CN111243046A - Image quality detection method, device, electronic equipment and storage medium - Google Patents
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Abstract
The disclosure relates to an image quality detection method, an image quality detection device, an electronic device and a storage medium, wherein the method comprises the following steps: acquiring an image to be detected and a first image size of the image to be detected; compressing an image to be detected according to the target image quality parameters to obtain a compressed intermediate image; and calculating the size of a second image of the intermediate image, and determining that the image to be detected meets the requirement of the target image quality parameter when the size of the second image is smaller than that of the first image. According to the method, the image to be detected and the first image size of the image to be detected are obtained, the image to be detected is compressed according to the target image quality parameters, a compressed intermediate image is obtained, the second image size of the intermediate image is calculated, and when the second image size is smaller than the first image size, the image to be detected is determined to meet the requirements of the target image quality parameters, so that the quality of the image to be detected can be rapidly detected to obtain a detection result.
Description
Technical Field
The present disclosure relates to the field of image processing technologies, and in particular, to an image quality detection method and apparatus, an electronic device, and a storage medium.
Background
With the rapid development of imaging and multimedia communication technologies, image quality detection has more and more important application values in fields such as image transmission, compression, image recovery, digital watermarking and the like. The image quality is mainly expressed in two aspects of the intelligibility and the fidelity of the image. A higher intelligibility or higher fidelity of an image indicates a higher image quality and vice versa.
At present, the image quality detection indexes are more, including image size, resolution ratio and the like, and different detection methods are provided respectively, so that the method is messy, the detection methods for various indexes are complex, and contradictions may exist among detection results obtained by different detection indexes, so that the existing image quality detection method is not suitable for scenes in which various conditions need to be comprehensively considered and the detection results need to be rapidly made.
Disclosure of Invention
The present disclosure provides an image quality detection method, apparatus, electronic device, and storage medium, to at least solve a problem that the related art is not suitable for a scene where a detection result is quickly made. The technical scheme of the disclosure is as follows:
according to a first aspect of the embodiments of the present disclosure, there is provided an image quality detection method, including: acquiring an image to be detected and a first image size of the image to be detected; compressing an image to be detected according to the target image quality parameters to obtain a compressed intermediate image; and calculating the size of a second image of the intermediate image, and determining that the image to be detected meets the requirement of the target image quality parameter when the size of the second image is smaller than that of the first image.
In one embodiment, after calculating the second image size of the intermediate image, the method further includes: and when the size of the second image is larger than that of the first image, determining that the image to be detected does not meet the requirement of the target image quality parameter.
In one embodiment, compressing an image to be detected according to a target image quality parameter to obtain a compressed intermediate image includes: drawing an image to be detected to obtain a drawn first image; performing first compression processing on the first image according to the target image quality parameter to obtain a second image subjected to the first compression processing; and carrying out second compression processing on the second image to obtain a compressed intermediate image.
In one embodiment, the first compression process is performed on the first image according to the target image quality parameter, and includes: acquiring the RGB gray value of each pixel point in the first image; and mapping the RGB gray value of each pixel point according to the target image quality parameter to obtain the RGB gray value after mapping of each pixel point.
In one embodiment, performing a second compression process on the second image to obtain a compressed intermediate image includes: acquiring the RGB gray value of each pixel point in the second image; and carrying out compression coding on the RGB gray values of all the pixel points in the second image according to the spatial continuity of the RGB gray values to obtain a compression-coded intermediate image.
According to a second aspect of the embodiments of the present disclosure, an image quality detection apparatus is provided, which includes an image acquisition module to be detected, a compression module, and a quality detection module, where the image acquisition module to be detected is configured to perform acquiring an image to be detected and a first image size of the image to be detected; the compression module is configured to compress the image to be detected according to the target image quality parameter to obtain a compressed intermediate image; and the quality detection module is configured to calculate the second image size of the intermediate image, and when the second image size is smaller than the first image size, the image to be detected is determined to meet the requirement of the target image quality parameter.
In one embodiment, the quality detection module is further configured to determine that the image to be detected does not meet the requirement of the target image quality parameter when the second image size is larger than the first image size after calculating the second image size of the intermediate image.
In one embodiment, the compression module comprises: the image compression device comprises an image drawing unit, a first compression unit and a second compression unit, wherein the image drawing unit is configured to draw an image to be detected to obtain a drawn first image; the first compression unit is configured to perform first compression processing on the first image according to the target image quality parameter to obtain a second image subjected to the first compression processing; the second compression unit is configured to perform a second compression process on the second image, resulting in a compressed intermediate image.
In one embodiment, the first compression unit comprises: the image processing device comprises a first gray value obtaining subunit and a gray value mapping subunit, wherein the first gray value obtaining subunit is configured to obtain RGB gray values of each pixel point in a first image; the gray value mapping subunit is configured to perform mapping on the RGB gray values of the pixel points according to the target image quality parameters to obtain the RGB gray values after the pixel points are mapped.
In one embodiment, the second compression unit comprises: the second gray value acquisition subunit is configured to execute acquisition of an RGB gray value of each pixel point in the second image; the coding subunit is configured to perform compression coding on the RGB gray values of the pixels in the second image according to the spatial continuity of the RGB gray values, so as to obtain a compression-coded intermediate image.
According to a third aspect of the embodiments of the present disclosure, there is provided a server, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to enable the server to perform the image quality detection method described in any embodiment of the first aspect.
According to a fourth aspect of embodiments of the present disclosure, there is provided a storage medium, wherein instructions, when executed by a processor of a server, enable the server to perform the image quality detection method described in any one of the first aspect.
According to a fifth aspect of embodiments of the present disclosure, there is provided a computer program product, the program product comprising a computer program, the computer program being stored in a readable storage medium, from which the at least one processor of the apparatus reads and executes the computer program, so that the apparatus performs the image quality detection method described in any one of the first aspect.
The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects: the method comprises the steps of obtaining a to-be-detected image and a first image size of the to-be-detected image, compressing the to-be-detected image according to target image quality parameters to obtain a compressed intermediate image, further calculating a second image size of the intermediate image, and determining that the to-be-detected image meets the requirements of the target image quality parameters when the second image size is smaller than the first image size, so that a detection result is rapidly made on the quality of the to-be-detected image.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure and are not to be construed as limiting the disclosure.
Fig. 1 is a diagram illustrating an application environment of an image quality detection method according to an exemplary embodiment.
Fig. 2 is a flow chart illustrating an image quality detection method according to an exemplary embodiment.
Fig. 3 is a flowchart illustrating an image quality detecting method according to another exemplary embodiment.
FIG. 4 is a flowchart illustrating steps for compressing an image to be detected according to an exemplary embodiment.
Fig. 5 is a block diagram illustrating an image quality detection apparatus according to an exemplary embodiment.
Fig. 6 is an internal block diagram of a server according to an example embodiment.
Detailed Description
In order to make the technical solutions of the present disclosure better understood by those of ordinary skill in the art, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
The image quality detection method provided by the present disclosure can be applied to the application environment shown in fig. 1. In this embodiment, the terminal 110 may be various devices having an image capturing or image storing function, such as but not limited to various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 120 may be implemented by an independent server or a server cluster formed by a plurality of servers. Specifically, the terminal 110 may be configured to acquire an image to be detected or store the image to be detected, and upload the image to be detected to the server 120 through a network. The server 120 obtains the image to be detected and the first image size of the image to be detected, compresses the image to be detected according to the target image quality parameter to obtain a compressed intermediate image, further calculates the second image size of the intermediate image, determines that the image to be detected meets the requirement of the target image quality parameter when the second image size is smaller than the first image size, and otherwise determines that the image to be detected does not meet the requirement of the target image quality parameter, thereby realizing the purpose of rapidly making a detection result on the quality of the image to be detected.
Fig. 2 is a flowchart illustrating an image quality detection method according to an exemplary embodiment, which is illustrated in fig. 2, and includes the following steps, taking the method as an example for being applied to the server in fig. 1.
In step S210, an image to be detected and a first image size of the image to be detected are acquired.
The image to be detected refers to an image to be subjected to quality detection uploaded by a front end, the image size refers to the digital size of an image file, and kilobytes (K), Megabytes (MB) or Gigabytes (GB) are used as measurement units. In this embodiment, for convenience of distinguishing, the image size of the image to be detected is referred to as a first image size. Due to the influence of the shooting environment and the shooting tool in the natural scene, the image to be detected may have different resolutions, sizes, and the like, and if the image quality is not controlled, the uploaded image quality may be uneven. Therefore, in this embodiment, after the terminal uploads the image to the server, the server needs to detect the quality of the uploaded image, specifically, the server first obtains the uploaded image to be detected, and then obtains the corresponding first image size according to the file of the image to be detected.
In step S220, the image to be detected is compressed according to the target image quality parameter, so as to obtain a compressed intermediate image.
The image quality refers to subjective evaluation of a person on visual perception of an image, and can be divided into image fidelity and image intelligibility. Image fidelity describes the degree of deviation between the processed image and the original image, while image intelligibility represents the degree to which a person or machine can extract information about features from the image. The image quality of each image can be evaluated by 0-1 (or converted into a quality percentage), and the target image quality parameter in this embodiment refers to the image quality that is expected to be achieved for the uploaded image, and can be specifically set according to the actual application scenario. Compression refers to the removal of excess data from an image, and from a mathematical point of view, this process actually transforms a two-dimensional pixel array into a statistically uncorrelated data set, i.e., the original pixel matrix is represented with fewer bits, lossy or lossless, and may also be referred to as image coding. In this embodiment, an image to be detected is compressed according to a set target image quality parameter, so as to obtain a compressed intermediate image, and then whether the image to be detected meets the requirement of the target image quality parameter is determined through the following steps.
In step S230, a second image size of the intermediate image is calculated.
Wherein the second image size refers to a digital size of an image file of the intermediate image. Since the size of an image file is generally proportional to the pixel size of the image, the more pixels that are included in an image, the more detail that can be displayed at a given print size, but the more disk storage space that is required. However, for images with the same pixel size, the sizes of the obtained images are different after the images are compressed according to different image quality requirements, and generally, the size of the compressed image is larger when the image quality requirement is higher than that of the compressed image when the image quality requirement is lower.
In step S240, when the second image size is smaller than the first image size, it is determined that the image to be detected meets the requirement of the target image quality parameter.
In this embodiment, when the second image size of the compressed intermediate image is smaller than the first image size of the image to be detected, it indicates that the image quality of the image to be detected is better than that of the intermediate image, and the intermediate image is obtained by compressing the intermediate image based on the target image quality parameter, that is, the image quality of the intermediate image meets the requirement of the target image quality parameter, so that it can be determined that the image to be detected also meets the requirement of the target image quality parameter.
According to the image quality detection method, the image to be detected and the first image size of the image to be detected are obtained, the image to be detected is compressed according to the target image quality parameters, a compressed intermediate image is obtained, the second image size of the intermediate image is further calculated, and when the second image size is smaller than the first image size, the image to be detected is determined to meet the requirements of the target image quality parameters, so that the quality of the image to be detected can be rapidly detected.
In an exemplary embodiment, as shown in fig. 3, after calculating the second image size of the intermediate image, the method further includes the following steps:
in step S250, when the second image size is larger than the first image size, it is determined that the image to be detected does not satisfy the requirement of the target image quality parameter.
Based on the above knowledge of the image size and the image quality, in this embodiment, when the second image size of the compressed intermediate image is larger than the first image size of the image to be detected, it indicates that the image quality of the intermediate image is better than that of the image to be detected, and the intermediate image is obtained by compressing the intermediate image based on the target image quality parameter, that is, the image quality of the intermediate image meets the requirement of the target image quality parameter, and the image quality of the image to be detected does not reach the image quality of the intermediate image, so that it can be determined that the image to be detected does not meet the requirement of the target image quality parameter.
According to the image quality detection method, the image to be detected and the first image size of the image to be detected are obtained, the image to be detected is compressed according to the target image quality parameter, a compressed intermediate image is obtained, the second image size of the intermediate image is further calculated, and the image quality of the image to be detected can be rapidly judged according to the second image size of the intermediate image and the first image size of the image to be detected, namely whether the image to be detected meets the requirement of the target image quality parameter is rapidly judged, so that subsequent operation is facilitated.
In an exemplary embodiment, as shown in fig. 4, in step S220, compressing the image to be detected according to the target image quality parameter may specifically be implemented by:
in step S410, an image to be detected is drawn, and a drawn first image is obtained.
Because the size of the image obtained by compressing the image with the same pixel size according to different image quality requirements is different. For example, for a certain image a, assuming that the image quality is 1, it is compressed into a1 with image quality of 90% and a2 with image quality of 80%, respectively, and the image size of a1 is larger than that of a2, that is, the compressed image size is larger when the requirement of image quality is high than that of the image size when the requirement of image quality is low. Therefore, in this embodiment, the image to be detected is redrawn based on the image to be detected and the size of the first image, so as to obtain a drawn first image.
Specifically, in this embodiment, when the server obtains the image to be detected uploaded by the terminal, an online flat surface design software (canvas) may be used to create a canvas node, and the image to be detected is drawn through the canvas node, that is, the codes of the pixels in the image to be detected are restored, so as to obtain a pixel matrix describing the codes of the pixels, that is, the first image after drawing is obtained.
In step S420, a first compression process is performed on the first image according to the target image quality parameter, so as to obtain a second image after the first compression process is performed.
Wherein the first compression process is a lossy compression process. In this embodiment, the RGB gray value of each pixel point is obtained by obtaining the code of each pixel point in the first image, and then the RGB gray value of each pixel point is mapped according to the target image quality parameter, so as to obtain the RGB gray value after mapping of each pixel point, and thus obtain the second image after the first compression processing.
Specifically, the RGB gray scale value of one pixel can be represented as (R, G, B), and the ranges of R, G, B are 0-255(256 values), respectively, and each pixel needs to record the RGB gray scale value with 8 bits × 3(3 bytes). For example, a picture with a resolution of 100 × 100 has 10000 pixels, and if the RGB grayscale values of each pixel are different, 10000 × 3 bytes to 30000 bytes are required to record the color data, that is, the size of the picture is 30000 bytes. This is not acceptable and therefore the picture size can usually be reduced by compressing it, but for some applications the uploaded image is also required to have some sharpness, whereas in Canva it can be evaluated by image quality.
Therefore, in this embodiment, the RGB grayscale values of each pixel point can be mapped by setting the target image quality parameter in canta. For example, if the set target image quality parameter a is 90%, 256 values of R, G, and B, which take values of 0-255, need to be divided into 10 (1/(100% -a)) segments, for example, 0-24 is the 1 st segment, 25-49 is the 2 nd segment, and …, 230-. And mapping the RGB gray value of each pixel point in the first image according to the segments, namely, taking the value which accords with the segment interval as the same value, for example, taking the value which falls into the interval of 0-24 as 0, taking the value which falls into the interval of 25-49 as 25, and so on to obtain the RGB gray value after mapping of each pixel point, namely obtaining the second image after the first compression processing.
In step S430, a second compression process is performed on the second image, and a compressed intermediate image is obtained.
Wherein the second compression process is a lossless compression process. In this embodiment, the RGB gray values of each pixel point in the second image are obtained, and then the RGB gray values of each pixel point in the second image are compressed and encoded according to the spatial continuity of the RGB gray values, so as to obtain the intermediate image after compression and encoding.
Specifically, after the step S420 is completed, the number of pixels of the RGB gray scale values that are continuously repeated in the second image is increased, that is, there is a continuous string of data, and the color values (i.e., the RGB gray scale values) described by the data are the same. For example, in the second image after the above processing, it is assumed that 20 consecutive pixels are white, and if the spatial continuity is not considered, the white needs 20 × 3 to 60 bytes to record the RGB grayscale value. However, if the spatial continuity is considered, the RGB gray value of the repeated pixel point may be recorded first (3 bytes are needed), and then how many times the pixel value is repeated (20 times, 1 byte is recordable) is recorded, so the size to be recorded is reduced from 60 bytes to 4 bytes, thereby implementing compression encoding on the RGB gray value of each pixel point in the second image, and obtaining a compressed intermediate image.
In the embodiment, the image to be detected is drawn through canvas to obtain the drawn first image, the first image is subjected to first compression processing according to the target image quality parameter to obtain the second image subjected to the first compression processing, the second image is subjected to second compression processing to obtain the compressed intermediate image, and based on the intermediate image, the image quality of the image to be detected can be rapidly evaluated, and the implementation method is simple and reliable and has strong popularization significance.
In an exemplary embodiment, the image quality detection method of the present disclosure is further described according to a specific application scenario, for example, when performing image quality detection on an uploaded avatar, because there is a certain requirement on the definition of the avatar, a higher target image quality parameter may be set, for example, the quality of the avatar uploaded by a user is required to be not lower than 80%. When the server acquires the head portrait uploaded by the terminal, the first image size of the head portrait is acquired, the uploaded head portrait is compressed by adopting the method shown in fig. 4 according to the set image quality parameter of 80%, a compressed intermediate image is obtained, the second image size of the intermediate image is calculated, when the second image size of the intermediate image is smaller than the first image size of the uploaded head portrait, the uploaded head portrait is determined to meet the requirement of the target image quality parameter, uploading is allowed, otherwise, the uploaded head portrait is determined not to meet the requirement of the target image quality parameter, and uploading of the clearer head portrait is prompted to the user.
In the operation activities of the merchant, the requirement on the picture quality is not so high, but the picture quality is required to be as small as possible under the condition that the viewing is not influenced, so that the uploaded picture quality can be set to be not higher than 70% (here, only one assumed value is used, and other values can be specifically set). When the server acquires a picture uploaded by the terminal, acquiring a first image size of the picture, further compressing the uploaded picture according to a set image quality parameter of 70% by adopting the method shown in fig. 4 to obtain a compressed intermediate image, calculating a second image size of the intermediate image, and when the second image size of the intermediate image is smaller than the first image size of the uploaded picture, determining that the uploaded picture is higher than a target image quality parameter (70%), thereby prompting a user to upload the compressed picture, or directly compressing the uploaded picture by canvas or other technologies (such as mozjpeg (jpg compression software) or optpng (png compression software)) to enable the uploaded picture to meet the requirement of the target image quality parameter.
It should be understood that although the various steps in the flow charts of fig. 1-4 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 1-4 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps or stages.
Fig. 5 is a block diagram illustrating an image quality detection apparatus according to an exemplary embodiment. Referring to fig. 5, the apparatus includes an image acquisition module 520 to be detected, a compression module 540, and a quality detection module 560.
An image to be detected acquisition module 520 configured to perform acquiring an image to be detected and a first image size of the image to be detected.
And the compressing module 540 is configured to compress the image to be detected according to the target image quality parameter, so as to obtain a compressed intermediate image.
And a quality detection module 560 configured to perform calculating a second image size of the intermediate image, and determine that the image to be detected meets the requirement of the target image quality parameter when the second image size is smaller than the first image size.
In an exemplary embodiment, the quality detection module 560, after calculating the second image size of the intermediate image, is further configured to perform determining that the image to be detected does not satisfy the requirement of the target image quality parameter when the second image size is larger than the first image size.
In an exemplary embodiment, the compression module 540 includes: the image compression device comprises an image drawing unit, a first compression unit and a second compression unit, wherein the image drawing unit is configured to draw an image to be detected to obtain a drawn first image; the first compression unit is configured to perform first compression processing on the first image according to the target image quality parameter to obtain a second image subjected to the first compression processing; the second compression unit is configured to perform a second compression process on the second image, resulting in a compressed intermediate image.
In an exemplary embodiment, the first compression unit includes: the image processing device comprises a first gray value obtaining subunit and a gray value mapping subunit, wherein the first gray value obtaining subunit is configured to obtain RGB gray values of each pixel point in a first image; the gray value mapping subunit is configured to perform mapping on the RGB gray values of the pixel points according to the target image quality parameters to obtain the RGB gray values after the pixel points are mapped.
In an exemplary embodiment, the second compression unit includes: the second gray value acquisition subunit is configured to execute acquisition of an RGB gray value of each pixel point in the second image; the coding subunit is configured to perform compression coding on the RGB gray values of the pixels in the second image according to the spatial continuity of the RGB gray values, so as to obtain a compressed intermediate image.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
Fig. 6 is a block diagram illustrating an apparatus for image quality detection S00 according to an exemplary embodiment. For example, the device S00 may be a server. Referring to FIG. 6, device S00 includes a processing component S20 that further includes one or more processors and memory resources represented by memory S22 for storing instructions, e.g., applications, that are executable by processing component S20. The application program stored in the memory S22 may include one or more modules each corresponding to a set of instructions. Further, the processing component S20 is configured to execute instructions to perform the method of image quality detection described above.
The device S00 may also include a power supply component S24 configured to perform power management of the device S00, a wired or wireless network interface S26 configured to connect the device S00 to a network, and an input-output (I/O) interface S28. The device S00 may operate based on an operating system stored in the memory S22, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, or the like.
In an exemplary embodiment, there is also provided a storage medium comprising instructions, such as the memory S22 comprising instructions, executable by the processor of the device S00 to perform the above method. The storage medium may be a non-transitory computer readable storage medium, which may be, for example, a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. An image quality detection method, comprising:
acquiring an image to be detected and a first image size of the image to be detected;
compressing the image to be detected according to the quality parameters of the target image to obtain a compressed intermediate image;
and calculating the size of a second image of the intermediate image, and determining that the image to be detected meets the requirement of the target image quality parameter when the size of the second image is smaller than that of the first image.
2. The image quality detection method according to claim 1, further comprising, after the calculating the second image size of the intermediate image:
and when the size of the second image is larger than that of the first image, determining that the image to be detected does not meet the requirement of the target image quality parameter.
3. The image quality detection method according to claim 1 or 2, wherein compressing the image to be detected according to the target image quality parameter to obtain a compressed intermediate image comprises:
drawing the image to be detected to obtain a drawn first image;
performing first compression processing on the first image according to the target image quality parameter to obtain a second image subjected to the first compression processing;
and carrying out second compression processing on the second image to obtain the compressed intermediate image.
4. The image quality detection method according to claim 3, wherein the performing of the first compression process on the first image according to the target image quality parameter includes:
acquiring the RGB gray value of each pixel point in the first image;
and mapping the RGB gray value of each pixel point according to the target image quality parameter to obtain the RGB gray value after mapping of each pixel point.
5. The image quality detection method according to claim 3, wherein the performing of the second compression processing on the second image to obtain the compressed intermediate image comprises:
acquiring the RGB gray value of each pixel point in the second image;
and carrying out compression coding on the RGB gray values of all the pixel points in the second image according to the spatial continuity of the RGB gray values to obtain the compression-coded intermediate image.
6. An image quality detection apparatus, characterized by comprising:
the image acquisition module to be detected is configured to acquire an image to be detected and a first image size of the image to be detected;
the compression module is configured to compress the image to be detected according to the target image quality parameters to obtain a compressed intermediate image;
and the quality detection module is configured to calculate a second image size of the intermediate image, and when the second image size is smaller than the first image size, the image to be detected is determined to meet the requirement of the target image quality parameter.
7. The image quality detection apparatus according to claim 6, wherein the quality detection module, after calculating the second image size of the intermediate image, is configured to perform determining that the image to be detected does not satisfy the requirement of the target image quality parameter when the second image size is larger than the first image size.
8. The image quality detection apparatus according to claim 6 or 7, wherein the compression module comprises:
the image drawing unit is configured to draw the image to be detected to obtain a drawn first image;
the first compression unit is configured to perform first compression processing on the first image according to a target image quality parameter to obtain a second image subjected to the first compression processing;
and the second compression unit is configured to execute second compression processing on the second image to obtain the compressed intermediate image.
9. A server, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the image quality detection method of any one of claims 1 to 5.
10. A storage medium in which instructions, when executed by a processor of a server, enable the server to perform the image quality detection method according to any one of claims 1 to 5.
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