positioning block 134 are located at the upper left corner, the upper right corner, the lower right corner, and the lower left corner of the calibration pattern B, respectively, and surround the analysis block 12. In this embodiment, the calibration pattern B, the first sub-positioning block 131, the second sub-positioning block 132, the third sub-positioning block 133, and the fourth sub-positioning block 134 are rectangular areas, but the present invention is not limited thereto.

[0031] Each of the first sub-positioning block 131, the second sub-positioning block 132, the third sub-positioning block 133, and the fourth sub-positioning block 134 includes a plurality of color blocks of different colors, the color of any of the color blocks of the first sub-positioning block 131, the second sub-positioning block 132, the third sub-positioning block 133, and the fourth sub-positioning block 134 is different from the color of the background block 11, and the arrangement patterns of the color blocks of any of the color blocks of the first sub-positioning block 131, the second sub-positioning block 132, the third sub-positioning block 133, and the fourth sub-positioning block 134 do not overlap.

[0032] Specifically, the first sub-positioning block 131 is located at the upper left corner of the calibration pattern B, and the upper half of the first sub-positioning block 131 has two color blocks from left to right, which respectively have a first color and a second color, and the lower half of the first sub-positioning block 131 has two color blocks from left to right, which respectively have a third color and a fourth color.

[0033] The second sub-positioning block 132 is located in the upper right corner of the calibration pattern B, and the upper half of the second sub-positioning block 132 has two color blocks from left to right, which respectively have the second color and the first color, and the lower half of the second sub-positioning block 132 has two color blocks from left to right, which respectively have the fourth color and the third color.

[0034] The third sub-positioning block 133 is located in the lower right corner of the calibration pattern B, and the upper half of the third sub-positioning block 133 has two color blocks from left to right, which have the fourth color and the third color, respectively, and the lower half of the third sub-positioning block 133 has two color blocks from left to right, which have the first color and the second color, respectively.

[0035] The fourth sub-positioning block 134 is located in the lower left corner of the calibration pattern B, and the two color blocks from left to right in the upper half of the fourth sub-positioning block 134 respectively have the third color and the fourth color, and the two color blocks from left to right in the lower half of the fourth sub-positioning block 134 respectively have the second color and the first color.

[0036] The first color, the second color, the third color, and the fourth color are, for example, red, green, blue, and black, but the present invention is not limited to this and can be any color different from the color of the background block 11.

[0037] Through the design of the positioning block 13 in FIG. 4, image positioning of complex scenes can be realized.

[0038] 5 is a flowchart of an embodiment of an image quality evaluation method of the image calibration device 1 applied in FIG. 4. Referring to FIG. 5, in step S501, the reference image capture device 2 is positioned to capture the scene A and the calibration pattern B to capture the reference image, so that the processing device 4 acquires a reference image. In step 502, the evaluation target image capture device 3 is positioned to capture the scene A and the calibration pattern B to capture the first contrast image, so that the processing device 4 acquires a first contrast image.

[0039] In step S503, the processing device 4 is configured to analyze the positioning block 13 in the reference image and the first contrast image to obtain the reference position information and the first position information, respectively. Specifically, the processing device 4 performs a binarization process on the reference image and the first contrast image to obtain the contours of the positioning block 13 in the reference image and the first contrast image.

[0040] In step S504, the processing device 4 is arranged to compare the first position information with the reference position information to generate a comparison result, and to generate calibration information for the evaluated image capture device 3 based on the comparison result.

[0041] In step S505, the processing device 4 is arranged to perform a positioning and calibration operation of the evaluation target image capture device 3 based on the calibration information. Specifically, the positioning and calibration operation of the evaluation target image capture device 3 is performed by the moving mechanism 5.

[0042] In step S506, the processing device 4 is arranged to determine whether the positioning calibration operation is successfully performed. If it is successful, proceed to step S507. If not, return to step S503. Specifically, the success or failure of the positioning calibration operation is determined based on a user-defined tolerance range. If the distance difference between the center position of the calibration pattern of the first contrast image after calibration and the center position of the calibration pattern of the reference image is within the tolerance range, the positioning calibration operation is deemed to be successful, otherwise it is deemed to be unsuccessful.

[0043] In step S507, the processing device 4 arranges the evaluation target image capture device 3 to capture the second contrast image by photographing the scene A and the calibration pattern B. In step S508, the processing device 4 arranges the processing device 4 to compare the analysis block 12 in the second contrast image with the analysis block 12 in the reference image and obtain a comparison result.

[0044] In step S509, the processing device 4 is arranged to perform a quantitative analysis of the image quality of the second contrast image based on the comparison between the second contrast image and the reference image.

[0045] In step S510, the processing device 4 is arranged to determine whether the quantitative analysis of image quality has been successfully performed. If so, proceed to step S511. If not, return to step S503. In particular, the success or failure of the quantitative analysis of image quality is determined based on a user-defined lower limit of the evaluation score. If the evaluation score is equal to or greater than the lower limit of the evaluation score, the quantitative analysis of image quality is deemed successful, otherwise it is deemed unsuccessful.

[0046] In step S511, the processing device 4 is arranged to generate an image quality assessment result of the second contrast image.

[0047] Through the image quality evaluation method of Figure 5, even in a complex scene, an accurate positioning and calibration operation can be performed on the image capture device 3 to be evaluated, and an accurate quantitative evaluation can be made on the image quality of the image captured by the image capture device 3 to be evaluated.

[0048] FIG. 6 is a schematic diagram of how the processing device 4 generates calibration information of the center point movement amount. As shown in FIG. 6, the intersection of the first straight line L1 and the second straight line L2 is the first center point P1 of the calibration pattern B of the reference image K, and the intersection of the third straight line L3 and the fourth straight line L4 is the second center point P2 of the calibration pattern B of the first contrast image M. The processing device 4 obtains the coordinates of the first center point P1 and the second center point P2, calculates the center point movement amount between the first center point P1 and the second center point P2, and provides the calibration information of the center point movement amount. This calibration information of the center point movement amount includes a movement distance indication and a movement direction indication D1 of the image capture device 3 to be evaluated.

[0049] Specifically, the processing device 4 performs a binarization process on the reference image K and the first contrast image M, and finds the contours of rectangular objects in the reference image K and the first contrast image M. Then, the processing device 4 determines whether each rectangular object includes color blocks of the four defined colors. If so, the rectangular object is marked as a sub-positioning block. Thus, the processing device 4 marks the first sub-positioning block 131, the second sub-positioning block 132, the third sub-positioning block 133, and the fourth sub-positioning block 134 in the reference image K and the first contrast image M, and finds the positioning center points of the first sub-positioning block 131, the second sub-positioning block 132, the third sub-positioning block 133, and the fourth sub-positioning block 134. Next, the first straight line L1 and the second straight line L2 are defined based on the four positioning center points in the reference image K, and the third straight line L3 and the fourth straight line L4 are defined based on the four positioning center points in the first contrast image M.

[0050] FIG. 7 is a schematic diagram of how the processing device 4 generates the calibration information of the rotation angle. As shown in FIG. 7, the fifth line L5 and the sixth line L6 of the reference image K are parallel to each other, and the seventh line L7 and the eighth line L8 of the first contrast image M are also parallel to each other. The fifth line L5 and the seventh line L7 intersect to generate a first angle G1, and the sixth line L6 and the eighth line L8 intersect to generate a second angle G2. The processing device 4 calculates the average value of the first angle G1 and the second angle G2 to define how much the calibration pattern B of the first contrast image M is rotated relative to the calibration pattern B of the reference image K. Ideally, the first angle G1 is equal to the second angle G2, but in reality there is a slight difference between the first angle G1 and the second angle G2, so the average value of the first angle G1 and the second angle G2 is defined as the rotation angle. Finally, the processing device 4 provides rotation angle calibration information, which includes the rotation angle indication and the rotation direction indication D2 of the image capture device 3 to be evaluated.

[0051] Specifically, the fifth straight line L5 and the sixth straight line L6 are defined based on four positioning center points in the reference image K, and the seventh straight line L7 and the eighth straight line L8 are defined based on four positioning center points in the first contrast image M.

[0052] FIG. 8 is a schematic diagram of how the processing device 4 generates calibration information of the scale ratio. As shown in FIG. 8, the processing device 4 obtains the areas of the first sub-positioning block 131, the second sub-positioning block 132, the third sub-positioning block 133, and the fourth sub-positioning block 134 in the reference image K and the first contrast image M, and calculates the average value by summing the areas of the first sub-positioning block 131, the second sub-positioning block 132, the third sub-positioning block 133, and the fourth sub-positioning block 134 in the reference image K to generate a first area average value. The processing device 4 calculates the average value by summing the areas of the first sub-positioning block 131, the second sub-positioning block 132, the third sub-positioning block 133, and the fourth sub-positioning block 134 in the first contrast image M to generate a second area average value. The processing device 4 calculates the ratio between the second area average value and the first area average value to calculate the scale ratio, and provides calibration information of the scale ratio. This scale calibration information includes a movement direction indication D3 of the image capture device 3 to be evaluated.

[0053] Fig. 9 is a schematic diagram of the processing device 4 generating the calibration information of the camera tilt angle. As shown in Fig. 9, the processing device 4 calculates the area ratio of the first sub-positioning block 131, the second sub-positioning block 132, the third sub-positioning block 133 and the fourth sub-positioning block 134 in the reference image K and the first contrast image M to calculate the camera tilt angle, and provides the calibration information of the camera tilt angle. The calibration information of the camera tilt angle includes a moving direction indication D4 of the image capture device 3 to be evaluated.

[0054] 10 is a flowchart of an example method for the processing device 4 to perform a quantitative evaluation of sharpness. Referring to FIG. 4 and FIG. 10, in step S1001, the processing device 4 analyzes the modulation transfer function (MTF) of the first sub-analysis block in the reference image and the second contrast image, and obtains a reference modulation transfer function and a contrast modulation transfer function, respectively. In step S1002, the processing device 4 calculates the deviation percentage of the contrast modulation transfer function to the reference modulation transfer function. In step S1003, the processing device 4 generates a quantitative evaluation result of the sharpness of the second contrast image based on the deviation percentage.

[0055] For example, if the deviation percentage of the transfer function of the contrast image from the reference modulation transfer function is less than 5%, the quantitative evaluation score of the clarity of the second contrast image is 7 to 10 points. If the deviation percentage of the contrast modulation transfer function from the reference modulation transfer function is within a range of 5% to 10%, the quantitative evaluation score of the clarity of the second contrast image is 4 to 6 points. If the deviation percentage of the contrast modulation transfer function from the reference modulation transfer function is within a range of 10% to 15%, the quantitative evaluation score of the clarity of the second contrast image is 1 to 3 points. If the deviation percentage of the contrast modulation transfer function from the reference modulation transfer function is more than 15%, the quantitative evaluation score of the clarity of the second contrast image is 0 points.

[0056] FIG. 11 is a flowchart of a method of a specific embodiment of the processing device 4 quantitatively evaluating the white balance. Referring to FIG. 4 and FIG. 11, in step S1101, the processing device 4 analyzes the color space values ​​in the background blocks of the reference image and the second contrast image, and obtains the contrast color space value and the reference color space value, respectively. Specifically, the color space value is a CIELAB color space value or a CIELCH color space value. In step S1102, the processing device 4 calculates the deviation percentage of the contrast color space value to the reference color space value. In step S1103, the processing device 4 generates a quantitative evaluation result of the white balance of the second contrast image based on the deviation percentage.

[0057] FIG. 12 is a flowchart of an example method in which the processing device 4 performs a quantitative evaluation of contrast. Referring to FIG. 4 and FIG. 12, in step S1201, the processing device 4 analyzes the grayscale of each color block of the second sub-analysis block of the reference image and the second contrast image, respectively, to obtain a plurality of contrast grayscales and a plurality of reference grayscales. In step S1202, the processing device 4 calculates a plurality of deviation percentages between the plurality of contrast grayscales and the plurality of reference grayscales. In step S1203, the processing device 4 calculates an average value of the plurality of deviation percentages. In step S1204, the processing device 4 generates a quantitative evaluation result of the contrast of the second contrast image based on the average value of the plurality of deviation percentages.

[0058] FIG. 13 is a flowchart of an example method for the processing device 4 to perform quantitative evaluation of saturation. Referring to FIG. 4 and FIG. 13, in step S1301, the processing device 4 analyzes the modulation transfer functions of the third sub-analysis block of the reference image and the second contrast image to obtain a reference modulation transfer function and a contrast modulation transfer function, respectively. In step S1302, the processing device 4 calculates the deviation percentage of the contrast image modulation transfer function to the reference image modulation transfer function. In step S1303, the processing device 4 generates a quantitative evaluation result of the saturation of the second contrast image based on the deviation percentage.

[0059] FIG. 14 is a flow chart of an example method for the processing device 4 to perform a quantitative evaluation of image brightness. Referring to FIG. 4 and FIG. 14, in step S1401, the processing device 4 analyzes the average grayscale of all color blocks of the reference image and the second contrast image. In step S1402, the processing device 4 calculates the deviation percentage of the average grayscale of the second contrast image to the average grayscale of the reference image. In step S1403, the processing device 4 generates a quantitative evaluation result of the image brightness of the second contrast image based on the deviation percentage.

[0060] FIG. 15 is a flowchart of an embodiment of a method for quantitatively evaluating the noise level by the processing device 4. Referring to FIG. 4 and FIG. 15, in step S1501, the processing device 4 analyzes the peak signal-to-noise ratios of the second sub-analysis blocks of the reference image and the second contrast image, and obtains the peak signal-to-noise ratio of the contrast and the reference peak noise ratio, respectively. In step S1502, the processing device 4 calculates the deviation percentage of the peak signal-to-noise ratio of the contrast of the second contrast image to the reference peak noise ratio. In step S1503, the processing device 4 generates a quantitative evaluation result of the noise level of the second contrast image based on the deviation percentage.

[0061] Through the quantitative analysis method of the six image quality items shown in Figures 10 to 15, the processing device 4 can obtain the quantitative scores of the six quality items of the image captured by the image capture device 3 to be evaluated. Finally, the processing device 4 creates a radar chart based on these quantitative scores and displays the evaluation results of clarity, white balance, contrast, saturation, image brightness, and noise level. Since each quality item of the image is quantitatively evaluated, the user can easily determine whether the quality of images captured by cameras with different specifications is similar, making the evaluation of image quality more objective and solving the problem of long camera development cycles.

[0062] FIG. 16 shows a radar chart of the quantitative evaluation of the image quality of two different cameras. As shown in FIG. 16, the items of the quantitative evaluation of the image quality include sharpness, white balance, contrast, saturation, brightness, and noise level. The sharpness score of the first camera T1 is higher than the sharpness score of the second camera T2. The white balance score of the first camera T1 is higher than the white balance score of the second camera T2. The contrast score of the first camera T1 is lower than the contrast score of the second camera T2. The saturation score of the first camera T1 is higher than the saturation score of the second camera T2. The brightness score of the first camera T1 is lower than the brightness score of the second camera T2. The noise level score of the first camera T1 is lower than the noise level score of the second camera T2.

[0063] [Beneficial Effects of the Invention] One beneficial effect of the present invention is that the image quality evaluation system, image quality evaluation method and image calibration device provided by the present invention can perform precise positioning and calibration operation and give a quantitative evaluation score to the image quality of the image captured by the image capture device in a complex scene, which makes the evaluation of image quality more objective and solves the problem of a long camera development cycle.

[0064] The contents disclosed above are merely preferred possible embodiments of the present invention, and do not limit the scope of the claims of the present invention. Therefore, all equivalent technical modifications made based on the contents of the specification and accompanying drawings of the present invention are intended to be included in the scope of the claims of the present invention. [Explanation of symbols]

[0065] 1 Image correction device 2. Reference Image Capture Device 3. Image capture device to be evaluated 4 Processing Equipment 5 Moving mechanism A Scene B Calibration Pattern 11 Background Blocks 12 Analysis Block 121 First sub-analysis block 1211 First Color Block 1212 Second Color Block 122 Second sub-analysis block 1221A, 1221B, 1221C, 1221D 3rd Color Block 1222 4th color block 1223 5th color block 1231A, 1231B, 1231C, 1231D, 1231E, 1231F 6th Color Block 123 Third sub-analysis block 13 Positioning block 131 First sub-positioning block 132 Second Sub-positioning Block 133 3rd Sub-positioning Block 134 4th Sub-positioning Block K Reference Image M First contrast image L1~L8 1st line to 8th line G1 First angle G2 Second Angle P1 First center point P2 Second center point D1 Direction of movement D2 Turning direction indication D3 Direction of movement D4 Direction of movement T1 First Camera T2 Second Camera S501-S511, S1001-S1003, S1101-S1103, S1201-S1204, S1301-S1303, S1401-S1403, S1501-S1503 Step

Claims

1. an image calibration device located within the scene and adapted to display a calibration pattern; an image capture device that images the scene and the calibration pattern to obtain a first contrast image; a processing device arranged to obtain the first contrast image and a reference image including the calibration pattern, compare the first contrast image and the calibration pattern in the reference image to generate a comparison result, and generate calibration information based on the comparison result; An image quality assessment system comprising: a calibration operation of the image capture device is performed based on the calibration information; the image capture device is configured to capture the scene and the calibration pattern to obtain a second contrast image after completing a positioning calibration operation of the image capture device, and the processing device is configured to compare the second contrast image and the calibration pattern in the reference image to generate an image quality assessment result.

1. An image quality assessment system comprising:

2. the calibration pattern includes a positioning block; The processing device includes: analyzing the positioning block in the first contrast image to obtain first position information; The positioning block in the reference image is analyzed to obtain reference position information; comparing the first position information and the reference position information to obtain the calibration information for performing the positioning calibration operation; 2. The image quality assessment system of claim 1, arranged to:

3. the positioning calibration operation includes configuring the processing device to control a movement mechanism coupled to the image capture device based on the calibration information to adjust an orientation and position of the image capture device; The image quality assessment system according to claim 2 , wherein the calibration information includes a center point movement amount, a rotation angle, a scale ratio, and a camera tilt angle.

4. 2. The image quality assessment system of claim 1, wherein the calibration pattern includes an analysis block, and the processing device is arranged to compare the second contrast image with the analysis block in the reference image to generate the image quality assessment result.

5. The image quality evaluation system according to claim 1 , wherein the image quality evaluation results include a sharpness evaluation result, a white balance evaluation result, a contrast evaluation result, a saturation evaluation result, an image brightness evaluation result, and a noise level evaluation result.

6. 2. The image quality assessment system of claim 1, further comprising five image proofing devices, said five image proofing devices being identical to one another and located at the four corners and a center of said scene, respectively.

7. an image capture device captures an image of a scene and a calibration pattern displayed by an image calibration device located within the scene to obtain a first contrast image; a processing device acquiring the first contrast image and a reference image including the calibration pattern, comparing the first contrast image with the calibration pattern in the reference image to generate a comparison result, and generating calibration information based on the comparison result; a positioning calibration operation performed on the image capture device is based on the calibration information; and the image capture device captures an image of the scene and the calibration pattern to obtain a second contrast image after completing the positioning calibration operation; the processing device compares the second contrast image with the calibration pattern in the reference image to generate an image quality assessment result.

13. A method for evaluating image quality comprising:

8. 8. The image quality assessment method of claim 7, wherein the calibration pattern includes an analysis block, and the processing device is configured to compare the analysis block of the second contrast image and the reference image to generate the image quality assessment result.

9. the calibration pattern includes an analysis block and a background block; the processor analyzes the second contrast image, an analysis block of the second contrast image, or a background block of the second contrast image to obtain a contrast modulation transfer function, a contrast color space value, a contrast grayscale, a contrast average grayscale, or a contrast peak signal to noise ratio; said processing device analyzing said reference image, an analysis block of said reference image or a background block of said reference image to obtain a reference modulation transfer function, a reference color space value, a reference grayscale, a reference average grayscale or a reference peak signal to noise ratio; 8. The image quality evaluation method of claim 7, wherein the processing device generates a sharpness evaluation result, a white balance evaluation result, a contrast evaluation result, a saturation evaluation result, an image brightness evaluation result, or a noise level evaluation result of the image quality evaluation result based on a deviation percentage of the contrast modulation transfer function from the reference modulation transfer function, a deviation percentage of the contrast color space value from the reference color space value, a deviation percentage of the contrast grayscale from the reference grayscale, a deviation percentage of the contrast average grayscale from the reference average grayscale, or a deviation percentage of the contrast peak signal to noise ratio from the reference peak signal to noise.

10. a calibration pattern consisting of a background block, an analysis block and a positioning block; the analysis block and the background block provide image quality information; the positioning block provides position information, and the positioning block is different from the analysis block; An image proofreading device comprising:

11. 11. The image proofing apparatus of claim 10, wherein the positioning block includes at least one color, and the color of the background block is different from the color of the positioning block.

12. 11. An image proofing apparatus according to claim 10, wherein said analysis block comprises at least three sub-analysis blocks, said three sub-analysis blocks differing from each other in colour or shape.

13. 11. The image calibration apparatus of claim 10, wherein the positioning block includes a plurality of sub-positioning blocks, the sub-positioning blocks being located at a plurality of corners of the calibration pattern, respectively.

14. 14. The image proofing apparatus of claim 13, wherein each sub-positioning block includes a plurality of color blocks of different colors, and the arrangement of the color blocks within the sub-positioning blocks does not overlap.

15. 11. The image proofing device of claim 10, wherein the analysis block includes a first sub-analysis block, a second sub-analysis block and a third sub-analysis block, the first sub-analysis block includes a pair of first color blocks and a pair of second color blocks which are complementary to each other, the second sub-analysis block includes a plurality of third color blocks having different grayscales and a fourth color block and a fifth color block which are complementary to each other, and the third sub-analysis block includes a plurality of sixth color blocks having at least six kinds of colors.

Images