CN117478888A - Image compression method, device, terminal equipment and readable storage medium - Google Patents
Image compression method, device, terminal equipment and readable storage medium Download PDFInfo
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- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
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- H04N19/30—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using hierarchical techniques, e.g. scalability
- H04N19/36—Scalability techniques involving formatting the layers as a function of picture distortion after decoding, e.g. signal-to-noise [SNR] scalability
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- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
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Abstract
The invention provides an image compression method, an image compression device, terminal equipment and a readable storage medium, and relates to the field of image processing. The method comprises the following steps: compressing a plurality of first images provided by target equipment at different compression ratios by adopting a plurality of compression algorithms to obtain a plurality of second images of each compression algorithm corresponding to the first images at different compression ratios; calculating image compression effect evaluation values corresponding to each compression algorithm under different compression ratios for a plurality of second images; and determining an optimal compression algorithm and an optimal compression ratio according to the image compression effect evaluation values corresponding to each compression algorithm under different compression ratios. The scheme of the invention solves the problem that the accuracy of image recognition can not be ensured while the response time and the storage pressure of an image recognition system are ensured in the compression process of image recognition in the prior art.
Description
Technical Field
The present invention relates to the field of image processing technologies, and in particular, to an image compression method, an image compression device, a terminal device, and a readable storage medium.
Background
At present, image recognition application software generally takes received original image data directly as an input information source to perform image recognition, but an image provided by a user has offset, and the image identification effect is directly affected by the offset condition of the image; meanwhile, the image recognition process is generally carried out by adopting a single JPEG image compression processing technology. Because of the adoption of the low compression ratio, the response time and the storage pressure of the image recognition system can be increased, and the transmission speed is reduced; with a high compression ratio, although the response time and storage pressure of the image recognition system are reduced, the accuracy of image recognition is reduced. Therefore, in the compression process of image recognition, the accuracy of image recognition cannot be ensured while the response time and the storage pressure of the image recognition system are ensured.
Disclosure of Invention
The invention aims to provide an image compression method, an image compression device, terminal equipment and a readable storage medium, which are used for solving the problem that the accuracy of image recognition cannot be ensured while the response time and storage pressure of an image recognition system are ensured in the compression process of image recognition in the prior art.
To achieve the above object, an embodiment of the present invention provides an image compression method, including:
compressing a plurality of first images provided by target equipment at different compression ratios by adopting a plurality of compression algorithms to obtain a plurality of second images of each compression algorithm corresponding to the first images at different compression ratios;
calculating image compression effect evaluation values corresponding to each compression algorithm under different compression ratios for a plurality of second images;
and determining an optimal compression algorithm and an optimal compression ratio according to the image compression effect evaluation values corresponding to each compression algorithm under different compression ratios.
Further, the calculating, for the plurality of second images, the image compression effect evaluation value corresponding to each compression algorithm under different compression ratios includes:
performing image recognition on each second image, and determining the image recognition accuracy of the second image;
acquiring an image quality evaluation result of the second image;
and determining an image compression effect evaluation value corresponding to each compression algorithm according to the resource size of the first image, the image recognition accuracy of the second image, the resource size of the second image and the image quality evaluation result of the second image.
Further, the determining an optimal compression algorithm and an optimal compression ratio according to the image compression effect evaluation value corresponding to each compression algorithm under different compression ratios includes:
the compression algorithm corresponding to the maximum value of the image compression effect evaluation value is an optimal compression algorithm;
compressing a plurality of groups of first images provided by the target equipment by adopting different high compression ratios by the optimal compression algorithm to obtain a plurality of groups of image compression effect evaluation values of third images corresponding to the first images;
performing image recognition on each third image, and determining the image recognition accuracy of the third images;
and determining the optimal compression ratio according to the image compression effect evaluation values of the third images and the image recognition accuracy of the third images.
Further, the method further comprises:
and saving the equipment identifier of the target equipment, the image characteristic identifier of the first image, the optimal compression ratio and the optimal compression algorithm as a data set.
Further, the method further comprises:
receiving an image compression request of a first device, wherein the image compression request comprises an image to be compressed;
acquiring a first characteristic identifier of the image to be compressed;
determining the data set matching a first device identification of the first device and the first characteristic identification; wherein the determined device identity in the data set matches the first device identity and the determined image feature identity in the data set matches the first feature identity;
and carrying out compression processing on the image to be compressed according to the determined optimal compression ratio and the determined optimal compression algorithm in the data set.
Further, before compressing the plurality of first images provided by the target device with different compression ratios, the method includes:
correcting the first image by adopting a Hough transform method;
and carrying out image edge detection processing on the corrected first image to obtain the processed first image.
Further, the correcting the first image by using the hough transform method includes:
determining the coordinates of the center of a preset area on the first image by adopting a Hough transformation circular detection method;
determining the slope of a target graph in a circular area on the first image by adopting a Hough transformation linear detection method;
and carrying out angle correction and position correction on the first image according to the coordinates of the center and the slope.
The embodiment of the invention also provides an image compression device, which comprises:
the compression module is used for compressing the plurality of first images provided by the target equipment at different compression ratios by adopting a plurality of compression algorithms to obtain a second image of each compression algorithm corresponding to the plurality of first images at different compression ratios;
the calculating module is used for calculating image compression effect evaluation values corresponding to each compression algorithm under different compression ratios for a plurality of second images;
and the determining module is used for determining an optimal compression algorithm and an optimal compression ratio according to the image compression effect evaluation value corresponding to each compression algorithm under different compression ratios.
To achieve the above object, an embodiment of the present invention provides a terminal device including a transceiver, a processor, a memory, and a program or instructions stored on the memory and executable on the processor; the processor, when executing the program or instructions, implements the image compression method as described above.
To achieve the above object, an embodiment of the present invention provides a readable storage medium having stored thereon a program or instructions which, when executed by a processor, implement the steps in the image compression method as described above.
The technical scheme of the invention has the following beneficial effects:
according to the image compression method, a plurality of compression algorithms are adopted to compress a plurality of first images provided by target equipment at different compression ratios, so that a second image of each compression algorithm corresponding to the plurality of first images at different compression ratios can be obtained; by evaluating the compression effect of the second image, an optimal compression ratio and an optimal compression method for compressing the first image can be determined. According to the image compression method, the optimal compression ratio and the optimal compression algorithm for compressing the first image can be determined by carrying out compression effect evaluation on different compression ratios and different compression algorithms, so that the response time and the storage pressure of an image recognition system are ensured, and the accuracy of image recognition is ensured.
Drawings
FIG. 1 is a flow chart of an image compression method according to an embodiment of the invention;
fig. 2 is a schematic structural diagram of an image compression apparatus according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a terminal device according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a terminal device according to another embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages to be solved more apparent, the following detailed description will be given with reference to the accompanying drawings and specific embodiments.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
In various embodiments of the present invention, it should be understood that the sequence numbers of the following processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
In addition, the terms "system" and "network" are often used interchangeably herein.
In the examples provided herein, it should be understood that "B corresponding to a" means that B is associated with a from which B may be determined. It should also be understood that determining B from a does not mean determining B from a alone, but may also determine B from a and/or other information.
As shown in fig. 1, an image compression method according to an embodiment of the present invention includes the following steps:
step 101, compressing a plurality of first images provided by target equipment at different compression ratios by adopting a plurality of compression algorithms to obtain a plurality of second images of each compression algorithm corresponding to the first images at different compression ratios;
102, calculating image compression effect evaluation values corresponding to each compression algorithm under different compression ratios for a plurality of second images;
and step 103, determining an optimal compression algorithm and an optimal compression ratio according to the image compression effect evaluation values corresponding to each compression algorithm under different compression ratios.
Optionally, the plurality of compression algorithms includes:
JPEG2000 algorithm and JPEG algorithm.
Optionally, the different compression ratios include:
and setting a plurality of compression ratios at preset step sizes from the first compression ratio to the second compression ratio.
In the embodiment of the invention, the first compression ratio is 1.5, the second compression ratio is 6, and the preset step length is between 0.2 and 0.5.
Under the application scene of the journey card identification, the quality difference of the source image caused by the difference of the user equipment, if the single high compression ratio is adopted for image compression, the accuracy of the image identification can be obviously reduced, and the user friendliness is affected; if a single low compression ratio is adopted, the system response time is obviously increased, and the transmission speed and the storage space occupation rate are reduced.
When the requirement on the size of the picture is not high, the JPEG algorithm is selected for compressing the image, so that the overall performance is relatively good; however, in application scenarios (such as mobile devices) with limited storage space, limited network transmission, traffic saving requirement, and limited uploading and downloading speeds, the JPEG2000 algorithm has comprehensive advantages in compressing stored pictures. As the image compression ratio increases, relative to the JPEG algorithm: when the compression ratio exceeds 1.5, the PSNR value of the JPEG2000 algorithm does not increase sharply; when the compression ratio exceeds 6, the fluctuation range of the MSSIM value and the image information entropy IIE value is smaller.
According to the image compression method, a plurality of compression algorithms are adopted to compress a plurality of first images provided by target equipment at different compression ratios, so that a second image of each compression algorithm corresponding to the plurality of first images at different compression ratios can be obtained; by evaluating the compression effect of the second image, an optimal compression ratio and an optimal compression method for compressing the first image can be determined. According to the image compression method, the optimal compression ratio and the optimal compression algorithm for compressing the first image can be determined by carrying out compression effect evaluation on different compression ratios and different compression algorithms, so that the response time and the storage pressure of an image recognition system are ensured, and the accuracy of image recognition is ensured.
Optionally, the calculating, for the plurality of second images, an image compression effect evaluation value corresponding to each compression algorithm at different compression ratios includes:
performing image recognition on each second image, and determining the image recognition accuracy of the second image;
acquiring an image quality evaluation result of the second image;
and determining an image compression effect evaluation value corresponding to each compression algorithm according to the resource size of the first image, the image recognition accuracy of the second image, the resource size of the second image and the image quality evaluation result of the second image.
Optionally, the performing image recognition on each of the second images, determining the accuracy of image recognition of the second images includes:
performing image recognition on a plurality of second images, and calculating an average value of the image recognition accuracy corresponding to each compression method;
and determining the image recognition accuracy of the second image corresponding to each compression method according to the average value of the image recognition accuracy under each compression method.
Optionally, the calculating means calculates an average value of the image recognition accuracy corresponding to each compression method by:
；/>；
wherein,the average value of the image recognition accuracy rate compressed by adopting a first compression algorithm is obtained; />The average value of the image recognition accuracy rate compressed by adopting a second compression algorithm; m is the number of the second images compressed by the first compression algorithm at different compression ratios; n is the number of said second images compressed at different compression ratios using a second compression algorithm; />For the ith acquisitionThe image recognition accuracy of compression is carried out by using a first compression algorithm; />Image recognition accuracy for compression for the j Zhang Caiyong second compression algorithm.
Optionally, the determining the image compression effect evaluation value corresponding to each compression algorithm according to the resource size of the first image, the image recognition accuracy of the second image, the resource size of the second image and the image quality evaluation result of the second image includes:
the image compression effect evaluation value is calculated by the following formula:
；
wherein,pis of the algorithm type;is the firstpThe image recognition accuracy of the compression algorithm is obtained; />An image quality evaluation result of the second image; />A resource size for the first image; />Is the resource size of the second image.
It should be noted that, the resource size of the first image is the size of the memory occupied by the first image; the resource size of the second image is the size of the memory occupied by the second image.
According to the image compression method, through the resource size of the first image, the image recognition accuracy of the second image, the resource size of the second image and the image quality evaluation result of the second image, the image compression effect evaluation value corresponding to each compression algorithm is determined, compression effect evaluation including the image recognition accuracy and the image quality aspects can be performed on each compression algorithm, and therefore the optimal compression algorithm can be determined.
Optionally, the acquiring the image quality evaluation result of the second image includes:
acquiring a peak signal-to-noise ratio PSNR, an average structural similarity MSSIM and an image information entropy IIE of the second image;
and determining an image quality evaluation result of the second image according to the peak signal-to-noise ratio PSNR, the average structural similarity MSSIM and the image information entropy IIE.
Optionally, the determining the image quality evaluation result of the second image according to the peak signal-to-noise ratio PSNR, the average structural similarity MSSIM, and the image information entropy IIE includes:
,l＞0，p=1,2；
where p is the type of compression algorithm and q is the number of first images.
According to the image compression method, the comprehensive image quality of the second image can be determined through the peak signal-to-noise ratio PSNR, the average structural similarity MSSIM and the image information entropy IIE.
Optionally, the determining an optimal compression algorithm and an optimal compression ratio according to the image compression effect evaluation value corresponding to each compression algorithm under different compression ratios includes:
the compression algorithm corresponding to the maximum value of the image compression effect evaluation value is an optimal compression algorithm;
compressing a plurality of groups of first images provided by the target equipment by adopting different high compression ratios by the optimal compression algorithm to obtain a plurality of groups of image compression effect evaluation values of third images corresponding to the first images;
performing image recognition on each third image, and determining the image recognition accuracy of the third images;
and determining the optimal compression ratio according to the image compression effect evaluation values of the third images and the image recognition accuracy of the third images.
Optionally, the determining the optimal compression ratio according to the multiple sets of image compression effect evaluation values of the third image and the image recognition accuracy of the third image includes:
calculating the average value of the image compression effect evaluation values of a plurality of groups of third images;
and determining the optimal compression ratio according to the product of the mean value and the image recognition accuracy.
According to the image compression method provided by the embodiment of the invention, the transmission speed and the storage space occupancy rate can be improved while the image identification accuracy is ensured by determining the optimal compression ratio and the optimal compression method of the image provided by the target equipment.
Optionally, the method further comprises:
and saving the equipment identifier of the target equipment, the image characteristic identifier of the first image, the optimal compression ratio and the optimal compression algorithm as a data set.
According to the image compression method, the device identification of the target device, the image characteristic identification of the first image, the optimal compression ratio and the optimal compression algorithm are stored in the form of the data set, so that a database can be built, and the processing efficiency of image compression is improved for subsequent image recognition.
Optionally, the method further comprises:
receiving an image compression request of a first device, wherein the image compression request comprises an image to be compressed;
acquiring a first characteristic identifier of the image to be compressed;
determining the data set matching a first device identification of the first device and the first characteristic identification; wherein the determined device identity in the data set matches the first device identity and the determined image feature identity in the data set matches the first feature identity;
and carrying out compression processing on the image to be compressed according to the determined optimal compression ratio and the determined optimal compression algorithm in the data set.
In the embodiment of the invention, the database is constructed aiming at different equipment and different image types, and the optimal compression ratio and the optimal compression algorithm of different equipment identifications and the characteristic identifications of the images are stored, so that the compression ratio and the compression algorithm which are required to be adopted can be quickly confirmed when different images of different equipment are received, the image identification accuracy is ensured, and the transmission speed and the storage space occupation rate are improved.
Optionally, before compressing the plurality of first images provided by the target device with different compression ratios by using a plurality of compression algorithms, the method includes:
correcting the first image by adopting a Hough transform method;
and carrying out image edge detection processing on the corrected first image to obtain the processed first image.
It should be noted that the targeted devices come from a variety of different categories, and that the acquired images have quality differences and angle differences, typically because the images are not properly angled resulting in image recognition errors or failures.
According to the image compression method, the angle and the position offset of the first image can be corrected through the Hough transform method, so that the efficiency of identifying and compressing the image is improved.
Optionally, the correcting the first image by using a hough transform method includes:
determining the coordinates of the center of a preset area on the first image by adopting a Hough transformation circular detection method;
determining the slope of a target graph in a circular area on the first image by adopting a Hough transformation linear detection method;
and carrying out angle correction and position correction on the first image according to the coordinates of the center and the slope.
According to the image compression method, the angle and the position offset of the first image can be corrected through the Hough transform method, so that the efficiency of identifying and compressing the image is improved.
As shown in fig. 2, an embodiment of the present invention further provides an image compression apparatus 200, including:
the compression module 201 is configured to compress the plurality of first images provided by the target device by using a plurality of compression algorithms at different compression ratios, so as to obtain a second image of each compression algorithm corresponding to the plurality of first images at different compression ratios;
a calculating module 202, configured to calculate, for a plurality of the second images, image compression effect evaluation values corresponding to each compression algorithm under different compression ratios;
a determining module 203, configured to determine an optimal compression algorithm and an optimal compression ratio according to the image compression effect evaluation values corresponding to each compression algorithm under different compression ratios.
According to the image compression device, a plurality of compression algorithms are adopted to compress a plurality of first images provided by target equipment at different compression ratios, so that a second image of each compression algorithm corresponding to the plurality of first images at different compression ratios can be obtained; by evaluating the compression effect of the second image, an optimal compression ratio and an optimal compression method for compressing the first image can be determined. According to the image compression method, the optimal compression ratio and the optimal compression algorithm for compressing the first image can be determined by carrying out compression effect evaluation on different compression ratios and different compression algorithms, so that the response time and the storage pressure of an image recognition system are ensured, and the accuracy of image recognition is ensured.
As shown in fig. 3, a terminal device 300 according to an embodiment of the present invention includes a processor 310, wherein,
the processor is used for compressing the plurality of first images provided by the target equipment by adopting a plurality of compression algorithms at different compression ratios to obtain a second image of each compression algorithm corresponding to the plurality of first images at different compression ratios;
calculating image compression effect evaluation values corresponding to each compression algorithm under different compression ratios for a plurality of second images;
and determining an optimal compression algorithm and an optimal compression ratio according to the image compression effect evaluation values corresponding to each compression algorithm under different compression ratios.
A terminal device according to another embodiment of the present invention, as shown in fig. 4, includes a transceiver 410, a processor 400, a memory 420, and a program or instructions stored on the memory 420 and executable on the processor 400; the processor 400, when executing the program or instructions, implements the above-described application to image compression methods.
The transceiver 410 is configured to receive and transmit data under the control of the processor 400.
Wherein in fig. 4, a bus architecture may comprise any number of interconnected buses and bridges, and in particular one or more processors represented by processor 400 and various circuits of memory represented by memory 420, linked together. The bus architecture may also link together various other circuits such as peripheral devices, voltage regulators, power management circuits, etc., which are well known in the art and, therefore, will not be described further herein. The bus interface provides an interface. Transceiver 410 may be a number of elements, i.e., including a transmitter and a receiver, providing a means for communicating with various other apparatus over a transmission medium. The user interface 430 may also be an interface capable of interfacing with an inscribed desired device for a different user device, including but not limited to a keypad, display, speaker, microphone, joystick, etc.
The processor 400 is responsible for managing the bus architecture and general processing, and the memory 420 may store data used by the processor 400 in performing operations.
The readable storage medium of the embodiment of the present invention stores a program or an instruction, which when executed by a processor, implements the steps in the image compression method described above, and can achieve the same technical effects, and is not described herein again for avoiding repetition.
Wherein the processor is a processor in the terminal device described in the above embodiment. The readable storage medium includes a computer readable storage medium such as a Read-Only Memory (ROM), a random access Memory (Random Access Memory RAM), a magnetic disk or an optical disk.
It is further noted that the terminals described in this specification include, but are not limited to, smartphones, tablets, etc., and that many of the functional components described are referred to as modules in order to more particularly emphasize their implementation independence.
In an embodiment of the invention, the modules may be implemented in software for execution by various types of processors. An identified module of executable code may, for instance, comprise one or more physical or logical blocks of computer instructions which may, for instance, be organized as an object, procedure, or function. Nevertheless, the executables of an identified module need not be physically located together, but may comprise disparate instructions stored in different bits which, when joined logically together, comprise the module and achieve the stated purpose for the module.
Indeed, a module of executable code may be a single instruction, or many instructions, and may even be distributed over several different code segments, among different programs, and across several memory devices. Likewise, operational data may be identified within modules and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different storage devices.
Where a module may be implemented in software, taking into account the level of existing hardware technology, a module may be implemented in software, and one skilled in the art may, without regard to cost, build corresponding hardware circuitry, including conventional Very Large Scale Integration (VLSI) circuits or gate arrays, and existing semiconductors such as logic chips, transistors, or other discrete components, to achieve the corresponding functions. A module may also be implemented in programmable hardware devices such as field programmable gate arrays, programmable array logic, programmable logic devices or the like.
The exemplary embodiments described above are described with reference to the drawings, many different forms and embodiments are possible without departing from the spirit and teachings of the present invention, and therefore, the present invention should not be construed as limited to the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will convey the scope of the invention to those skilled in the art. In the drawings, the size of the elements and relative sizes may be exaggerated for clarity. The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Unless otherwise indicated, a range of values includes the upper and lower limits of the range and any subranges therebetween.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the present invention.
Claims (10)
1. An image compression method, comprising:
compressing the plurality of first images provided by the target equipment at different compression ratios by adopting a plurality of compression algorithms to obtain second images of each compression algorithm corresponding to the plurality of first images at different compression ratios;
calculating image compression effect evaluation values corresponding to each compression algorithm under different compression ratios for a plurality of second images;
and determining an optimal compression algorithm and an optimal compression ratio according to the image compression effect evaluation values corresponding to each compression algorithm under different compression ratios.
2. The image compression method according to claim 1, wherein the calculating of the image compression effect evaluation value at the different compression ratios corresponding to each compression algorithm for the plurality of the second images includes:
performing image recognition on each second image, and determining the image recognition accuracy of the second image;
acquiring an image quality evaluation result of the second image;
and determining an image compression effect evaluation value corresponding to each compression algorithm according to the resource size of the first image, the image recognition accuracy of the second image, the resource size of the second image and the image quality evaluation result of the second image.
3. The image compression method according to claim 1, wherein the determining an optimal compression algorithm and an optimal compression ratio according to the image compression effect evaluation value at the different compression ratios corresponding to each compression algorithm includes:
the compression algorithm corresponding to the maximum value of the image compression effect evaluation value is an optimal compression algorithm;
compressing a plurality of groups of first images provided by the target equipment by adopting different high compression ratios by the optimal compression algorithm to obtain a plurality of groups of image compression effect evaluation values of third images corresponding to the first images;
performing image recognition on each third image, and determining the image recognition accuracy of the third images;
and determining the optimal compression ratio according to the image compression effect evaluation values of the third images and the image recognition accuracy of the third images.
4. The image compression method according to claim 1, characterized in that the method further comprises:
and saving the equipment identifier of the target equipment, the image characteristic identifier of the first image, the optimal compression ratio and the optimal compression algorithm as a data set.
5. The image compression method according to claim 4, characterized in that the method further comprises:
receiving an image compression request of a first device, wherein the image compression request comprises an image to be compressed;
acquiring a first characteristic identifier of the image to be compressed;
determining the data set matching a first device identification of the first device and the first characteristic identification; wherein the determined device identity in the data set matches the first device identity and the determined image feature identity in the data set matches the first feature identity;
and carrying out compression processing on the image to be compressed according to the determined optimal compression ratio and the determined optimal compression algorithm in the data set.
6. The image compression method according to claim 1, wherein before compressing the plurality of first images provided by the target device with different compression ratios, respectively, using a plurality of compression algorithms, the method comprises:
correcting the first image by adopting a Hough transform method;
and carrying out image edge detection processing on the corrected first image to obtain the processed first image.
7. The image compression method according to claim 6, wherein the correcting the first image by hough transform includes:
determining the coordinates of the center of a preset area on the first image by adopting a Hough transformation circular detection method;
determining the slope of a target graph in a circular area on the first image by adopting a Hough transformation linear detection method;
and carrying out angle correction and position correction on the first image according to the coordinates of the center and the slope.
8. An image compression apparatus, comprising:
the compression module is used for compressing the plurality of first images provided by the target equipment at different compression ratios by adopting a plurality of compression algorithms to obtain a second image of each compression algorithm corresponding to the plurality of first images at different compression ratios;
the calculating module is used for calculating image compression effect evaluation values corresponding to each compression algorithm under different compression ratios for a plurality of second images;
and the determining module is used for determining an optimal compression algorithm and an optimal compression ratio according to the image compression effect evaluation value corresponding to each compression algorithm under different compression ratios.
9. A terminal device, comprising: a transceiver, a processor, a memory, and a program or instructions stored on the memory and executable on the processor; the image compression method according to any one of claims 1 to 7, characterized in that the processor implements the image compression method when executing the program or instructions.
10. A readable storage medium having stored thereon a program or instructions which when executed by a processor performs the steps in the image compression method according to any of claims 1-7.
Priority Applications (1)
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5223150B1 (en) * | 2012-01-24 | 2013-06-26 | 株式会社アクセル | Image processing apparatus and image processing method |
| CN107341113A (en) * | 2016-04-29 | 2017-11-10 | 龙芯中科技术有限公司 | Cache compression method and device |
| CN109815199A (en) * | 2018-12-14 | 2019-05-28 | 深圳壹账通智能科技有限公司 | A kind of choosing method and device of picture compression algorithm |
| CN112348788A (en) * | 2020-11-03 | 2021-02-09 | 中科创达软件股份有限公司 | Image quality evaluation method and device, electronic equipment and storage medium |
| CN112770114A (en) * | 2020-12-29 | 2021-05-07 | 平安普惠企业管理有限公司 | Image data compression method and device, computer equipment and storage medium |
-
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5223150B1 (en) * | 2012-01-24 | 2013-06-26 | 株式会社アクセル | Image processing apparatus and image processing method |
| CN107341113A (en) * | 2016-04-29 | 2017-11-10 | 龙芯中科技术有限公司 | Cache compression method and device |
| CN109815199A (en) * | 2018-12-14 | 2019-05-28 | 深圳壹账通智能科技有限公司 | A kind of choosing method and device of picture compression algorithm |
| CN112348788A (en) * | 2020-11-03 | 2021-02-09 | 中科创达软件股份有限公司 | Image quality evaluation method and device, electronic equipment and storage medium |
| CN112770114A (en) * | 2020-12-29 | 2021-05-07 | 平安普惠企业管理有限公司 | Image data compression method and device, computer equipment and storage medium |
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