CN112954310A - Image quality detection method, device, computer equipment and readable storage medium - Google Patents
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Abstract
The invention discloses an image quality detection method, an image quality detection device, computer equipment and a readable storage medium, wherein the image quality detection method comprises the following steps: acquiring a test image of the image equipment; testing the image quality index of the test image; determining an image quality score of the image equipment based on the test result of the image quality index; wherein the image quality indicator comprises at least one of resolution, uniformity, distortion, color, noise, and dynamic range. According to the method, various image quality indexes can be automatically tested according to the pictures shot by the image equipment, and the quantized image quality scores are output according to the test results, so that a user can be helped to judge the imaging quality condition of the image equipment more intuitively.
Description
Technical Field
Embodiments of the present invention relate to computer technologies, and in particular, to a method and an apparatus for detecting image quality, a computer device, and a storage medium.
Background
With the popularization and use of image equipment such as cameras and cameras in various industries, the requirements for the image quality of the image equipment in the fields of mobile phones, automobiles, security and the like are higher and higher, so the detection requirements for the image quality are gradually increased. However, such a detection method is inconvenient for detecting the image quality in various aspects of the imaging device, and the performance parameter obtained by detection is only one index, so that the user needs to judge the image quality by experience, and the user with insufficient experience cannot intuitively judge the quality of the image quality.
Disclosure of Invention
In view of the above, the present invention provides an image quality detection method, an image quality detection apparatus, a computer device, and a readable storage medium, which can test various imaging quality indexes of an imaging device and output a quantized image quality score.
In a first aspect, an embodiment of the present invention provides an image quality detection method, including:
acquiring a test image of the image equipment;
testing the image quality index of the test image;
determining an image quality score of the image equipment based on the test result of the image quality index;
wherein the image quality indicator comprises at least one of resolution, uniformity, distortion, color, noise, and dynamic range.
According to the image quality detection method, various image quality indexes can be automatically tested according to the pictures shot by the image equipment, and quantitative image quality scores are output according to the test results, so that a user can be helped to judge the imaging quality condition of the image equipment more intuitively.
In one embodiment, the number of the image quality indicators is plural, and the step of determining the image quality score of the video device based on the test result of the image quality indicators comprises:
calculating the single score of each image quality index according to the test result of each image quality index and a preset weight;
and determining the image quality score of the image equipment based on the single score of each image quality index.
In one embodiment, the method further comprises:
acquiring image quality scores of a plurality of image devices;
ranking the image quality of the video device based on the image quality score.
In one embodiment, the step of ranking the image quality of the video device based on the image quality score comprises:
acquiring equipment information of the plurality of image equipment;
classifying the plurality of image devices according to the image device information;
ranking the image quality of the image devices within each classification based on the image quality scores.
In one embodiment, the image device information includes a number of pixels and/or a field angle.
In one embodiment, the number of the verification image vectors is multiple, and the method further includes:
acquiring the position information of the test image;
and reproducing the test of the image quality index according to the position information.
In a second aspect, an embodiment of the present invention further provides an image quality detection apparatus, where the apparatus includes:
the acquisition module is used for acquiring a test image of the image equipment;
the test module is used for testing the image quality index of the test image;
the grading module is used for determining the image quality grade of the image equipment based on the test result of the image quality index;
wherein the image quality indicator comprises at least one of resolution, uniformity, distortion, color, noise, and dynamic range.
In one embodiment, the apparatus further comprises:
the ranking module is used for obtaining image quality scores of a plurality of image devices and ranking the image quality of the image devices based on the image quality scores.
The image quality detection device can automatically test various image quality indexes according to the pictures shot by the image equipment, and can output quantized image quality scores according to test results, so that a user can be helped to judge the imaging quality condition of the image equipment more intuitively.
In a third aspect, an embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the image quality detection method as described above.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the image quality detection method as described above.
Drawings
FIG. 1 is a flow chart illustrating an exemplary method for detecting image quality;
FIG. 2 is a flow diagram that illustrates the steps of determining an image quality score for a device based on the results of a test of an image quality indicator, according to one embodiment;
FIG. 3 is a flowchart illustrating an image quality detection method according to another embodiment;
FIG. 4 is a flow diagram that illustrates the steps of ranking image quality of video devices based on image quality scores according to one embodiment;
FIG. 5 is a flowchart illustrating an image quality detection method according to another embodiment;
FIG. 6 is a schematic diagram showing the structure of an image quality detection apparatus according to an embodiment;
fig. 7 is a schematic structural diagram of an image quality detection apparatus in another embodiment.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Fig. 1 is a schematic flowchart of an image quality detection method in an embodiment, and as shown in fig. 1, in an embodiment, an image quality detection method may specifically include:
step S120: and acquiring a test image of the imaging equipment.
Specifically, the image device may be a device that performs shooting independently, or a component that is integrated in a mobile phone, an automobile, an unmanned aerial vehicle, or the like to implement an image acquisition function, and the image device may include a camera, a video camera, or a lens therein, a photosensitive element, or the like, and the specific type of the image device may be determined according to actual detection requirements. Before image quality detection is carried out on the image equipment, a test image for detection needs to be obtained firstly, the number and the content of the test image can be determined according to actual detection requirements, the test image can be an image shot in the normal working process of the image equipment, can also be a color card picture or a gray-scale picture shot specially for detection, and the like, a complete image quality detection process can be carried out through one test image, different test images can be obtained respectively aiming at the test items of each image quality index, or more test images are obtained to improve the accuracy of the test result. The acquisition of the test image can be realized through wired or wireless transmission modes, and the acquired test image can be an image shot by the imaging equipment in real time or an image shot by the stored imaging equipment in history.
Step S140: and testing the image quality index of the test image.
Specifically, after the test image of the image device is acquired, the image quality index of the test image may be tested. The number and the type of the image quality indexes can be determined according to actual detection requirements, different image detection modules are arranged aiming at different image quality indexes, and the image detection modules can respectively perform corresponding image transformation or data calculation and other processing on the test image, so that parameters of all the image quality indexes are obtained as test results to carry out image quality grading on the image equipment. In a particular embodiment, the image quality indicator includes at least one of resolution, uniformity, distortion, color, noise, and dynamic range. For the image quality indexes, corresponding test modules can be respectively arranged to perform corresponding image quality tests.
The Resolution (Resolution) module can firstly carry out Gamma linearization processing on a test image, search the center point coordinates of each Line of the bevel Edge image after processing, then fit the center point coordinate data, carry out bevel Edge inspection after fitting, relocate the bevel Edge image, sample an Edge Spread Function (ESF) by 4 times, obtain the data of a Linear Spread Function (LSF) according to the derivation of the ESF data, and carry out Hamming window processing and discrete Fourier transform on the obtained LSF data. The resolution module judges the resolution condition of the video equipment according to ESF curves and LSF curves of R, G, B and Y channels of the test image, wherein the LSF curve trend represents the resolution condition of the video equipment, the key parameters are MTF50P (an abscissa value corresponding to 50% of the maximum value of the LSF curve), MTF30P (an abscissa value corresponding to 30% of the maximum value of the LSF curve) and the like, and the numerical values of the parameters represent the resolution.
The uniformity (Shading) module can convert a test image from an RGB color space to an Lab color space, and then calculates color difference data such as delta C, delta E, delta H and the like according to a preset standard, and the uniformity module determines the brightness uniformity parameter level of the image equipment according to the color difference data among different channels in the Lab color space.
The Distortion (Distortion) module can carry out binarization processing and Gaussian filtering processing on a test image, identify point outlines in the image after processing, search central points of all the outlines, then search in a traversing mode towards the peripheral direction based on each central point, screen and sort the searched points, calculate geometric Distortion according to coordinates of four sorted corner points and middle column points, and calculate other Distortion parameters such as color Distortion parameters according to centroid error data, so that the Distortion condition and the Distortion degree of the image equipment are judged.
The Color module can calculate R, G, B, Y data of each Color channel in the image according to a Color card image shot by the image device, linearly convert the data of each Color channel into data between 0 and 1, and express parameters such as Color difference and saturation of the image device through different standard parameters, thereby judging the Color reduction capability of the image device.
The Noise and Dynamic Range (Noise & Dynamic Range) module can calculate the brightness levels of different gray-scale blocks according to gray-scale images shot by the image equipment, determine a response curve according to the brightness levels and gray-scale density values, calculate the average image of all analysis blocks, calculate the average brightness of all the gray-scale blocks and the average image, determine the standard Noise of the gray-scale images and the average image, the standard total Noise and the standard average Noise of a difference image, calculate random Noise and fixed Noise, and determine increment deviation, signal-to-Noise ratio and Dynamic Range data, thereby judging the Noise condition of the image equipment and the display capability of the image equipment to different brightness levels.
Step S160: and determining the image quality score of the image equipment based on the test result of the image quality index.
Specifically, after the image quality index is tested correspondingly, the image quality of the image device may be scored according to parameters in the test result, and a specific rule of scoring may be determined according to an actual detection requirement, for example, a total score of scoring may be 0 to 5, 0 to 10, or 0 to 100; the highest value of the score can be set as the highest value which can be reached by the parameter theory of the image index, and the highest value of the score can also be set as the highest value which is reached in the test; the method can directly perform equal-scale transformation on the parameter data of the test result according to the image index parameter corresponding to the highest value of the score to obtain the image quality score, can also set the preset image quality score corresponding to the parameter data in a certain interval, and can also determine the comprehensive image quality score by synthesizing the test results of a plurality of image quality indexes when the image quality indexes comprise a plurality of items. According to the image quality scores, the user can intuitively judge the image quality level of the tested image equipment and is convenient to compare the image quality of different image equipment.
According to the image quality detection method, various image quality indexes can be automatically tested according to the pictures shot by the image equipment, and quantitative image quality scores are output according to the test results, so that a user can be helped to judge the imaging quality condition of the image equipment more intuitively.
Fig. 2 is a schematic flow chart of determining an image quality score of a device based on a test result of an image quality indicator in an embodiment, based on the above embodiment, as shown in fig. 2, in an embodiment, the number of image quality indicators is multiple, and step S160 of the method may specifically include:
step S162: and calculating the single score of each image quality index according to the test result of each image quality index and the preset weight.
Step S164: and determining the image quality score of the image equipment based on the single score of each image quality index.
Specifically, in order to comprehensively judge the image quality level of the video device, the image quality indicators to be tested are generally many items, and may include the above-mentioned indicators of resolution, uniformity, distortion, color, noise, and dynamic range, for example. For the test result of each image quality index, the occupied weight is generally preset, and the specific distribution proportion of the preset weight can be determined according to the actual detection requirement, for example, when the image equipment is required to have relatively balanced image quality, the preset weight can be uniformly distributed to each image quality index, and when some image quality indexes of the image equipment are heavily weighted, more preset weights can be distributed to the image quality indexes. According to the total score of the image quality scores and the preset weight of each image quality index, the single total score of each image quality index can be determined, and then according to the single total score of each image quality index and the test result of the image quality index, the single score of each image quality index can be calculated.
After determining the individual scores of each image quality index, the individual scores may be added to obtain an image quality score of the video device. It is understood that the relationship between the image quality score and each image quality index and the calculation method may be determined according to actual conditions, and are not limited to the conditions described in the present embodiment.
Fig. 3 is a schematic flow chart of an image quality detection method in another embodiment, and based on the above embodiment, as shown in fig. 3, in an embodiment, the image quality detection method may further include:
step S220: and acquiring image quality scores of a plurality of image devices.
Step S240: ranking the image quality of the video device based on the image quality score.
Specifically, the image quality scores of different image devices may be compared by the image quality scores to obtain the image quality scores of a plurality of image devices that need to be compared, where the image quality scores of the plurality of image devices may be obtained by testing the image devices in real time, or may be obtained by obtaining the image quality scores of historical tests of the image devices in a database. Based on the obtained image quality scores, the image qualities of the multiple image devices can be ranked, so that the imaging qualities of different image devices can be compared conveniently. It is to be understood that, in one embodiment, the number of the image quality indicators of the video devices is multiple, and the ranking of the image qualities of the multiple video devices may include ranking of the total imaging quality scores thereof, and may further include ranking of the individual scores of the image quality indicators, so as to facilitate comparison of different image quality indicators of the video devices.
Fig. 4 is a schematic flow chart of ranking the image quality of the video device based on the image quality score in an embodiment, and based on the above embodiment, as shown in fig. 4, in an embodiment, the step S240 of the image quality detection method may specifically include:
step S242: and acquiring equipment information of a plurality of imaging equipment.
Step S244: and classifying the plurality of image devices according to the device information.
Step S246: ranking the image quality of the image devices within each classification based on the image quality scores.
Specifically, since various attributes and parameters of different image devices are different, and the reference for scoring the image quality ranking of the image devices with large differences is poor, when ranking the image quality of a plurality of image devices, the device information of each image device can be firstly obtained, the image devices are classified according to the device information, the image devices with the same or similar types are classified into the same category, then the image devices in each category are scored and ranked respectively, and the image devices in each category are scored and ranked based on the same standard, so that the image quality of the image devices can be compared transversely.
Further, in a specific embodiment, the device information includes a number of pixels and/or a field angle. The image devices may be classified according to the number of pixels and the angle of the field of view, for example, the image devices are classified into 200 ten thousand pixels or less, 200 to 800 ten thousand pixels, 800 ten thousand to 2000 ten thousand pixels, 2000 ten thousand to 5000 ten thousand pixels, and 5000 ten thousand pixels or more according to the number of pixels; the image devices are classified into 0 to 120 degrees, 120 to 150 degrees, 150 to 180 degrees, and more than 180 degrees according to the angle of the field of view. It is understood that the number and the type of the device information for classifying the image device may be determined according to actual situations, and are not limited to the situations described in this embodiment, and in other embodiments, the device information may be classified according to other device information such as a device application field, a device price, or a device volume, so as to implement image quality lateral contrast at different angles.
Fig. 5 is a schematic flowchart of an image quality detection method in another embodiment, and based on the above embodiment, as shown in fig. 5, in an embodiment, the image quality detection method may further include:
step S320: position information of the test image is acquired.
Step S340: and reproducing the test of the image quality index according to the position information.
Specifically, when the test image is obtained, the position information of the test image can be recorded by using a positioning function, and the position information specifically includes shooting coordinates, azimuth angles and the like, so that the subsequent test reproduction is realized by residing in the position information, and the image equipment or other image equipment can be arranged at the position to obtain the test image, so that the verification and comparison of the image quality test are facilitated.
Fig. 6 is a schematic structural diagram of an image quality detection apparatus according to an embodiment, and as shown in fig. 6, in an embodiment, an image quality detection apparatus 500 includes: an obtaining module 520, configured to obtain a test image of the imaging device; the test module 540 is used for testing the image quality index of the test image; a scoring module 560 for determining an image quality score of the device based on the test result of the image quality indicator; wherein the image quality indicator includes at least one of resolution, uniformity, distortion, color, noise, and dynamic range.
Specifically, in the image quality detection apparatus 500, the obtaining module 520 may obtain a test image of an imaging device, where the imaging device may specifically include a camera, a video camera, or a lens and a photosensitive element therein, the test image may be an image shot during a normal operation of the imaging device, or may be a color chart picture or a gray scale picture shot specially for detection, and the obtaining module 520 sends the obtained test image to the test module 540. The testing module 540 may perform an image quality index test on the test image, and according to the difference of the image quality index required to be detected, the testing module 540 may specifically include a resolution module, a uniformity module, a distortion module, a color module, a noise and dynamic range module, and the like, and after the test image is tested, the testing module 540 sends the test result to the scoring module 560.
The scoring module 560 may score the image quality of the image device according to the received test result, and the specific rule of the scoring may be determined according to the actual detection requirement. When the image quality indexes include multiple items, the scoring module 560 may determine a comprehensive image quality score by synthesizing the test results of the multiple image quality indexes, and the scoring module 560 may specifically calculate a single score of each image quality index according to the test result of each image quality index and a preset weight, and then determine an image quality score of the image device based on the single score of each image quality index.
The image quality detection device 500 can automatically test various image quality indexes according to pictures shot by the image equipment, and can output quantized image quality scores according to test results, so that a user can be helped to judge the imaging quality condition of the image equipment more intuitively.
Fig. 7 is a schematic structural diagram of an image quality detection apparatus in another embodiment, and based on the above embodiment, as shown in fig. 7, in an embodiment, an image quality detection apparatus 600 includes an obtaining module 620, a testing module 640, and a scoring module 660, which may be respectively the same as corresponding structures in the above embodiments, and the image quality detection apparatus 600 in this embodiment may further include: the ranking module 680 is configured to obtain image quality scores of the plurality of image devices, and rank the image quality of the image devices based on the image quality scores.
Specifically, the ranking module 680 may obtain image quality scores of a plurality of image devices, and the ranking module 680 may test the image devices in real time to obtain the image quality scores, or may obtain the image quality scores of historical tests of the image devices in a database. Ranking module 680 ranks the image quality of the multiple image devices based on the obtained image quality scores, thereby facilitating a comparison of the imaging quality of different image devices. And when the number of the image quality indexes of the image equipment is multiple, scoring and ranking the analyzed result. By comparing other test data stored in the database, the ranking module 680 may also rank the individual scores of the image quality indicators, thereby facilitating comparison of different image quality indicators of the image device.
In an embodiment, on the basis of the above embodiment, the ranking module 680 may specifically include an obtaining unit, a classifying unit, and a ranking unit; the acquisition unit is used for acquiring equipment information of a plurality of image equipment; the classification unit is used for performing classification ranking on the plurality of image devices according to the device information, and ranking the image quality of the image devices in each classification based on the image quality scores. The device information includes the number of pixels and/or the angle of the field of view, etc.
In one embodiment, on the basis of the above embodiment, the image quality detection apparatus may further include a position module and a reproduction module; the position module is used for obtaining position information of the test image, and the reproduction module is used for reproducing the test of the image quality index according to the position information.
It can be understood that the image quality detection apparatus provided by the embodiment of the present invention can execute the image quality detection method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects of the execution method. Each unit and module included in the image quality detection apparatus in the above embodiment are only divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be realized; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
In one embodiment, a computer device is provided that includes a memory, a processor, and a computer program stored on the memory and executable on the processor. The processor, when running the program, may perform the steps of: acquiring a test image of the image equipment; testing the image quality index of the test image; determining an image quality score of the device based on the test result of the image quality index; wherein the image quality indicator includes at least one of resolution, uniformity, distortion, color, noise, and dynamic range.
It is to be understood that the computer device provided by the embodiments of the present invention, the processor of which executes the program stored in the memory, is not limited to the method operations described above, and may also execute the relevant operations in the image quality detection method provided by any embodiments of the present invention.
Further, the number of processors in the computer may be one or more, and the processors and the memory may be connected by a bus or other means. The memory can mainly comprise a program storage area and a data storage area, wherein the program storage area can store an operating system and an application program required by at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the memory may further include memory located remotely from the processor, which may be connected to the device/terminal/server via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
In one embodiment, the present invention also provides a computer readable storage medium having a computer program stored thereon, which when executed by a processor, causes the processor to perform the steps of: acquiring a test image of the image equipment; testing the image quality index of the test image; determining an image quality score of the device based on the test result of the image quality index; wherein the image quality indicator includes at least one of resolution, uniformity, distortion, color, noise, and dynamic range.
It is to be understood that the computer-readable storage medium containing the computer program according to the embodiments of the present invention is not limited to the method operations described above, and may also perform related operations in the image quality detection method according to any embodiments of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods described in the embodiments of the present invention.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above embodiments only represent the preferred embodiments of the present invention and the applied technical principles, and the description thereof is specific and detailed, but not construed as limiting the scope of the invention. Numerous variations, changes and substitutions will be apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in more detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. An image quality detection method, comprising:
acquiring a test image of the image equipment;
testing the image quality index of the test image;
determining an image quality score of the image equipment based on the test result of the image quality index;
wherein the image quality indicator comprises at least one of resolution, uniformity, distortion, color, noise, and dynamic range.
2. The method of claim 1, wherein the image quality indicator is a plurality of items, and the step of determining the image quality score of the video device based on the image quality indicator comprises:
calculating the single score of each image quality index according to the test result of each image quality index and a preset weight;
and determining the image quality score of the image equipment based on the single score of each image quality index.
3. The method of claim 1, further comprising:
acquiring image quality scores of a plurality of image devices;
ranking the image quality of the video device based on the image quality score.
4. The method of claim 3, wherein ranking the image quality of the video device based on the image quality score comprises:
acquiring equipment information of the plurality of image equipment;
classifying the plurality of image devices according to the image device information;
ranking the image quality of the image devices within each classification based on the image quality scores.
5. The method of claim 4, wherein the camera information comprises a number of pixels and/or a field angle.
6. The method of claim 1, further comprising:
acquiring the position information of the test image;
and reproducing the test of the image quality index according to the position information.
7. An image quality detection apparatus, characterized by comprising:
the acquisition module is used for acquiring a test image of the image equipment;
the test module is used for testing the image quality index of the test image;
the grading module is used for determining the image quality grade of the image equipment based on the test result of the image quality index;
wherein the image quality indicator comprises at least one of resolution, uniformity, distortion, color, noise, and dynamic range.
8. The apparatus of claim 7, further comprising:
the ranking module is used for obtaining image quality scores of a plurality of image devices and ranking the image quality of the image devices based on the image quality scores.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the image quality detection method according to any one of claims 1 to 6 when executing the program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the image quality detection method according to any one of claims 1 to 6.
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