CN112153388A - Image compression method, device and related equipment - Google Patents
Image compression method, device and related equipment Download PDFInfo
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Abstract
The application discloses an image compression method, which comprises the steps of splitting a target image frame into a plurality of image sub-blocks when the target image frame is obtained; comparing each image subblock with an image subblock at a position corresponding to the previous image frame to obtain similarity; if the similarity is higher than a preset threshold value, extracting a target image sub-block different from the image sub-block of the previous image frame from the target image frame; compressing the target image sub-blocks to obtain a block compressed image; integrating the block compressed image and the compressed image corresponding to the previous image frame to obtain a target compressed image corresponding to the target image frame; the image compression method can realize rapid and efficient image compression and effectively reduce the power consumption of the processor. The application also discloses an image compression device, equipment and a computer readable storage medium, which have the beneficial effects.
Description
Technical Field
The present application relates to the field of image processing technologies, and in particular, to an image compression method, and further, to an image compression apparatus, a device, and a computer-readable storage medium.
Background
With the continuous development of internet multimedia technology, digital image information becomes more and more important, and due to the large data volume, image compression technology becomes an indispensable part, and commonly used image compression technologies include JPEG compression, wavelet transform compression and fractal compression. However, the conventional image compression technology processes image data frame by frame, which has a huge task amount and causes a great burden on a processor, and also generates great power consumption because image compression processing needs to be performed uninterruptedly for a long time.
Therefore, how to implement fast and efficient image compression while effectively reducing the power consumption of the processor is an urgent problem to be solved by those skilled in the art.
Disclosure of Invention
The image compression method can realize rapid and efficient image compression and effectively reduce the power consumption of a processor; another object of the present application is to provide an image compression apparatus, a device, and a computer-readable storage medium, which also have the above-mentioned advantageous effects.
In a first aspect, the present application provides an image compression method, including:
when a target image frame is acquired, splitting the target image frame into a plurality of image sub-blocks;
comparing each image subblock with an image subblock at a position corresponding to the previous image frame to obtain similarity;
if the similarity is higher than a preset threshold value, extracting a target image sub-block different from the image sub-block of the previous image frame from the target image frame;
compressing the target image sub-blocks to obtain a block compressed image;
and integrating the block compressed image and the compressed image corresponding to the previous image frame to obtain a target compressed image corresponding to the target image frame.
Preferably, before splitting the target image frame into a plurality of image sub-blocks, the method further includes:
and carrying out format conversion on the target image frame according to a preset image format.
Preferably, the preset image format is a YUV format.
Preferably, the splitting the target image frame into a plurality of image sub-blocks includes:
and splitting the target image frame according to the resolution ratio to obtain each image sub-block.
Preferably, the comparing each image sub-block with the image sub-block at the position corresponding to the previous image frame to obtain the similarity includes:
calculating a first hash value of each image sub-block of the target image frame;
calculating a second hash value of each image sub-block of the previous image frame;
and comparing each first hash value with the corresponding second hash value to obtain the similarity.
Preferably, the image compression method further includes:
and if the similarity is not higher than the preset threshold, compressing the target image frame to obtain the target compressed image.
Preferably, the image compression method further includes:
and storing the target compressed image into a preset storage space.
In a second aspect, the present application also discloses an image compression apparatus, comprising:
the image splitting module is used for splitting a target image frame into a plurality of image sub-blocks when the target image frame is obtained;
the image comparison module is used for comparing each image subblock with an image subblock at a position corresponding to the previous image frame to obtain similarity;
the image extraction module is used for extracting a target image sub-block different from the image sub-block of the previous image frame from the target image frame if the similarity is higher than a preset threshold value;
the block compression module is used for compressing the target image sub-blocks to obtain a block compressed image;
and the image integration module is used for integrating the block compressed image and the compressed image corresponding to the previous image frame to obtain a target compressed image corresponding to the target image frame.
In a third aspect, the present application also discloses an image compression apparatus, comprising:
a memory for storing a computer program;
a processor for executing the computer program to implement the steps of any of the image compression methods described above.
In a fourth aspect, the present application also discloses a computer readable storage medium having stored therein a computer program which, when executed by a processor, is adapted to carry out the steps of any of the image compression methods as described above.
The image compression method comprises the steps that when a target image frame is obtained, the target image frame is split into a plurality of image sub-blocks; comparing each image subblock with an image subblock at a position corresponding to the previous image frame to obtain similarity; if the similarity is higher than a preset threshold value, extracting a target image sub-block different from the image sub-block of the previous image frame from the target image frame; compressing the target image sub-blocks to obtain a block compressed image; and integrating the block compressed image and the compressed image corresponding to the previous image frame to obtain a target compressed image corresponding to the target image frame.
Therefore, the image compression method provided by the application can be used for splitting a target image frame to obtain a plurality of image sub-blocks, comparing and analyzing the image sub-blocks to obtain the similarity between the target image frame and a previous image frame, further, when the similarity between the target image frame and the previous image frame is low, only the image sub-blocks with differences are extracted from the target image frame to be compressed, and finally, the compression result and the compression result of the previous image frame are integrated to complete the compression of the target image frame, namely, only the parts with differences in the target image frame are compressed instead of compressing the whole target image frame, so that the processing amount of a processor can be effectively reduced, the image compression efficiency is improved, and meanwhile, the power consumption of the processor is also reduced.
The image compression device, the image compression device and the computer-readable storage medium provided by the application all have the beneficial effects, and are not described herein again.
Drawings
In order to more clearly illustrate the technical solutions in the prior art and the embodiments of the present application, the drawings that are needed to be used in the description of the prior art and the embodiments of the present application will be briefly described below. Of course, the following description of the drawings related to the embodiments of the present application is only a part of the embodiments of the present application, and it will be obvious to those skilled in the art that other drawings can be obtained from the provided drawings without any creative effort, and the obtained other drawings also belong to the protection scope of the present application.
Fig. 1 is a schematic flowchart of an image compression method provided in the present application;
FIG. 2 is a schematic diagram of an image compression system provided in the present application;
FIG. 3 is a flowchart illustrating an image compression method according to the present application;
FIG. 4 is a schematic structural diagram of an image compression apparatus provided in the present application;
fig. 5 is a schematic structural diagram of an image compression apparatus provided in the present application.
Detailed Description
The core of the application is to provide an image compression method, which can realize fast and efficient image compression and effectively reduce the power consumption of a processor; another core of the present application is to provide an image compression apparatus, a device and a computer-readable storage medium, which also have the above-mentioned advantages.
In order to more clearly and completely describe the technical solutions in the embodiments of the present application, the technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Referring to fig. 1, fig. 1 is a schematic flow chart of an image compression method provided in the present application, where the image compression method may include:
s101: when a target image frame is acquired, splitting the target image frame into a plurality of image sub-blocks;
the method aims to realize the acquisition and the splitting of a target image frame, wherein the target image frame is image data needing to be compressed. Specifically, when image compression is required, the target image frame may be sent to the image compression device, and when the device master controller acquires the target image frame, the device master controller may perform image splitting processing to obtain a plurality of image sub-blocks. It can be understood that the specific type of the image splitting method is not unique, and the image splitting may be implemented, and the number of image sub-blocks may be different by using different image splitting methods, which does not affect the implementation of the technical solution, and is not limited in the present application.
As a preferred embodiment, before the splitting the target image frame into a plurality of image sub-blocks, the method may further include: and carrying out format conversion on the target image frame according to a preset image format.
The present preferred embodiment is directed to implementing image format conversion to convert a target image frame into image data in a specific format, i.e., the above-mentioned preset image format, thereby implementing image compression processing. It can be understood that, by converting the image format, the uniformity of the compressed image format can be effectively ensured, and the image compression efficiency can be improved. The specific type of the preset image format is not unique, and the specific type is set by a technician according to actual requirements, which is not limited in the application.
As a preferred embodiment, the preset image format may be a YUV format.
The preferred embodiment provides a specific type of preset image format, namely YUV format. Specifically, YUV is a color coding method, which is used to describe the color and saturation of an image and can be divided into three components, wherein "Y" represents brightness, i.e. gray scale, and "U" and "V" represent chrominance, and the most advantage of using YUV format is that it only needs to occupy very little bandwidth.
As a preferred embodiment, the splitting the target image frame into a plurality of image sub-blocks may include: and splitting the target image frame according to the resolution ratio to obtain each image sub-block.
The preferred embodiment provides a more specific image splitting method, that is, a target image frame is split into a plurality of image sub-blocks according to different resolutions, where the resolution is the number of pixel points included in a unit inch and is a measurement standard of image definition or concentration.
S102: comparing each image sub-block with the image sub-block at the corresponding position of the previous image frame to obtain the similarity;
the step aims to realize image comparison and obtain the image similarity, wherein the image similarity refers to the similarity between a target image frame and a previous image frame. Specifically, each image sub-block of the target image frame is compared with the image sub-block at the corresponding position of the previous image frame one by one, that is, the image sub-blocks at the same position of the two image frames are compared to realize the comparison of the two image frames, so that the similarity between the target image frame and the previous image frame can be obtained.
As a preferred embodiment, the comparing each image sub-block with the image sub-block at the position corresponding to the previous image frame to obtain the similarity may include: calculating a first hash value of each image sub-block of the target image frame; calculating a second hash value of each image sub-block of the last image frame; and comparing each first hash value with the corresponding second hash value to obtain the similarity.
The preferred embodiment provides a more specific image subblock comparison method, so as to achieve the acquisition of similarity. Specifically, the hash calculation may be performed on each image sub-block of the target image frame and the previous image frame to obtain the hash value of each image sub-block, and then the difference between the two image sub-blocks is determined by comparing the hash values (the first hash value and the second hash value) of the image sub-blocks at the same position of the two image sub-blocks to obtain the similarity between the two image sub-blocks.
S103: if the similarity is higher than a preset threshold value, extracting a target image sub-block different from the image sub-block of the previous image frame from the target image frame;
s104: compressing the target image sub-blocks to obtain block compressed images;
this step is intended to achieve the extraction of a target image sub-block, which is an image sub-block in the target image frame that is different from the previous image frame. Specifically, when the similarity between the target image frame and the previous image frame is high, that is, the similarity exceeds the preset threshold, the image sub-blocks, which are different from the previous image frame, in the target image frame can be extracted and used as the target image sub-blocks to be compressed, so as to obtain a block compressed image, that is, only different parts of the two image frames are extracted and compressed, so that the image compression efficiency can be effectively improved compared with the conventional whole image compression. The specific value of the preset threshold does not affect the implementation of the technical scheme, and can be set by a technician according to actual requirements, which is not limited by the application.
S105: and integrating the block compressed image and the compressed image corresponding to the previous image frame to obtain a target compressed image corresponding to the target image frame.
The step aims to realize the integration of compressed images, and because the previous step only carries out image compression processing on different image sub-blocks in two frame images, the compression result is only the compressed image of the partial image sub-blocks, namely the block compressed image is not the compressed image of a complete target image frame, and because the uncompressed part of the target image frame is the same as the previous image frame, the target compressed image corresponding to the complete target image frame can be obtained only by integrating the block compressed image and the compressed image corresponding to the previous image frame, thereby completing the image compression processing of the target image frame.
As a preferred embodiment, the image compression method may further include: and if the similarity is not higher than the preset threshold, compressing the target image frame to obtain a target compressed image.
Specifically, when the similarity between the target image frame and the previous image frame is not high, it is indicated that different portions of the two image frames occupy a larger portion, that is, the number of target image sub-blocks is larger, at this time, the target image sub-blocks do not need to be extracted, so that time waste is effectively avoided, the whole target image frame is directly compressed, and a corresponding target compressed image can be obtained.
As a preferred embodiment, the image compression method may further include: and storing the target compressed image into a preset storage space.
The step aims to realize image storage, specifically, a storage space can be created in advance, and after a target compressed image corresponding to a target image frame is obtained, the target compressed image is stored in the preset storage space. By storing the target compressed image, a comparison template can be provided for the image compression processing process of the subsequent image frame, and further the image compression processing of the subsequent image frame is realized.
Therefore, the image compression method provided by the application can be used for splitting a target image frame to obtain a plurality of image sub-blocks, comparing and analyzing the image sub-blocks to obtain the similarity between the target image frame and a previous image frame, further, when the similarity between the target image frame and the previous image frame is low, only the image sub-blocks with differences are extracted from the target image frame to be compressed, and finally, the compression result and the compression result of the previous image frame are integrated to complete the compression of the target image frame, namely, only the parts with differences in the target image frame are compressed instead of compressing the whole target image frame, so that the processing amount of a processor can be effectively reduced, the image compression efficiency is improved, and meanwhile, the power consumption of the processor is also reduced.
On the basis of the foregoing embodiments, the present preferred embodiment provides a more specific image compression method, which is implemented in the following steps:
first, please refer to fig. 2, fig. 2 is a schematic structural diagram of an image compression system provided in the present application, the image compression system mainly includes a capture module, a format conversion module, a splitting module, an input buffer module, a comparison module, a MUX module, an image compression module, an image processing module, and an output buffer module. The capturing module is used for acquiring original image data; the format conversion module is used for converting the image format from an RGB format to a YUV format; the splitting module is used for splitting the images with different resolutions into different numbers of image sub-blocks; the input buffer module is used for storing two frames of image data, including image sub-blocks corresponding to each other; the comparison module is used for analyzing the difference of the two frames of cached image data; the image compression module is used for realizing image compression; the MUX module is used for determining whether the image data directly enters the image compression module for processing or needs to be processed by the image processing module and then compressed according to the comparison result of the comparison module; the image processing module is used for processing two frames of image data with small difference, specifically, extracting a differential part from the image data according to coordinate values, transmitting the differential part to the image compression module for compression, and integrating the compressed part with the compression result of the previous frame of image; the output buffer module is used for storing the two frames of compressed image data.
More specifically, the comparison module performs hash calculation on each image subblock of the two frames of images to obtain a hash value of each image subblock, and then determines the difference between the two frames of images by comparing the hash values of the image subblocks at the same position of the two frames of images. Further, after comparison and analysis, if only a small part of the image sub-blocks of the two frames of images are different, the coordinates of the image sub-blocks of different parts are sent to the image processing module, and the image processing module sends the part of the image sub-blocks to the image compression module for compression processing according to the obtained coordinate values; if most image subblocks in the two frames of images are different, sending the complete image data to an image compression module for compression.
Based on the above image compression system, please refer to fig. 3, fig. 3 is a flowchart of an image compression method provided in the present application, and the workflow is as follows:
when an nth frame of image needs to be compressed, firstly, acquiring nth frame of image data through a capturing module, converting the image format from an RGB (red, green and blue) format into a YUV format through a format conversion module, and then splitting the nth frame of image data in the YUV format into different numbers of image sub-blocks with the same size according to the size of resolution through a splitting module; then, the split image chunks are sequentially put into an input cache module to replace the n-2 th frame of image data; further, the image subblock of the nth frame of image data and the image subblock of the (n-1) th frame of image data are compared and analyzed through a Hash algorithm in a comparison module, if the difference between the image subblocks is larger, the image subblock directly enters an image compression module to compress the nth frame of image data, and finally the compressed image data is put into an output cache module to be output; if the difference between the image subblocks is smaller, the image processing module extracts the image subblocks with the difference in the nth frame of image data, sends the image subblocks to the image compression module for compression, returns the compression result to the image processing module, integrates the compression result of part of the image subblocks with the compression result of the nth-1 frame of image data in the output cache module by the image processing module, and finally puts the integrated image data into the output cache module for output. In the working process, when the image transformation of continuous frames is not large, only the differential part is compressed, thereby greatly reducing the workload of the processor, improving the processing speed and simultaneously reducing the power consumption of the processor.
It can be seen that the image compression method provided in the embodiment of the present application splits a target image frame to obtain a plurality of image sub-blocks, obtains the similarity between the target image frame and a previous image frame by performing a comparative analysis on the image sub-blocks, further, when the similarity between the target image frame and the previous image frame is low, only the image sub-blocks with differences are extracted from the target image frame to perform a compression process, and finally the compression result and the compression result of the previous image frame are integrated to complete the compression of the target image frame, that is, only the portions with differences in the target image frame are compressed, but not the entire target image frame is compressed, which can effectively reduce the processing amount of a processor, improve the image compression efficiency, and also reduce the power consumption of the processor.
To solve the above technical problem, the present application further provides an image compression apparatus, please refer to fig. 4, where fig. 4 is a schematic structural diagram of the image compression apparatus provided in the present application, and the image compression apparatus may include:
the image splitting module 1 is configured to split a target image frame into a plurality of image sub-blocks when the target image frame is acquired;
the image comparison module 2 is used for comparing each image sub-block with the image sub-block at the position corresponding to the previous image frame to obtain the similarity;
the image extraction module 3 is used for extracting a target image sub-block different from the image sub-block of the previous image frame from the target image frame if the similarity is higher than a preset threshold;
the block compression module 4 is used for compressing the target image sub-blocks to obtain a block compressed image;
and the image integration module 5 is configured to integrate the block compressed image and the compressed image corresponding to the previous image frame to obtain a target compressed image corresponding to the target image frame.
It can be seen that, the image compression apparatus provided in the embodiment of the present application splits a target image frame to obtain a plurality of image sub-blocks, obtains the similarity between the target image frame and a previous image frame by performing a comparison analysis on the image sub-blocks, further, when the similarity between the target image frame and the previous image frame is low, only the image sub-blocks with differences are extracted from the target image frame to perform a compression process, and finally the compression result and the compression result of the previous image frame are integrated to complete the compression of the target image frame, that is, only the portions with differences in the target image frame are compressed, but not the entire target image frame is compressed, which can effectively reduce the processing amount of a processor, improve the image compression efficiency, and also reduce the power consumption of the processor.
As a preferred embodiment, the image compression apparatus may further include an image conversion module, configured to perform format conversion on the target image frame according to a preset image format before the target image frame is split into the plurality of image sub-blocks.
As a preferred embodiment, the preset image format may be a YUV format.
As a preferred embodiment, the image splitting module 1 may be specifically configured to, when the target image frame is obtained, split the target image frame according to the resolution, so as to obtain each image sub-block.
As a preferred embodiment, the image comparison module 2 may be specifically configured to calculate a first hash value of each image sub-block of the target image frame; calculating a second hash value of each image sub-block of the last image frame; and comparing each first hash value with the corresponding second hash value to obtain the similarity.
As a preferred embodiment, the image compression apparatus may further include an image compression module, configured to perform compression processing on the target image frame to obtain a target compressed image if the similarity is not higher than a preset threshold.
As a preferred embodiment, the image compression apparatus may further include an image storage module for storing the target compressed image into a preset storage space.
For the introduction of the apparatus provided in the present application, please refer to the above method embodiments, which are not described herein again.
To solve the above technical problem, the present application further provides an image compression apparatus, please refer to fig. 5, where fig. 5 is a schematic structural diagram of an image compression apparatus provided in the present application, and the image compression apparatus may include:
a memory 10 for storing a computer program;
the processor 20, when executing the computer program, may implement the steps of any of the image compression methods described above.
For the introduction of the system provided by the present application, please refer to the above method embodiment, which is not described herein again.
To solve the above problem, the present application further provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, can implement the steps of any one of the image compression methods described above.
The computer-readable storage medium may include: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
For the introduction of the computer-readable storage medium provided in the present application, please refer to the above method embodiments, which are not described herein again.
The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The technical solutions provided by the present application are described in detail above. The principles and embodiments of the present application are explained herein using specific examples, which are provided only to help understand the method and the core idea of the present application. It should be noted that, for those skilled in the art, without departing from the principle of the present application, several improvements and modifications can be made to the present application, and these improvements and modifications also fall into the protection scope of the present application.
Claims (10)
1. An image compression method, comprising:
when a target image frame is acquired, splitting the target image frame into a plurality of image sub-blocks;
comparing each image subblock with an image subblock at a position corresponding to the previous image frame to obtain similarity;
if the similarity is higher than a preset threshold value, extracting a target image sub-block different from the image sub-block of the previous image frame from the target image frame;
compressing the target image sub-blocks to obtain a block compressed image;
and integrating the block compressed image and the compressed image corresponding to the previous image frame to obtain a target compressed image corresponding to the target image frame.
2. The image compression method of claim 1, wherein before the splitting the target image frame into a plurality of image sub-blocks, further comprising:
and carrying out format conversion on the target image frame according to a preset image format.
3. The image compression method according to claim 2, wherein the preset image format is YUV format.
4. The image compression method of claim 1, wherein the splitting the target image frame into a plurality of image sub-blocks comprises:
and splitting the target image frame according to the resolution ratio to obtain each image sub-block.
5. The image compression method according to claim 1, wherein the comparing each image sub-block with the image sub-block at the position corresponding to the previous image frame to obtain the similarity comprises:
calculating a first hash value of each image sub-block of the target image frame;
calculating a second hash value of each image sub-block of the previous image frame;
and comparing each first hash value with the corresponding second hash value to obtain the similarity.
6. The image compression method according to claim 1, further comprising:
and if the similarity is not higher than the preset threshold, compressing the target image frame to obtain the target compressed image.
7. The image compression method according to claim 1, further comprising:
and storing the target compressed image into a preset storage space.
8. An image compression apparatus, comprising:
the image splitting module is used for splitting a target image frame into a plurality of image sub-blocks when the target image frame is obtained;
the image comparison module is used for comparing each image subblock with an image subblock at a position corresponding to the previous image frame to obtain similarity;
the image extraction module is used for extracting a target image sub-block different from the image sub-block of the previous image frame from the target image frame if the similarity is higher than a preset threshold value;
the block compression module is used for compressing the target image sub-blocks to obtain a block compressed image;
and the image integration module is used for integrating the block compressed image and the compressed image corresponding to the previous image frame to obtain a target compressed image corresponding to the target image frame.
9. An image compression apparatus characterized by comprising:
a memory for storing a computer program;
a processor for executing the computer program to carry out the steps of the image compression method according to any one of claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, is adapted to carry out the steps of the image compression method according to any one of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112948151A (en) * | 2021-04-13 | 2021-06-11 | 山东云海国创云计算装备产业创新中心有限公司 | Program interface image transmission method, substrate management controller and remote control equipment |
| CN113613022A (en) * | 2021-06-18 | 2021-11-05 | 山东云海国创云计算装备产业创新中心有限公司 | JPEG image compression method, device, equipment and readable medium |
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