CN107181943A - A kind of satellite sequence Lossless Image Compression Algorithm method and system based on Mixed Entropy Coding - Google Patents
A kind of satellite sequence Lossless Image Compression Algorithm method and system based on Mixed Entropy Coding Download PDFInfo
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- H—ELECTRICITY
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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
- H04N19/102—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
- H04N19/103—Selection of coding mode or of prediction mode
- H04N19/107—Selection of coding mode or of prediction mode between spatial and temporal predictive coding, e.g. picture refresh
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- 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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- 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
- H04N19/13—Adaptive entropy coding, e.g. adaptive variable length coding [AVLC] or context adaptive binary arithmetic coding [CABAC]
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- H04N19/20—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using video object coding
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Abstract
The invention discloses a kind of satellite sequence Lossless Image Compression Algorithm method and system based on Mixed Entropy Coding, belong to Image Compression field.The inventive method inputs present frame and reference frame image first, from two kinds of predictive modes：Inter prediction and infra-frame prediction obtain prediction residual.Then prediction residual is mapped to non-negative region, finally devise the mixed self-adapting arithmetic coding based on arithmetic coding and block code, according to the distribution character of residual error data, arithmetic coding and block code are respectively adopted to different pieces of information, finally coding result is integrated and exported.The invention also achieves a kind of satellite sequence Lossless Image Compression Algorithm system based on Mixed Entropy Coding.Technical solution of the present invention can be according to sequence image spatial redundancy and time redundancy characteristic automatic switchover predictive mode, so that predicted pixel values are closer to actual value, the entropy coder that the present invention is designed simultaneously has more preferable coding efficiency, significantly improves Lossless Image Compression Algorithm ratio.
Description
Technical field
The invention belongs to Image Compression field, more particularly, to a kind of satellite sequence based on Mixed Entropy Coding
Lossless Image Compression Algorithm method and system.
Background technology
Remote sensing technology plays very important effect in terms of military surveillance, environmental monitoring, management of earth resources, special
Be not remote sensing images have intuitively, informative the characteristics of.With the development of space technology, particularly space military technology
Development, higher requirement is proposed to space remote sensing, mainly carrying including image resolution ratio, spectral resolution and temporal resolution
Height, causes star epigraph data volume to ramp.And view data is sent to ground in real time from space, it is most of satellite
Main task.In some application fields, it is necessary to which Lossless Compression, therefore, faces the sharp increase of space remote sensing view data, need one kind badly
Lossless compression method with more high compression performance.
View data not only spatially has certain correlation, and with the raising of frame frequency, there is also redundancy in time.
In lossless compression method, the redundancy of room and time is not only solved, coding redundancy is also solved, comprehensive both could improve
Lossless Compression performance.
Current existing Lossless Compression standard such as JPEG-LS, JPEG2000, JPEG etc. or pertinent literature, are solving space
During with time redundancy or computation complexity is higher, it is impossible to adapt to the limited defect of computing resource on star, or nothing can not be realized
Damage compression；For coding, it is impossible to give full play to the performance of encryption algorithm, so also to there is certain information superfluous for the result after coding
It is remaining.Therefore, a kind of complementary lossless compression method is needed badly in terms of predicting and encoding two.
The content of the invention
For the disadvantages described above or Improvement requirement of prior art, the invention provides a kind of satellite based on Mixed Entropy Coding
Sequence image lossless compression method and system, its object is to cut automatically according to sequence image spatial redundancy and time redundancy characteristic
Infra-frame prediction and inter-frame forecast mode are changed, and is encoded using ADAPTIVE MIXED entropy code, existing star epigraph is thus solved
Compression algorithm complexity height and the high technical problem of information redundance in compress technique.
To achieve the above object, according to one aspect of the present invention, there is provided a kind of satellite sequence based on Mixed Entropy Coding
Row Lossless Image Compression Algorithm method and system, this method includes：
(1) gradient calculation：Input picture, determines whether reference frame, if without reference to frame, calculating input pixel periphery
Frame in gradient between pixel two-by-two, into step (3)；Otherwise input pixel peripheral image vegetarian refreshments and reference frame respective pixel are calculated
The frame in gradient of interframe gradient and the pixel of calculating input simultaneously between point；
(2) inter prediction and amendment：If interframe gradient absolute value and less than given threshold if utilize interframe gradient and ginseng
Examine frame respective pixel prediction input point pixel and obtain predicted value, and quantify interframe gradient and predicted value is modified；Otherwise enter
Step (3)
(3) infra-frame prediction and amendment：Predicted value is obtained using pixel neighboring pixel prediction input point pixel is inputted, and is measured
Change frame in gradient to be modified predicted value；
(4) residual values are calculated and handled：Input pixel value subtracts prediction and is worth to residual values, and residual values are limited in into default model
In enclosing, re-map non-negative region and obtain mapping value mapErrVal；
(5) Mixed Entropy Coding：Probability initialization, granny rag Lars point are carried out to interval [0, Th] using the distribution of granny rag Lars
Cloth：
Arithmetic coding initialization probability model is obtained, wherein, P (t) is probability, and σ is the distributed constant of setting, and Th is setting
Value；If mapErrVal ∈ [0, Th], then carry out arithmetic coding according to probabilistic model afterwards, and by whole byte polishing coding result,
Then use mapErrVal update probabilistic models；If mapErrVal ∈ (Th, MAXVAL], then fixed length volume is carried out to mapErrVal
Code；Finally coding result is integrated and exported.
Further, the step (1) specifically includes：
(11) input picture, determines whether reference frame, if without reference to frame, into step (12)；Otherwise step is entered
Suddenly (13)；
(12) the frame in gradient of input pixel is calculated,
Wherein, P9, P3, P8 and P2 are adjacent two-by-two, and P3 and P2 are adjacent with input pixel side, P9 and P8 and input pixel
Angle is adjacent, into step (3)；
(13) calculate frame in gradient and calculate the interframe gradient of input pixel simultaneously, interframe gradient is：
Wherein, P5, P4 and P10 be reference frame in and P3, P2 and P8 corresponding pixel points.
Further, the step (2) includes：
(21) judge (| D4 |+| D5 |+| D6 |) whether≤T1 set up, wherein, T1 is prediction threshold value；If then entering step
(22)；Otherwise step (3) is entered；
(22) predicted value of the input pixel is：
Wherein,For predicted value, P1 is pixel value of the input pixel in reference frame corresponding points；
(23) calculate G (inter)=| D4 |+| D5 |+| D6 |, G (inter) is quantified as 10 in interval [0, MAXVAL]
Individual grade, that is, set 10 context models to predicted valueIt is modified, wherein MAXVAL is the maximum of input picture gray scale
Value, afterwards into step (4).
Further, the step (3) includes：
(31) predicted value is：
(32) D1, D2 and D3 are carried out quantifying to obtain context index value, predicted value carried out by context index value
Amendment.
Further, the step (4) includes：
(41) the prediction residual value of input pixel is calculatedP is input picture point pixel value；
(42) if errVal<0, then update errVal=errVal+RANGE；Judge again errVal >=((RANGE+1)/
2) whether set up, be, update errVal=errVal-RANGE, wherein, RANGE=MAXVAL+1；
(43) errVal is mapped to non-negative region, mapping value is：
It is another aspect of this invention to provide that there is provided a kind of satellite sequence Lossless Image Compression Algorithm system based on Mixed Entropy Coding
System, the system includes：
Gradient calculation module, for input picture, determines whether reference frame, if without reference to frame, calculating input picture
The frame in gradient of plain periphery two-by-two between pixel, into infra-frame prediction and correcting module；Otherwise input pixel neighboring pixel is calculated
The frame in gradient of interframe gradient and the pixel of calculating input simultaneously between point and reference frame corresponding pixel points；
Inter prediction and correcting module, for judging, if interframe gradient absolute value and less than given threshold, utilize frame
Between gradient and reference frame respective pixel prediction input point pixel obtain predicted value, and quantify interframe gradient predicted value repaiied
Just；Otherwise infra-frame prediction and correcting module are entered；
Infra-frame prediction and correcting module, for using input pixel neighboring pixel prediction input point pixel predicted
It is worth, and quantized frame inside gradient is modified to predicted value；
Residual values are calculated and processing module, are subtracted prediction for input pixel value and are worth to residual values, residual values are limited in
In preset range, re-map non-negative region and obtain mapping value mapErrVal；
Mixed Entropy Coding module, for carrying out probability initialization to interval [0, Th] using the distribution of granny rag Lars, granny rag is drawn
This distribution：
Arithmetic coding initialization probability model is obtained, wherein, P (t) is probability, and σ is the distributed constant of setting, and Th is setting
Value；If mapErrVal ∈ [0, Th], then carry out arithmetic coding according to probabilistic model afterwards, and by whole byte polishing coding result,
Then use mapErrVal update probabilistic models；If mapErrVal ∈ (Th, MAXVAL], then fixed length volume is carried out to mapErrVal
Code；Finally coding result is integrated and exported.
Further, the gradient calculation module is specifically included：
Reference frame judging unit, for input picture, determines whether reference frame, if without reference to frame, into frame in
Gradient calculation unit；Otherwise inter-frame inside gradient computing unit is entered；
Frame in gradient calculation unit, the frame in gradient for calculating input pixel,
Wherein, P9, P3, P8 and P2 are adjacent two-by-two, and P3 and P2 are adjacent with input pixel side, P9 and P8 and input pixel
Angle is adjacent, into infra-frame prediction and correcting module；
Inter-frame inside gradient computing unit, for calculating frame in gradient and while calculating the interframe gradient of input pixel, frame
Between gradient be：
Wherein, P5, P4 and P10 be reference frame in and P3, P2 and P8 corresponding pixel points.
Further, it is characterised in that the inter prediction and correcting module include：
Judging unit is predicted, for judging (| D4 |+| D5 |+| D6 |) whether≤T1 set up, wherein, T1 is prediction threshold value；
If then entering inter prediction unit；Otherwise infra-frame prediction and correcting module are entered；
Inter prediction unit, for calculating inter prediction value, the predicted value of the input pixel is：
Wherein,For predicted value, P1 is pixel value of the input pixel in reference frame corresponding points；
Inter prediction amending unit, for calculate G (inter)=| D4 |+| D5 |+| D6 |, in interval [0, MAXVAL]
G (inter) is quantified as 10 grades, that is, 10 context models are set to predicted valueIt is modified, wherein MAXVAL is
The maximum of input picture gray scale, enters residual values and calculates and processing module afterwards.
Further, the infra-frame prediction and correcting module include：
Intraprediction unit, for calculating intra prediction value, predicted value is：
Infra-frame prediction amending unit, for carrying out quantifying to obtain context index value to D1, D2 and D3, passes through context rope
Draw value to be modified predicted value.
Further, the residual values are calculated and processing module includes：
Residual computations unit, the prediction residual value for calculating input pixelP is input picture point
Pixel value；
Residual error limits unit, for residual values to be limited within a preset range, if errVal<0, then update errVal=
errVal+RANGE；Judge whether errVal >=((RANGE+1)/2) set up again, be to update errVal=errVal-
RANGE, wherein, RANGE=MAXVAL+1；
Residual error map unit, for errVal to be mapped into non-negative region, mapping value is：
In general, by the contemplated above technical scheme of the present invention compared with prior art, it is special with following technology
Levy and beneficial effect：
(1) present invention sets up space-time context and interframe and intra prediction value is carried out according to room and time redundancy properties
Amendment, enriches context environmental situation on the basis of JPEG-LS frame in contexts, optimizes forecast model so that prediction
Value is more nearly pixel actual value, a greater degree of to reduce room and time redundancy；
(2) the mixed self-adapting arithmetic coding based on arithmetic coding that the present invention is designed can preferably adapt to coded object
Distribution character, more plays the performance of arithmetic coding so that coding result improves Lossless Compression further to the entropy of information source
Than；
(3) according to the satellite sequence Lossless Image Compression Algorithm method proposed by the present invention based on Mixed Entropy Coding, can effectively it solve
Certainly star transmission bandwidth and big data quantity contradiction.While high compression ratio is obtained, implementation complexity can also meet and be counted on star
The requirement of calculation ability.
Brief description of the drawings
Fig. 1 is flow chart of the method for the present invention；
Fig. 2 diamond search algorithm schematic diagrames of the embodiment of the present invention；
Fig. 3 is the prediction module of interframe of the embodiment of the present invention and frame in；
Fig. 4 is granny rag Lars distribution schematic diagram；
Fig. 5 is that the embodiment of the present invention predicts value histogram；
Fig. 6 is the histogram after predicted value of the embodiment of the present invention maps；
Fig. 7 is mixed self-adapting arithmetic coding block diagram of the embodiment of the present invention.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.As long as in addition, technical characteristic involved in each embodiment of invention described below
Not constituting conflict each other can just be mutually combined.
As shown in figure 1, the present embodiment has following flow：
(1) gradient calculation：Input picture, determines whether reference frame, if without reference to frame, calculating input pixel periphery
The frame in gradient between pixel, into step (3), otherwise calculates input pixel peripheral image vegetarian refreshments and reference frame respective pixel two-by-two
The frame in gradient of interframe gradient and the pixel of calculating input simultaneously between point；
(11) input picture, determines whether reference frame, if without reference to frame, into step (12)；Otherwise step is entered
Suddenly (13)；The reference frame be present frame former frames in any one frame, preferably former frame, first in one group of image sequence
Frame is without reference to frame；
(12) the frame in gradient of input pixel is calculated,
Wherein, P9, P3, P8 and P2 are adjacent two-by-two, and P3 and P2 are adjacent with input pixel side, P9 and P8 and input pixel
Angle is adjacent, into step (3)；
(13) calculate frame in gradient and calculate the interframe gradient of input pixel simultaneously, interframe gradient is：
D4=P3-P5
D5=P2-P4
D6=P8-P10,
Wherein, P5, P4 and P10 be reference frame in and P3, P2 and P8 corresponding pixel points；The corresponding pixel points use Fig. 2
Shown diamond search method, the motion vector between adjacent two frame is calculated according to minimum absolute difference and criterion, and motion vector adds institute
Pixel point coordinates is selected to be designated as reference frame corresponding pixel points；By the prediction module of interframe of the embodiment of the present invention as shown in Figure 3 and frame in
Carry out gradient calculation.
(2) inter prediction and amendment：If interframe gradient absolute value and less than given threshold if utilize interframe gradient and ginseng
Examine frame respective pixel prediction input point pixel and obtain predicted value, and quantify interframe gradient and predicted value is modified；Otherwise enter
Step (3)；
(21) judge (| D4 |+| D5 |+| D6 |) whether≤T1 set up, wherein, T1 is prediction threshold value；If then entering step
(22)；Otherwise step (3) is entered；
(22) predicted value of the input pixel is：
Wherein,For predicted value, P1 is pixel value of the input pixel in reference frame corresponding points；
(23) calculate G (inter)=| D4 |+| D5 |+| D6 |, G (inter) is quantified as 10 in interval [0, MAXVAL]
Individual grade, that is, set 10 context models to predicted valueBe modified, wherein, MAXVAL be input picture gray scale most
Big value, afterwards into step (4).
(3) infra-frame prediction and amendment：Predicted value is obtained using pixel neighboring pixel prediction input point pixel is inputted, and is measured
Change frame in gradient to be modified predicted value；
(31) predicted value is：
(32) D1, D2 and D3 are carried out quantifying to obtain context index value, predicted value carried out by context index value
Amendment；It is illustrated in figure 4 the histogram that the present embodiment predicts value set.
(4) residual values are calculated and handled：Input pixel value subtracts prediction and is worth to residual values, and residual values are limited in into default model
In enclosing, re-map non-negative region and obtain mapping value mapErrVal；It is illustrated in figure 5 the mapping value of embodiment；
(41) the prediction residual value of input pixel is calculatedP is input picture point pixel value；
(42) if errVal<0, then update errVal=errVal+RANGE；Judge again errVal >=((RANGE+1)/
2) whether set up, be, update errVal=errVal-RANGE, wherein, RANGE=MAXVAL+1；
(43) errVal is mapped to non-negative region, mapping value is：
(5) Mixed Entropy Coding：As shown in fig. 6, embodiment mixed self-adapting arithmetic coding is specially：Utilize granny rag Lars point
Cloth carries out probability initialization to interval [0, Th], obtains arithmetic coding initialization probability model, granny rag Lars is distributed as：
It is illustrated in figure 7 the distribution curve of granny rag Lars distribution；Wherein, P (t) is probability, and σ is the distributed constant of setting,
Th is setting value；If mapErrVal ∈ [0, Th], then carry out arithmetic coding according to probabilistic model afterwards, and by whole byte polishing
Coding result, then uses mapErrVal update probabilistic models；If mapErrVal ∈ (Th, MAXVAL], then mapErrVal is entered
Row block code；Finally coding result is integrated and exported.
As it will be easily appreciated by one skilled in the art that the foregoing is merely illustrative of the preferred embodiments of the present invention, it is not used to
The limitation present invention, any modifications, equivalent substitutions and improvements made within the spirit and principles of the invention etc., it all should include
Within protection scope of the present invention.
Claims (10)
1. a kind of satellite sequence Lossless Image Compression Algorithm method based on Mixed Entropy Coding, it is characterised in that methods described include with
Lower step：
(1) gradient calculation：Input picture, determines whether reference frame, if without reference to frame, calculating input pixel periphery two-by-two
Frame in gradient between pixel, into step (3)；Otherwise calculate input pixel peripheral image vegetarian refreshments and reference frame corresponding pixel points it
Between interframe gradient and simultaneously calculate input pixel frame in gradient；
(2) inter prediction and amendment：If interframe gradient absolute value and less than given threshold, utilize interframe gradient and reference frame
Respective pixel prediction input point pixel obtains predicted value, and quantifies interframe gradient predicted value is modified；Otherwise step is entered
(3)；
(3) infra-frame prediction and amendment：Predicted value, and quantized frame are obtained using pixel neighboring pixel prediction input point pixel is inputted
Inside gradient is modified to predicted value；
(4) residual values are calculated and handled：Input pixel value subtracts prediction and is worth to residual values, and residual values are limited in into preset range
It is interior, re-map non-negative region and obtain mapping value mapErrVal；
(5) Mixed Entropy Coding：Probability initialization, the distribution of granny rag Lars are carried out to interval [0, Th] using the distribution of granny rag Lars：
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Arithmetic coding initialization probability model is obtained, wherein, P (t) is probability, and σ is the distributed constant of setting, and Th is setting value；
If mapErrVal ∈ [0, Th], then carry out arithmetic coding according to probabilistic model afterwards, and presses whole byte polishing coding result, with
MapErrVal update probabilistic models are used afterwards；If mapErrVal ∈ (Th, MAXVAL], then block code is carried out to mapErrVal；
Finally coding result is integrated and exported.
2. a kind of satellite sequence Lossless Image Compression Algorithm method based on Mixed Entropy Coding according to claim 1, its feature
It is, the step (1) specifically includes：
(11) input picture, determines whether reference frame, if without reference to frame, into step (12)；Otherwise step is entered
(13)；
(12) the frame in gradient of input pixel is calculated,
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Wherein, P9, P3, P8 and P2 are adjacent two-by-two, and P3 and P2 are adjacent with input pixel side, P9 and P8 and input pixel angle phase
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(13) calculate frame in gradient and calculate the interframe gradient of input pixel simultaneously, interframe gradient is：
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Wherein, P5, P4 and P10 be reference frame in and P3, P2 and P8 corresponding pixel points.
3. a kind of satellite sequence Lossless Image Compression Algorithm method based on Mixed Entropy Coding according to claim 2, its feature
It is, the step (2) includes：
(21) judge (| D4 |+| D5 |+| D6 |) whether≤T1 set up, wherein, T1 is prediction threshold value；If then entering step
(22)；Otherwise step (3) is entered；
(22) predicted value of the input pixel is：
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Wherein,For predicted value, P1 is pixel value of the input pixel in reference frame corresponding points；
(23) calculate G (inter)=| D4 |+| D5 |+| D6 |, G (inter) is quantified as 10 etc. in interval [0, MAXVAL]
Level, that is, set 10 context models to predicted valueIt is modified, wherein MAXVAL is the maximum of input picture gray scale,
Enter step (4) afterwards.
4. a kind of satellite sequence Lossless Image Compression Algorithm method based on Mixed Entropy Coding according to claim 3, its feature
It is, the step (3) includes：
(31) predicted value is：
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<mrow>
<mi>max</mi>
<mrow>
<mo>(</mo>
<mi>P</mi>
<mn>2</mn>
<mo>,</mo>
<mi>P</mi>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
<mtd>
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<mrow>
<mi>i</mi>
<mi>f</mi>
</mrow>
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<mrow>
<mi>P</mi>
<mn>8</mn>
<mo>&le;</mo>
<mi>min</mi>
<mrow>
<mo>(</mo>
<mi>P</mi>
<mn>2</mn>
<mo>,</mo>
<mi>p</mi>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
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</mtr>
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</mtd>
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<mi>P</mi>
<mn>2</mn>
<mo>+</mo>
<mi>P</mi>
<mn>3</mn>
<mo>-</mo>
<mi>P</mi>
<mn>8</mn>
</mrow>
</mtd>
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<mi>e</mi>
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</mtr>
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</mfenced>
<mo>;</mo>
</mrow>
(32) D1, D2 and D3 are carried out quantifying to obtain context index value, predicted value are modified by context index value.
5. a kind of satellite sequence Lossless Image Compression Algorithm method based on Mixed Entropy Coding according to claim 4, its feature
It is, the step (4) includes：
(41) the prediction residual value of input pixel is calculatedP is input picture point pixel value；
(42) if errVal<0, then update errVal=errVal+RANGE；Judging errVal >=((RANGE+1)/2) again is
It is no to set up, it is to update errVal=errVal-RANGE, wherein, RANGE=MAXVAL+1；
(43) errVal is mapped to non-negative region, mapping value is：
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>p</mi>
<mi>E</mi>
<mi>r</mi>
<mi>r</mi>
<mi>V</mi>
<mi>a</mi>
<mi>l</mi>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
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<mn>2</mn>
<mo>*</mo>
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<mi>r</mi>
<mi>r</mi>
<mi>V</mi>
<mi>a</mi>
<mi>l</mi>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>e</mi>
<mi>r</mi>
<mi>r</mi>
<mi>V</mi>
<mi>a</mi>
<mi>l</mi>
<mo>&GreaterEqual;</mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mo>-</mo>
<mn>2</mn>
<mo>*</mo>
<mi>e</mi>
<mi>r</mi>
<mi>r</mi>
<mi>V</mi>
<mi>a</mi>
<mi>l</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>e</mi>
<mi>l</mi>
<mi>s</mi>
<mi>e</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>.</mo>
</mrow>
6. a kind of satellite sequence Lossless Image Compression Algorithm system based on Mixed Entropy Coding, it is characterised in that the system includes：
Gradient calculation module, for input picture, determines whether reference frame, if without reference to frame, calculating input pixel week
The frame in gradient of side two-by-two between pixel, into infra-frame prediction and correcting module；Otherwise calculate input pixel peripheral image vegetarian refreshments and
The frame in gradient of interframe gradient and the pixel of calculating input simultaneously between reference frame corresponding pixel points；
Inter prediction and correcting module, for judging, if interframe gradient absolute value and less than given threshold, utilize interframe ladder
Spend and reference frame respective pixel prediction input point pixel obtains predicted value, and quantify interframe gradient and predicted value is modified；It is no
Then enter infra-frame prediction and correcting module；
Infra-frame prediction and correcting module, for using input pixel neighboring pixel prediction input point pixel obtain predicted value, and
Quantized frame inside gradient is modified to predicted value；
Residual values are calculated and processing module, are subtracted prediction for input pixel value and are worth to residual values, residual values are limited in default
In the range of, re-map non-negative region and obtain mapping value mapErrVal；
Mixed Entropy Coding module, for carrying out probability initialization, granny rag Lars point to interval [0, Th] using the distribution of granny rag Lars
Cloth：
<mrow>
<mi>P</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<msqrt>
<mrow>
<mn>2</mn>
<msup>
<mi>&sigma;</mi>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mfrac>
<mo>&CenterDot;</mo>
<mi>exp</mi>
<mrow>
<mo>(</mo>
<mfrac>
<mrow>
<mo>-</mo>
<mn>2</mn>
<mo>|</mo>
<mi>t</mi>
<mo>|</mo>
</mrow>
<msqrt>
<mrow>
<mn>2</mn>
<msup>
<mi>&sigma;</mi>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mfrac>
<mo>)</mo>
</mrow>
<mo>,</mo>
<mi>t</mi>
<mo>&Element;</mo>
<mo>&lsqb;</mo>
<mn>0</mn>
<mo>,</mo>
<mi>T</mi>
<mi>h</mi>
<mo>&rsqb;</mo>
<mo>,</mo>
</mrow>
Arithmetic coding initialization probability model is obtained, wherein, P (t) is probability, and σ is the distributed constant of setting, and Th is setting value；
If mapErrVal ∈ [0, Th], then carry out arithmetic coding according to probabilistic model afterwards, and presses whole byte polishing coding result, with
MapErrVal update probabilistic models are used afterwards；If mapErrVal ∈ (Th, MAXVAL], then block code is carried out to mapErrVal；
Finally coding result is integrated and exported.
7. a kind of satellite sequence Lossless Image Compression Algorithm system based on Mixed Entropy Coding according to claim 6, its feature
It is, the gradient calculation module is specifically included：
Reference frame judging unit, for input picture, determines whether reference frame, if without reference to frame, into frame in gradient
Computing unit；Otherwise inter-frame inside gradient computing unit is entered；
Frame in gradient calculation unit, the frame in gradient for calculating input pixel,
<mrow>
<mtable>
<mtr>
<mtd>
<mrow>
<mi>D</mi>
<mn>1</mn>
<mo>=</mo>
<mi>P</mi>
<mn>9</mn>
<mo>-</mo>
<mi>P</mi>
<mn>3</mn>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mi>D</mi>
<mn>2</mn>
<mo>=</mo>
<mi>P</mi>
<mn>3</mn>
<mo>-</mo>
<mi>P</mi>
<mn>8</mn>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mi>D</mi>
<mn>3</mn>
<mo>=</mo>
<mi>P</mi>
<mn>8</mn>
<mo>-</mo>
<mi>P</mi>
<mn>2</mn>
</mrow>
</mtd>
</mtr>
</mtable>
<mo>,</mo>
</mrow>
Wherein, P9, P3, P8 and P2 are adjacent two-by-two, and P3 and P2 are adjacent with input pixel side, P9 and P8 and input pixel angle phase
Neighbour, into infra-frame prediction and correcting module；
Inter-frame inside gradient computing unit, for calculating frame in gradient and while the interframe gradient of calculating input pixel, interframe ladder
Spend and be：
<mrow>
<mtable>
<mtr>
<mtd>
<mrow>
<mi>D</mi>
<mn>4</mn>
<mo>=</mo>
<mi>P</mi>
<mn>3</mn>
<mo>-</mo>
<mi>P</mi>
<mn>5</mn>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mi>D</mi>
<mn>5</mn>
<mo>=</mo>
<mi>P</mi>
<mn>2</mn>
<mo>-</mo>
<mi>P</mi>
<mn>4</mn>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mi>D</mi>
<mn>6</mn>
<mo>=</mo>
<mi>P</mi>
<mn>8</mn>
<mo>-</mo>
<mi>P</mi>
<mn>10</mn>
</mrow>
</mtd>
</mtr>
</mtable>
<mo>,</mo>
</mrow>
Wherein, P5, P4 and P10 be reference frame in and P3, P2 and P8 corresponding pixel points.
8. a kind of satellite sequence Lossless Image Compression Algorithm system based on Mixed Entropy Coding according to claim 7, its feature
It is, the inter prediction and correcting module include：
Judging unit is predicted, for judging (| D4 |+| D5 |+| D6 |) whether≤T1 set up, wherein, T1 is prediction threshold value；If
Then enter inter prediction unit；Otherwise infra-frame prediction and correcting module are entered；
Inter prediction unit, for calculating inter prediction value, the predicted value of the input pixel is：
<mrow>
<mover>
<mi>P</mi>
<mo>^</mo>
</mover>
<mi>x</mi>
<mo>=</mo>
<mi>P</mi>
<mn>1</mn>
<mo>+</mo>
<mfrac>
<mrow>
<mo>(</mo>
<mi>D</mi>
<mn>4</mn>
<mo>+</mo>
<mi>D</mi>
<mn>5</mn>
<mo>+</mo>
<mi>D</mi>
<mn>6</mn>
<mo>)</mo>
</mrow>
<mn>3</mn>
</mfrac>
<mo>,</mo>
</mrow>
Wherein,For predicted value, P1 is pixel value of the input pixel in reference frame corresponding points；
Inter prediction amending unit, for calculate G (inter)=| D4 |+| D5 |+| D6 |, by G in interval [0, MAXVAL]
(inter) 10 grades are quantified as, that is, 10 context models are set to predicted valueIt is modified, wherein MAXVAL is defeated
Enter the maximum of gradation of image, residual values are entered afterwards and are calculated and processing module.
9. a kind of satellite sequence Lossless Image Compression Algorithm system based on Mixed Entropy Coding according to claim 8, its feature
It is, the infra-frame prediction and correcting module include：
Intraprediction unit, for calculating intra prediction value, predicted value is：
<mrow>
<mover>
<mi>P</mi>
<mo>^</mo>
</mover>
<mi>x</mi>
<mo>=</mo>
<mfenced open = "{" close = "">
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<mtr>
<mtd>
<mrow>
<mi>min</mi>
<mrow>
<mo>(</mo>
<mi>P</mi>
<mn>2</mn>
<mo>,</mo>
<mi>P</mi>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
<mtd>
<mtable>
<mtr>
<mtd>
<mrow>
<mi>i</mi>
<mi>f</mi>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>P</mi>
<mn>8</mn>
<mo>&GreaterEqual;</mo>
<mi>max</mi>
<mrow>
<mo>(</mo>
<mi>P</mi>
<mn>2</mn>
<mo>,</mo>
<mi>P</mi>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
</mtr>
</mtable>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mi>max</mi>
<mrow>
<mo>(</mo>
<mi>P</mi>
<mn>2</mn>
<mo>,</mo>
<mi>P</mi>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
<mtd>
<mtable>
<mtr>
<mtd>
<mrow>
<mi>i</mi>
<mi>f</mi>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>P</mi>
<mn>8</mn>
<mo>&le;</mo>
<mi>min</mi>
<mrow>
<mo>(</mo>
<mi>P</mi>
<mn>2</mn>
<mo>,</mo>
<mi>p</mi>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
</mtr>
</mtable>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mi>P</mi>
<mn>2</mn>
<mo>+</mo>
<mi>P</mi>
<mn>3</mn>
<mo>-</mo>
<mi>P</mi>
<mn>8</mn>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>e</mi>
<mi>l</mi>
<mi>s</mi>
<mi>e</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>;</mo>
</mrow>
Infra-frame prediction amending unit, for carrying out quantifying to obtain context index value to D1, D2 and D3, passes through context index value
Predicted value is modified.
10. a kind of satellite sequence Lossless Image Compression Algorithm system based on Mixed Entropy Coding according to claim 9, its feature
It is, the residual values are calculated and processing module includes：
Residual computations unit, the prediction residual value for calculating input pixelP is input picture point pixel
Value；
Residual error limits unit, for residual values to be limited within a preset range, if errVal<0, then update errVal=errVal
+RANGE；Judge whether errVal >=((RANGE+1)/2) set up again, be to update errVal=errVal-RANGE, its
In, RANGE=MAXVAL+1；
Residual error map unit, for errVal to be mapped into non-negative region, mapping value is：
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>p</mi>
<mi>E</mi>
<mi>r</mi>
<mi>r</mi>
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<mi>l</mi>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mn>2</mn>
<mo>*</mo>
<mi>e</mi>
<mi>r</mi>
<mi>r</mi>
<mi>V</mi>
<mi>a</mi>
<mi>l</mi>
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</mtd>
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<mrow>
<mi>e</mi>
<mi>r</mi>
<mi>r</mi>
<mi>V</mi>
<mi>a</mi>
<mi>l</mi>
<mo>&GreaterEqual;</mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mo>-</mo>
<mn>2</mn>
<mo>*</mo>
<mi>e</mi>
<mi>r</mi>
<mi>r</mi>
<mi>V</mi>
<mi>a</mi>
<mi>l</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>e</mi>
<mi>l</mi>
<mi>s</mi>
<mi>e</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>.</mo>
</mrow>
4
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