CN110099279A - A kind of method of hardware based adjustable lossy compression - Google Patents
A kind of method of hardware based adjustable lossy compression Download PDFInfo
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- CN110099279A CN110099279A CN201810093981.7A CN201810093981A CN110099279A CN 110099279 A CN110099279 A CN 110099279A CN 201810093981 A CN201810093981 A CN 201810093981A CN 110099279 A CN110099279 A CN 110099279A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- 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
- H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
- H04N19/124—Quantisation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- 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
- H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
- H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
- H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
Abstract
This application discloses a kind of method of hardware based adjustable lossy compression, the application the technical solution adopted is that: piecemeal is carried out to the image of input, pixel mean value and the pixel for calculating each macro block are very poor；When pixel is very poor is greater than given threshold, each macro block is quantified, macroblock transform result parameter list is obtained；When pixel is very poor is not more than the given threshold, the list of macroblock transform result parameter is arranged according to pixel mean value；Compression of images parameter list is obtained according to macroblock transform result parameter list, carries out writing compression obtaining compressed image file to compression of images parameter list.Using technical solution of the present invention, calculation amount is enabled to significantly to be reduced, only allows to be conveniently realized under hardware environment with comparison operation with a small amount of plus-minus；And the present invention provides customized parameters such as transformation threshold values, the optimal result of suitable current demand can be selected for greater flexibility, adapts to a variety of different compression requirements.
Description
Technical field
The present invention relates to field of image processings, more particularly to a kind of method of hardware based adjustable lossy compression.
Background technique
When carrying out image or transmission of video, due to the limitation of transmission bandwidth and transmission rate, the video to transmission is needed
Or image carries out compression processing.Since original sampling data amount is huge, and memory storage capabilities are limited, and band when data transmission
The limitation of the factors such as width, transmission rate, so that the image of high compression ratio or the lossy compression of video file are imperative.
In order to meet the needs of different compression ratios and picture quality, and it is easier to algorithm and is achieved (example in hardware view
Such as, existing common jpeg compression method computation complexity is excessively high, it is difficult to be based on hardware realization), thus study based on hard
The controllable compression method of part has important practical significance.
Summary of the invention
In order to satisfy the use demand compression of images more, this application provides a kind of hardware based are adjusted to damage pressure
The method of contracting.
The application the technical solution adopted is that: a kind of compression method of hardware based adjustable lossy compression, comprising:
Piecemeal is carried out to the image of input, pixel mean value and the pixel for calculating each macro block are very poor；
When the pixel is very poor is greater than given threshold, each macro block is quantified, obtains macroblock transform result parameter column
Table；When the pixel is very poor is not more than the given threshold, macroblock transform result parameter is arranged according to the pixel mean value and is arranged
Table；
Compression of images parameter list is obtained according to the macroblock transform result parameter list, described image compression parameters are arranged
Table, which carries out writing compression, obtains compressed image file.
Interactive interface shows that a variety of preset values are selected for user, and user selects one of them pre- according to the demand of picture quality
If value is used as given threshold.
It is described that each macro block is quantified, the transformation results parameter list of each macro block is obtained, following sub-step is specifically included:
Calculate quantization threshold and quantization scale list；
The macro block pixels deviation matrix quantified according to quantization scale list；
According to the macro block pixels deviation matrix of quantization, the pixel mean value of each macro block, quantization mark and quantization threshold setting
Macroblock transform result parameter list.
The calculating quantization threshold specially calculates the difference of current macro block pixels maximum value and current macro block pixels mean value
Value, and calculate the difference of current macro block pixels mean value and current macro block pixels minimum value, the maximum of more above-mentioned two difference
Value, using the maximum value of two differences as the quantization threshold of current macro.
Calculate quantization scale list, the specially specific range of multiple quantized intervals of setting current macro.
The macro block pixels deviation matrix quantified according to quantization scale list, specifically: by multiple quantized intervals
Endpoint be set as default value group, successively determine current macro in each pixel deviations value it is corresponding in the default value group
Numerical value, the quantizing pixel deviation of each position as current macro combine the quantizing pixel deviation of each position of current macro
Obtain macro block pixels deviation matrix.
The macroblock transform result parameter list includes pixel mean value, quantization mark, the quantization threshold for effectively quantifying macro block
With the macro block pixels deviation matrix of quantization.
It is described that compression of images parameter list is obtained according to the macroblock transform result parameter list, it specifically includes:
According to macroblock transform result parameter list, summarize to obtain image transformation results parameter list；
Compression of images parameter list is calculated by image transformation results parameter list.
Described image compression parameters list include pixel mean value a reference value, quantization threshold a reference value, effectively quantization macro block it is total
Number, coding bit wide list and coded information sequences.
A kind of decompression method of hardware based adjustable lossy compression, comprising:
It is unziped it to obtain compression of images parameter list according to compressed image file；Compression of images parameter list is carried out
Decoding obtains the transformation results parameter list of each macro block；
When the pixel in the transformation results parameter list of each macro block is very poor is greater than given threshold, by each pixel of current macro
Value is reduced to current macro block pixels mean value and adds corresponding deviation；When the pixel in the transformation results parameter list of each macro block is very poor not
When greater than given threshold, each pixel value of current macro is reduced to current macro block pixels mean value；
The pixel value of each macro block after reduction is summarized into the image after being decompressed and output.
It is described that compression of images parameter list is decoded to obtain the transformation results parameter list of each macro block, specifically:
By the equal value sequence in pixel mean value a reference value and coded information sequences, the pixel mean value of each macro block is obtained；
By effectively quantifying the mark sequence in macro block sum and coded information sequences, the quantization mark of each macro block is obtained；
By the threshold series in quantization threshold a reference value and coded information sequences, the quantization threshold of each effective quantization macro block is obtained
Value；
By the sequence of differences in quantization threshold and coded information sequences, the deviation value matrix quantified；
By the pixel mean value of obtained each macro block, quantization mark, the deviation of the quantization threshold of effectively quantization macro block and quantization
Value matrix combines to obtain the transformation results parameter list of each macro block.
The beneficial effect that the present invention obtains is: using technical solution of the present invention, calculation amount is enabled to obtain significantly
Reduce, only allows to be conveniently realized under hardware environment with comparison operation with a small amount of plus-minus；And the present invention mentions
The customized parameters such as transformation threshold value have been supplied, the optimal result of suitable current demand can be selected for greater flexibility, adapt to various differences
Compression requirements.
Detailed description of the invention
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The some embodiments recorded in application can also be obtained according to these attached drawings other for those of ordinary skill in the art
Attached drawing.
Fig. 1 is existing compression method flow chart；
Fig. 2 is the compression method process for the hardware based adjustable lossy compression of one kind that the embodiment of the present invention one provides
Figure；
Fig. 3 is existing decompression method flow chart；
Fig. 4 is the decompression method process of the hardware based adjustable lossy compression of one kind provided by Embodiment 2 of the present invention
Figure.
Specific embodiment
Below with reference to the attached drawing in the embodiment of the present application, technical solutions in the embodiments of the present application carries out clear, complete
Ground description, it is clear that described embodiment is some embodiments of the present application, instead of all the embodiments.Based on the application
In embodiment, those skilled in the art's every other embodiment obtained without making creative work, all
Belong to the range of the application protection.
Embodiment one
Referring to Fig. 1, existing compression method specifically:
Step 101: piecemeal being carried out to the image of input, image transformation results parameter is obtained to each macroblock transform；
Step 102: carrying out summarizing arrangement obtaining compression of images parameter list to image transformation results parameter；
Step 103: coding being carried out to image according to compression of images parameter list and writes compression, obtains compressed image file；
The embodiment of the present invention one improves on the basis of existing compression method, realizes adjustable lossy compression,
Improved compression method specifically:
A kind of compression method of hardware based adjustable lossy compression, as shown in Figure 2, which comprises
Step 201: piecemeal being carried out to the image of input, the pixel mean value for calculating each macro block is very poor with pixel and save；
Step 202: judging that pixel is very poor and whether be greater than given threshold, if so, 203 are thened follow the steps, otherwise according to picture
The list of macroblock transform result parameter is arranged in plain mean value, executes step 206；
Wherein, given threshold is the corresponding preset value that user selects according to the demand of picture quality, it is preferred that Yong Hujiao
The mutual a variety of preset values of interface display are selected for user, and user selects one of them pre- according to the use demand of the extent of damage of compression
If value is used as given threshold.
Step 203: calculating quantization threshold and quantization scale list；
The calculation method of the quantization threshold Theta of each macro block is: calculating current macro block pixels maximum value and current macro picture
The difference of plain mean value, and the difference of current macro block pixels mean value and current macro block pixels minimum value is calculated, it is more above-mentioned two
The maximum value of difference, using the maximum value of two differences as the quantization threshold of current macro；
The calculation method of quantization scale list specifically: the specific range of multiple quantized intervals of current macro is set, it is excellent
6 values of choosing setting, including-Theta ,-Theta*0.75 ,-Theta*0.25, Theta*0.25, Theta*0.75, Theta, example
If calculated quantization threshold is 10, then quantization scale list is { -10, -7.5, -2.5,2.5,7.5,10 }.
Step 204: the macro block pixels deviation matrix quantified according to quantization scale list；
This step is specifically, set default value group for the endpoint of multiple quantized intervals, successively in determining current macro
Each pixel deviations value corresponding numerical value in the default value group, the quantizing pixel deviation of each position as current macro,
It combines the quantizing pixel deviation of each position of current macro to obtain macro block pixels deviation matrix；
For example,
Numerical value in-Theta~- Theta*0.75 range is set as the first numerical value, such as -2；
Second value, such as -1 are set by the numerical value in-Theta*0.75~- Theta*0.25 range；
Third value, such as 0 are set by the numerical value within the scope of-Theta*0.25~Theta*0.25；
The 4th numerical value, such as 1 are set by the numerical value within the scope of Theta*0.25~Theta*0.75；
The 5th numerical value, such as 2 are set by the numerical value within the scope of Theta*0.75~Theta；
Compare each pixel deviations value in current macro in which above-mentioned numberical range, is then set to corresponding
One to the 5th numerical value；For example, multiple pixel values of current macro are -9, -1,3 ..., the current macro obtained after quantified
Pixel deviations are { -2,0,1 ... }, combine the pixel deviations after all quantizations of current macro to obtain macro block pixels deviation square
Battle array；
It is compressed by above-mentioned quantization, by the very poor pixel value more than user's use demands of pixel in macro block, from -10 to 10 models
It is compressed in the range of -2 to 2 in enclosing, is greatly saved amount of storage, improve the rate of image data transmission.
Step 205: macroblock transform result is arranged according to the macro block pixels deviation matrix of quantization threshold, pixel mean value and quantization
Parameter list；
Macroblock transform parameter list information includes pixel mean value, quantization mark, the quantization threshold and amount for effectively quantifying macro block
The macro block pixels deviation matrix of change；
Wherein, quantization mark specifically marks whether each macro block is quantified, it is preferred that the macro block quantified is set 1, not
The macro block quantified sets 0, for example, the image of input includes four macro blocks, wherein macro block 1 and macro block 3 are quantified, macro block 2
Do not quantified with macro block 4, then quantization is identified as 1010；
If the pixel of some macro block of image is very poor to be less than given threshold, without being quantified, macroblock transform parameter
The macro block pixels deviation matrix quantified in list is then set as empty, is recorded by quantization mark.
Step 206: compression of images parameter list is obtained according to macroblock transform result parameter list；
Wherein, according to macroblock transform result parameter list, summarize to obtain image transformation results parameter list；It is converted by image
Compression of images parameter list is calculated in result parameter list.
Step 207: carrying out writing compression obtaining compressed image file to compression of images parameter list.
Specifically, selecting bit wide appropriate according to compression of images parameter list, compression parameters are carried out to write compression；Wherein,
Bit wide appropriate is selected according to according to compression of images parameter list specifically:
According to the corresponding mean value bit wide of pixel mean value computation in compression of images parameter list；
Corresponding mark bit wide is calculated according to the quantization mark in compression of images parameter list；
Corresponding threshold value bit wide is calculated according to the quantization threshold in compression of images parameter list；
Corresponding difference bit wide is calculated according to the macro block pixels deviation matrix of the quantization in compression of images parameter list；
Circular is identical, illustrates by taking pixel mean value as an example, calculates pixel mean value N within the scope of 2 Nth power
Value is mean value bit wide, such as pixel mean value is 12, then within the scope of 2 biquadratic, i.e., mean value bit wide is 4, and so on
To bit wide appropriate；
There are many mode of existing compression of images parameter list, it should be noted that the application does not limit which is used
Kind of mode, in the following manner for illustrate；
Compression of images parameter list includes pixel mean value a reference value, quantization threshold a reference value, effectively quantization macro block sum, volume
The wide list of code bit and coded information sequences；
Wherein, pixel mean value a reference value is the pixel mean value of first macro block；
Quantization threshold a reference value is the quantization threshold of first effective quantization macro block；
Effectively quantization macro block sum is to quantify to be identified as 1 number of macroblocks；
Coding bit wide list is the bit wide list being made of mean value bit wide, mark bit wide, threshold value bit wide and difference bit wide；
Coded information sequences include equal value sequence, threshold series, mark sequence and sequence of differences.Specifically, equal value sequence
It with mark sequence is carried out obtained by differential pulse coding with quantization mark according to corresponding bit wide by the pixel mean value of a macro block respectively；
Threshold series and sequence of differences are to carry out Differential pulse code modulation by the deviation value matrix after each effective macro block threshold value and quantization respectively
It encodes and obtains, the macro block for being identified as 0 to difference here only has compressed its macro block mark and mean value residual error.
Coding is carried out to image according to compression of images parameter list and writes compression, obtains compressed image file；Specifically, will figure
As compression parameters list carries out the compressed image file that coding boil down to computer can identify.
By compared with currently used method for compressing image, present invention has an advantage that
1, core of the invention algorithm steps calculation amount is significantly reduced, and the algorithm is only with a small amount of plus-minus compared with
Operation is instead of largely plus-minus and multiplication and division operation in existing compression algorithm, therefore the algorithm can be in the side of being able under hardware environment
Just it realizes；
2, the present invention provides customized parameters such as transformation threshold values, compared to existing compression algorithm, which can be cleverer
The optimal result for selecting suitable current demand livingly adapts to a variety of different compression requirements.
Embodiment two
Referring to Fig. 3, existing decompression method specifically:
Step 301: being unziped it to obtain compression of images parameter list according to compressed image file；
Step 302: being decoded to obtain each macroblock transform result parameter list according to compression of images parameter list；
Step 303: inverse transformation being carried out to each macroblock transform result parameter list and summarizes the image after being decompressed.
The embodiment of the present invention two improves on the basis of existing decompression method, improved in corresponding embodiment one
Compression method realizes adjustable lossy compression, improved decompression method specifically:
A kind of decompression method of hardware based adjustable lossy compression, as shown in Figure 4, which comprises
Step 401: being unziped it to obtain compression of images parameter list according to compressed image file；
Step 402: compression of images parameter list being decoded to obtain each macroblock transform result parameter list；
By the equal value sequence in pixel mean value a reference value and coded information sequences, the pixel mean value of each macro block is obtained；
By effectively quantifying the mark sequence in macro block sum and coded information sequences, quantization mark is obtained；
By the threshold series in quantization threshold a reference value and coded information sequences, the quantization threshold of each effective macro block is obtained；
By the sequence of differences in quantization threshold a reference value and coded information sequences, the deviation value matrix quantified；
The pixel mean value of obtained each macro block, quantization mark, quantization threshold and the deviation matrix of quantization are combined to obtain
Each macroblock transform result parameter list；
Step 403: it is more very poor than the pixel in each macroblock transform result parameter list whether to be greater than given threshold, if so,
Then follow the steps 404, no to then follow the steps 405:
Step 404: each pixel value of current macro being reduced to current macro block pixels mean value and adds corresponding deviation, executes step
406；
Specifically,
If pixel is very poor to be greater than given threshold, illustrate that current macro is the macro block after quantization, to macro after the quantization
It needs to be gone back according to the deviation value matrix in the pixel mean value and transformation results parameter list of current macro when block is restored
It is former.
Step 405: each pixel value of current macro being reduced to current macro block pixels mean value, executes step 406；
If pixel is very poor to be less than or equal to given threshold, illustrate current macro without quantization, then to this without amount
When the macro block of change is restored, directly using the pixel mean value of each macro block as the pixel value after reduction.
Step 406: the pixel value of each macro block after reduction is summarized into the image after being decompressed and output.
It will be understood by those skilled in the art that the various illustrative methods here in conjunction with the disclosed embodiments description walk
Rapid and device unit can be realized with the combination of electronic hardware, software or both.In order to be clearly shown hardware and software it
Between interchangeability, the above description various illustrative steps and unit carried out in the form of its is functional generally.
This functionality be with hardware realization or the design implemented in software realized dependent on specific application and whole system about
Beam.Those skilled in the art can realize described function in many ways for each specific application, but this
The result that kind is realized should not be construed as away from the scope of the present invention.
Utilize general processor, digital signal processor (DSP), specific integrated circuit (ASIC), field-programmable gate array
Arrange (FPGA) either other programmable logical devices, discrete gate or transistor logic, discrete hardware components or they it
In any combination, may be implemented or execute in conjunction with embodiment disclosed herein description various illustrative units.General place
Managing device may be microprocessor, but in another scenario, the processor may be any conventional processor, controller,
Microcontroller or state machine.Processor may also be implemented as calculating the combination of equipment, for example, the group of DSP and microprocessor
Conjunction, multi-microprocessor, the microprocessor of one or more combination DSP cores or any other such structure.
The step of method in conjunction with described in embodiment disclosed above, can be embodied directly in hardware, by processor execution
Software module or the combination of both.Software module is likely to be present in RAM memory, flash memory, ROM memory, EPROM storage
The storage of device, eeprom memory, register, hard disk, mobile disk, CD-ROM or any other form well known in the art
In medium.A kind of exemplary storage medium is coupled with processor, so that processor can read information from the storage media, and
It can be to the storage media write information.In replacement example, storage media is the component part of processor.Processor and storage media
It is likely to be present in an ASIC.The ASIC is likely to be present in a subscriber station.In a replacement example, processor and deposit
Storage medium can be used as the presence of the discrete assembly in subscriber station.
According to the disclosed embodiment, those skilled in the art can be made to can be realized or using the present invention.It is right
For those skilled in the art, the various modifications of these embodiments are it will be apparent that and the general principles that define here
It can also be applied to other embodiments on the basis of not departing from the scope and spirit of the present invention.Embodiment described above is only
Presently preferred embodiments of the present invention is not intended to limit the invention, all within the spirits and principles of the present invention, made
What modification, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.
Claims (11)
1. a kind of compression method of hardware based adjustable lossy compression characterized by comprising
Piecemeal is carried out to the image of input, pixel mean value and the pixel for calculating each macro block are very poor；
When the pixel is very poor is greater than given threshold, each macro block is quantified, macroblock transform result parameter list is obtained；When
The pixel it is very poor be not more than the given threshold when, according to the pixel mean value be arranged the list of macroblock transform result parameter；
Obtain compression of images parameter list according to the macroblock transform result parameter list, to the list of described image compression parameters into
Row write is compressed to obtain compressed image file.
2. compression method as described in claim 1, which is characterized in that interactive interface shows that a variety of preset values are selected for user,
User selects one of preset value as given threshold according to the demand of picture quality.
3. compression method as described in claim 1, which is characterized in that it is described that each macro block is quantified, obtain each macro block
Transformation results parameter list specifically includes following sub-step:
Calculate quantization threshold and quantization scale list；
The macro block pixels deviation matrix quantified according to quantization scale list；
According to the macro block pixels deviation matrix of quantization, the pixel mean value of each macro block, quantization mark and quantization threshold, macro block is set
Transformation results parameter list.
4. compression method as claimed in claim 3, which is characterized in that the calculating quantization threshold specially calculates current macro
The difference of block pixel maximum and current macro block pixels mean value, and calculate current macro block pixels mean value and current macro block pixels most
The difference of small value, the maximum value of more above-mentioned two difference, using the maximum value of two differences as the quantization threshold of current macro.
5. compression method as claimed in claim 3, which is characterized in that calculate quantization scale list, specially setting is current macro
The specific range of multiple quantized intervals of block.
6. compression method as claimed in claim 5, which is characterized in that the macro block quantified according to quantization scale list
Pixel deviations matrix, specifically: default value group is set by the endpoint of multiple quantized intervals, is successively determined each in current macro
Pixel deviations value corresponding numerical value in the default value group, the quantizing pixel deviation of each position as current macro will
The quantizing pixel deviation of each position of current macro combines to obtain macro block pixels deviation matrix.
7. compression method as claimed in claim 3, which is characterized in that the macroblock transform result parameter list includes that pixel is equal
Value, quantization identify, effectively quantify the quantization threshold of macro block and the macro block pixels deviation matrix of quantization.
8. compression method as described in claim 1, which is characterized in that described to be obtained according to the macroblock transform result parameter list
To compression of images parameter list, specifically include:
According to macroblock transform result parameter list, summarize to obtain image transformation results parameter list；
Compression of images parameter list is calculated by image transformation results parameter list.
9. the compression method as described in any one of claim 1-8, which is characterized in that described image compression parameters list packet
Include pixel mean value a reference value, quantization threshold a reference value, effectively quantization macro block sum, coding bit wide list and coded information sequences.
10. a kind of decompression method of the hardware based adjustable lossy compression for such as claim 1-9, feature exist
In, comprising:
It is unziped it to obtain compression of images parameter list according to compressed image file；Compression of images parameter list is decoded
Obtain the transformation results parameter list of each macro block；
When the pixel in the transformation results parameter list of each macro block is very poor is greater than given threshold, also by each pixel value of current macro
It originally was that current macro block pixels mean value adds corresponding deviation；It is not more than when the pixel in the transformation results parameter list of each macro block is very poor
When given threshold, each pixel value of current macro is reduced to current macro block pixels mean value；
The pixel value of each macro block after reduction is summarized into the image after being decompressed and output.
11. decompression method as claimed in claim 10, which is characterized in that described to be decoded to compression of images parameter list
The transformation results parameter list of each macro block is obtained, specifically:
By the equal value sequence in pixel mean value a reference value and coded information sequences, the pixel mean value of each macro block is obtained；
By effectively quantifying the mark sequence in macro block sum and coded information sequences, the quantization mark of each macro block is obtained；
By the threshold series in quantization threshold a reference value and coded information sequences, the quantization threshold of each effective quantization macro block is obtained；
By the sequence of differences in quantization threshold and coded information sequences, the deviation value matrix quantified；
The pixel mean value of obtained each macro block, quantization are identified, the deviation square of the quantization threshold of effectively quantization macro block and quantization
Battle array combination obtains the transformation results parameter list of each macro block.
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