CN104243947B - Parallax estimation method and device - Google Patents
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Abstract
The present invention provides a kind of parallax estimation method and device, methods described comprise the following steps：Obtain and analyze the disparity vector field of encoded frame, obtain global disparity vector；The hunting zone of frame to be encoded is chosen in reference frame according to the global disparity vector；Coded frame is treated according to the hunting zone and carries out disparity estimation, obtains the disparity vector of frame to be encoded.Above-mentioned parallax estimation method and device, by the disparity vector field for obtaining and analyzing encoded frame, obtain global disparity vector, the hunting zone of frame to be encoded is chosen in reference frame according to global disparity vector, coded frame is treated according to hunting zone and carries out disparity estimation, obtain the disparity vector of frame to be encoded, reduced according to the disparity vector distribution trend of encoded frame and treat the hunting zone that coded frame carries out disparity estimation, reduce the amount of calculation of frame matching, so as to improve video coding efficiency.
Description
Technical field
The present invention relates to video compression technology, more particularly to a kind of parallax estimation method and device.
Background technology
According to the difference of prediction direction, the interframe estimation of the Video coding of multi-view point video can be divided into disparity estimation and fortune
Dynamic estimation, disparity estimation estimate that estimation is estimated for the interframe of time orientation for the interframe of viewpoint direction.
In order to obtain good interframe estimation effect, disparity estimation is needed to carrying out intensive search in the range of reference frame full frame
Rope, to find out accurate frame matching position.
However, due in frame of video data volume be continuously increased, cause the amount of calculation of traditional disparity estimation to be continuously increased,
Influence video coding efficiency.
The content of the invention
Based on this, it is necessary to for disparity estimation in Video coding amount of calculation it is high the problem of, there is provided one kind can be reduced
The parallax estimation method of amount of calculation.
In addition, it there is a need to the problem of amount of calculation for disparity estimation in Video coding is high, there is provided one kind can be reduced
The disparity estimation device of amount of calculation.
A kind of parallax estimation method, comprises the following steps：Obtain and analyze the disparity vector field of encoded frame, obtain the overall situation
Disparity vector；The hunting zone of frame to be encoded is chosen in reference frame according to the global disparity vector；According to the search model
Enclose and disparity estimation is carried out to the frame to be encoded, obtain the disparity vector of the frame to be encoded.
It is described to obtain and analyze the disparity vector field of encoded frame in a wherein example, obtain global disparity vector
The step of include：Obtain the disparity vector of each macro block of the encoded frame with disparity estimation；Obtain the disparity vector
Average value, using the average value as the global disparity vector.
In a wherein example, the search for choosing frame to be encoded in reference frame according to the global disparity vector
The step of scope, includes：Set according to the global disparity vector in frame to be encoded in each search of the macro block in reference frame
The heart；Choose the hunting zone of each macro block in the reference frame according to the search center and preset search width.
It is described that disparity estimation is carried out to the frame to be encoded according to the hunting zone in a wherein example, obtain
Also comprise the following steps after the step of disparity vector of the frame to be encoded：According to the obtained disparity vector to described complete
Office's disparity vector is modified；Disparity estimation is carried out according to revised global disparity vector.
In a wherein example, the disparity vector obtained described in the basis enters to the global disparity vector
Row amendment the step of be：Whether judge the previous frame of video of present frame has carry out disparity estimation；If so, then according to formulaThe global disparity vector is repaiied
Just, wherein GPV is global disparity vector, and the update times that i is GPV index, and APV is that the mean parallax of present frame is vectorial, Alpha
For the time domain weights factor.
A kind of disparity estimation device, including：Acquisition module, for obtaining and analyzing the disparity vector field of encoded frame, obtain
To global disparity vector；Selecting module, for choosing the search of frame to be encoded in reference frame according to the global disparity vector
Scope；Estimation module, for carrying out disparity estimation to the frame to be encoded according to the hunting zone, obtain the frame to be encoded
Disparity vector.
In a wherein example, the acquisition module is additionally operable to obtain each grand of the encoded frame with disparity estimation
The disparity vector of block, the average value of the disparity vector is calculated, using the average value as the global disparity vector.
In a wherein example, the selecting module includes：Setup unit, for being set according to the global disparity vector
Each search center of the macro block in reference frame in fixed frame to be encoded；Unit is chosen, for according to the search center and default
Search width chooses the hunting zone of each macro block in the reference frame.
In a wherein example, described device also includes：Correcting module, for the disparity vector pair obtained according to
The global disparity vector is modified；The estimation module is additionally operable to be estimated according to revised global disparity vector progress parallax
Meter.
In a wherein example, the correcting module includes：Judging unit, for judge present frame previous frame of video whether
There is carry out disparity estimation；Amending unit, for according to formula
The global disparity vector is modified, wherein GPV is global disparity vector, and the update times that i is GPV index, and APV is to work as
The mean parallax vector of previous frame, Alpha is the time domain weights factor.
Above-mentioned parallax estimation method and device, by obtaining and analyzing the disparity vector field of encoded frame, obtain the overall situation and regard
Difference vector, the hunting zone of frame to be encoded is chosen in reference frame according to global disparity vector, according to hunting zone to be encoded
Frame carries out disparity estimation, obtains the disparity vector of frame to be encoded, is reduced pair according to the disparity vector distribution trend of encoded frame
Frame to be encoded carries out the hunting zone of disparity estimation, reduces the amount of calculation of frame matching, so as to improve Video coding
Efficiency.
Brief description of the drawings
Fig. 1 is a kind of parallax estimation method schematic flow sheet in an example；
Fig. 2 is a kind of parallax estimation method schematic flow sheet in another example；
Fig. 3 is a kind of parallax estimation method schematic flow sheet in another example；
Fig. 4 is a kind of disparity estimation apparatus structure schematic diagram in an example；
Fig. 5 is a kind of disparity estimation apparatus structure schematic diagram in another example；
Fig. 6 is a kind of disparity estimation apparatus structure schematic diagram in another example；
Fig. 7 is a kind of disparity estimation apparatus structure schematic diagram in another example.
Embodiment
The technical scheme of parallax estimation method and device is described in detail with reference to specific example and accompanying drawing,
So that it is clearer.
As shown in figure 1, in an example, a kind of parallax estimation method, including step S110, S130 and S150.Wherein,
Step S110, obtain and analyze the disparity vector field of encoded frame, obtain global disparity vector.
In this example, multi-view point video comprises at least 2 viewpoints, i.e. left view point and right viewpoint, is clapped simultaneously corresponding to two
Take the photograph the video camera of video pictures.Encoded frame has calculated the disparity vector of each macro block and carried out according to the disparity vector
The frame of video of data compression, disparity vector field are that the distribution that disparity vector corresponding to all macro blocks is formed in a frame of video becomes
Gesture, the vector data for extracting the trend form global disparity vector.Due to having certain phase between the consecutive frame of time orientation
Guan Xing, so disparity vector field also has certain correlation, so being obtained according to the corresponding trend analysis of disparity vector field
Global disparity vector have more accuracy.The disparity vector characteristic of each macro block, institute are combined additionally, due to global disparity vector
To have more robustness.
Specifically, it can be calculated every by the disparity vector for each macro block for obtaining the encoded frame with disparity estimation
The average value of the disparity vector of one macro block is as global disparity vector.In the frame of video of a viewpoint of time orientation, warp is obtained
An encoded frame of disparity estimation is crossed, obtains the disparity vector of each macro block in the frame, calculates all disparity vectors in the frame
Average vector describes the frame disparity vector field, and using the average vector as global disparity vector.Macro block in frame of video can be with
It is an equal amount of image block, a frame of video is such as divided into 16*16 fritter, method of partition is simple, and amount of calculation is small；Other video
The macro block of frame can also be gray scale neighborhood or characteristic block, and gray scale neighborhood refers to there is same grayscale feature based on pixel
Matching unit, characteristic block refer to the macro block table of the obvious line of grey scale change, face or structure in image, gray scale field or characteristic block
Show method due to carrying out piecemeal according to characteristics of image, so the description to frame of video is more accurate.Calculate being averaged for disparity vector
Value, amount of calculation is small, simple and fast.
Step S130, the hunting zone of frame to be encoded is chosen in reference frame according to global disparity vector.
In this example, reference frame is parallel in time with the frame of video of current view point in the frame of video of another viewpoint
The adjacent video frames of frame, i.e. viewpoint direction, can be encoded frame or uncoded frame.Because global disparity vector is retouched
The overall parallax trend between viewpoint direction consecutive frame has been stated, so compare for consecutive frame all images data area, it is global
Disparity vector can reduce hunting zone of the frame to be encoded in reference frame, and the hunting zone is that each macro block exists in frame to be encoded
The region scope of matched position in reference frame.Due to reducing hunting zone, it is possible to reduce data amount of calculation.
Specifically, as shown in Fig. 2 the hunting zone of frame to be encoded is chosen as follows：
Step S131, each search center of the macro block in reference frame in frame to be encoded is set according to global disparity vector.
Reference frame and frame to be encoded are placed in identical reference frame, obtain the relative position of frame and reference frame to be encoded, then
Correspondence position of each macro block in reference frame is obtained according to global disparity vector, using the correspondence position as search center.
Step S133, the hunting zone of each macro block is chosen in reference frame according to search center and preset search width.
Default search width is added on the basis of the image-region of the heart in the search, the preset search width can be a length along path
The width of a degree either macro block, i.e., re-extend search center periphery to the region of default line segment length, or by macro block
Periphery extends out to the position of a macroblock size as hunting zone corresponding to each macro block.It is true by global disparity vector
Determine search center, by preset search width limit search scope, due to hunting zone preset it is adjustable, it is possible to neatly adjust
Whole amount of calculation, improve efficiency and improve accuracy rate.
Step S150, coded frame is treated according to hunting zone and carries out disparity estimation, obtains the disparity vector of frame to be encoded.
In this example, due to each macroblock search scope in frame to be encoded is determined by global disparity vector, so
The matched position of the macro block is searched in hunting zone corresponding to each macro block, such as passes through method or base based on region
Disparity estimation is carried out in method of feature etc., the disparity vector of each macro block is calculated, so as to obtain the disparity vector of frame to be encoded.
Above-mentioned parallax estimation method, by obtaining and analyzing the disparity vector field of encoded frame, global disparity vector is obtained,
The hunting zone of frame to be encoded is chosen in reference frame according to global disparity vector, treating coded frame according to hunting zone is regarded
Difference estimation, obtains the disparity vector of frame to be encoded, is reduced according to the disparity vector distribution trend of encoded frame and treat coded frame
The hunting zone of disparity estimation is carried out, reduces the amount of calculation of frame matching, so as to improve video coding efficiency.
As shown in figure 3, in an example, also comprise the following steps after above-mentioned steps S150：
Step S170, global disparity vector is modified according to resulting disparity vector.
In this example, disparity estimation is carried out due to treating coded frame according to encoded frame, the frame to be encoded has become
Encoded frame, the disparity vector field formed by the disparity vector obtained by disparity estimation are also changed, so needing
Global disparity vector is modified, increases the accuracy of global disparity vector.
Specifically, in first judging the coded frame of current view point, whether the previous frame of video of present frame has carry out disparity estimation,
If it is not, need not be then updated to global disparity vector, i.e., existing global disparity vector is still effective.
If so, then according to formulaTo the overall situation
Disparity vector is modified, and wherein GPV is global disparity vector, and the update times that i is GPV index, and APV is being averaged for present frame
Disparity vector, Alpha are the time domain weights factor.If former frame has parallax prediction, i.e., have in the coded data of previous frame of video
Disparity vector field, if calculating global disparity vector first, then calculate its mean parallax vector and be used as global disparity vector, it is right
Answer i=0 situation；If existing global disparity vector, according to formula Alpha*GPV (i-1)+(1-Alpha) * APV (i) to complete
Office's disparity vector is modified renewal, i.e., can be calculated in the existing global disparity vector of consideration consideration and present frame complete
Office's disparity vector draws new global disparity vector, and wherein Alpha is less than 1 positive number, and rule of thumb Alpha can be
0.35。
Step S190, disparity estimation is carried out according to revised global disparity vector.
In this example, disparity estimation is carried out to new frame to be encoded according to new global disparity vector, similar step S150,
Simply global disparity vector has been updated over, and such as in the adjacent frame of video of time orientation, the first frame is entered according to traditional method
Row disparity estimation, the disparity vector field of the first frame is obtained, global disparity vector is obtained according to the disparity vector field of the first frame, according to
Global disparity vector carries out disparity estimation to the second frame, the disparity vector field of the second frame is obtained, according to the disparity vector of the second frame
Field amendment global disparity vector, obtains revised disparity vector, the 3rd frame is regarded according to revised disparity vector field
By that analogy, follow-up frame of video carries out disparity estimation according to revised global disparity vector for difference prediction ... ....The overall situation is regarded
Difference vector is updated the temporal correlation for considering global disparity vector, and global disparity vector is weighted from time orientation, subtracts
Lack the departure degree between true disparity vector, improve the accuracy of disparity estimation.
As shown in figure 4, in an example, a kind of disparity estimation device, including acquisition module 110, the and of selecting module 130
Estimation module 150.Wherein,
Acquisition module 110, for obtaining and analyzing the disparity vector field of encoded frame, obtain global disparity vector.
In this example, multi-view point video comprises at least 2 viewpoints, i.e. left view point and right viewpoint, is clapped simultaneously corresponding to two
Take the photograph the video camera of video pictures.Encoded frame has calculated the disparity vector of each macro block and carried out according to the disparity vector
The frame of video of data compression, disparity vector field are that the distribution that disparity vector corresponding to all macro blocks is formed in a frame of video becomes
Gesture, the vector data for extracting the trend form global disparity vector.Due to having certain phase between the consecutive frame of time orientation
Guan Xing, so disparity vector field also has certain correlation, so being obtained according to the corresponding trend analysis of disparity vector field
Global disparity vector have more accuracy.The disparity vector characteristic of each macro block, institute are combined additionally, due to global disparity vector
To have more robustness.
Specifically, acquisition module 110 is additionally operable to regarding for each macro block by obtaining the encoded frame with disparity estimation
Difference vector, the average value of disparity vector of each macro block is calculated as global disparity vector.Regarded in a viewpoint of time orientation
In frequency frame, acquisition module 110 obtains the encoded frame Jing Guo disparity estimation, obtains the disparity vector of each macro block in the frame,
The average vector for calculating all disparity vectors in the frame describes the frame disparity vector field, and using the average vector as global disparity
Vector.Macro block in frame of video can be an equal amount of image block, and a frame of video is such as divided into 16*16 fritter, piecemeal side
Method is simple, and amount of calculation is small；The macro block of other frame of video can also be gray scale neighborhood or characteristic block, and gray scale neighborhood refers to be based on picture
The Matching unit with same grayscale feature of vegetarian refreshments, characteristic block refer to the obvious line of grey scale change, face or structure in image, ash
The macro block method for expressing of degree field or characteristic block according to characteristics of image due to carrying out piecemeal, so the description to frame of video is more
Accurately.The average value of disparity vector is calculated, amount of calculation is small, simple and fast.
Selecting module 130, for choosing the hunting zone of frame to be encoded in reference frame according to global disparity vector.
In this example, reference frame is parallel in time with the frame of video of current view point in the frame of video of another viewpoint
The adjacent video frames of frame, i.e. viewpoint direction, can be encoded frame or uncoded frame.Because global disparity vector is retouched
The overall parallax trend between viewpoint direction consecutive frame has been stated, so compare for consecutive frame all images data area, it is global
Disparity vector can reduce hunting zone of the frame to be encoded in reference frame, and the hunting zone is that each macro block exists in frame to be encoded
The region scope of matched position in reference frame.Due to reducing hunting zone, it is possible to reduce data amount of calculation.
Specifically, as shown in figure 5, selecting module 130 includes setup unit 131 and chooses unit 133.
Setup unit 131, for setting each macro block searching in reference frame in frame to be encoded according to global disparity vector
Suo Zhongxin.Reference frame and frame to be encoded are placed in identical reference frame, obtain the relative position of frame and reference frame to be encoded
Put, correspondence position of each macro block in reference frame is then obtained according to global disparity vector, using the correspondence position as search
Center.
Unit 133 is chosen, for choosing searching for each macro block in reference frame according to search center and preset search width
Rope scope.Default search width is added on the basis of the image-region of the heart in the search, the preset search width can be one
The width of an individual line segment length either macro block, i.e., re-extend search center periphery to the region of default line segment length, or
Macro block periphery is extended out to the position of a macroblock size as hunting zone corresponding to each macro block by person.Regarded by the overall situation
Difference vector determines search center, by preset search width limit search scope, due to hunting zone preset it is adjustable, it is possible to
Neatly Adjustable calculation amount, improve efficiency and improve accuracy rate.
Estimation unit 150, disparity estimation is carried out for treating coded frame according to hunting zone, obtains the parallax of frame to be encoded
Vector.
In this example, due to each macroblock search scope in frame to be encoded is determined by global disparity vector, so
The matched position of the macro block is searched in hunting zone corresponding to each macro block, such as passes through method or base based on region
Disparity estimation is carried out in method of feature etc., the disparity vector of each macro block is calculated, so as to obtain the disparity vector of frame to be encoded.
Above-mentioned disparity estimation device, by obtaining and analyzing the disparity vector field of encoded frame, global disparity vector is obtained,
The hunting zone of frame to be encoded is chosen in reference frame according to global disparity vector, treating coded frame according to hunting zone is regarded
Difference estimation, obtains the disparity vector of frame to be encoded, is reduced according to the disparity vector distribution trend of encoded frame and treat coded frame
The hunting zone of disparity estimation is carried out, reduces the amount of calculation of frame matching, so as to improve video coding efficiency.
As shown in fig. 6, in an example, said apparatus also includes correcting module 170, estimation module 150 is additionally operable to root
Disparity estimation is carried out according to revised global disparity vector.
Correcting module 170, for being modified according to resulting disparity vector to global disparity vector.
In this example, disparity estimation is carried out due to treating coded frame according to encoded frame, the frame to be encoded has become
Encoded frame, the disparity vector field formed by the disparity vector obtained by disparity estimation are also changed, so needing
Global disparity vector is modified, increases the accuracy of global disparity vector.
Specifically, as shown in fig. 7, correcting module 170 includes judging unit 171 and amending unit 173.
Judging unit 171, for judging in the coded frame of current view point, whether the previous frame of video of present frame has progress
Disparity estimation, if it is not, need not be then updated to global disparity vector, i.e., existing global disparity vector is still effective；If
It is then to notify amending unit 173.
Amending unit 173, for according to formula
Global disparity vector is modified, wherein GPV is global disparity vector, and the update times that i is GPV index, and APV is present frame
Mean parallax vector, Alpha is the time domain weights factor.If former frame has parallax prediction, i.e., the coded number of previous frame of video
There is disparity vector field in, if calculating global disparity vector first, then calculate its mean parallax vector and be used as global disparity
Vector, corresponding i=0 situation；If existing global disparity vector, according to formula Alpha*GPV (i-1)+(1-Alpha) * APV
(i) renewal is modified to global disparity vector, that is, considers to calculate in existing global disparity vector and present frame
The global disparity vector drawn draws new global disparity vector, and wherein Alpha is less than 1 positive number, and rule of thumb Alpha can
To be 0.35.
Estimation module 150 is additionally operable to carry out disparity estimation according to revised global disparity vector.
In this example, estimation module 150 carries out disparity estimation according to new global disparity vector to new frame to be encoded, such as
In the adjacent frame of video of time orientation, the first frame is to carry out disparity estimation according to traditional method, obtains the parallax of the first frame
Vector field, global disparity vector is obtained according to the disparity vector field of the first frame, and the second frame is regarded according to global disparity vector
Difference estimation, obtains the disparity vector field of the second frame, corrects global disparity vector according to the disparity vector field of the second frame, is corrected
Disparity vector afterwards, parallax prediction ... ... is carried out by that analogy to the 3rd frame according to revised disparity vector field, follow-up regards
Frequency frame carries out disparity estimation according to revised global disparity vector.Global disparity vector is updated and considers global disparity
The temporal correlation of vector, global disparity vector is weighted from time orientation, reduces the deviation between true disparity vector
Degree, improve the accuracy of disparity estimation.
Example described above only expresses the several embodiments of the present invention, and its description is more specific and detailed, but not
Therefore the limitation to the scope of the claims of the present invention can be interpreted as.It should be pointed out that come for one of ordinary skill in the art
Say, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to the protection of the present invention
Scope.Therefore, the protection domain of patent of the present invention should be determined by the appended claims.
Claims (8)
1. a kind of parallax estimation method, comprises the following steps：
Obtain and analyze the disparity vector field of encoded frame, obtain global disparity vector；
Reference frame and frame to be encoded are placed in identical reference frame, obtain the phase of the frame to be encoded and the reference frame
To position, set according to the global disparity vector in the frame to be encoded in each search of macro block in the reference frame
The heart, choose the hunting zone of each macro block in the reference frame according to the search center and preset search width；
Disparity estimation is carried out to the frame to be encoded according to the hunting zone, obtains the disparity vector of the frame to be encoded.
2. parallax estimation method according to claim 1, it is characterised in that described to obtain and analyze the parallax of encoded frame
Vector field, the step of obtaining global disparity vector, include：
Obtain the disparity vector of each macro block of the encoded frame with disparity estimation；
The average value of the disparity vector is obtained, using the average value as the global disparity vector.
3. parallax estimation method according to claim 1, it is characterised in that described to be treated according to the hunting zone to described
Coded frame carries out disparity estimation, also comprises the following steps after the step of obtaining the disparity vector of the frame to be encoded：
The global disparity vector is modified according to the obtained disparity vector；
Disparity estimation is carried out according to revised global disparity vector.
4. parallax estimation method according to claim 3, it is characterised in that the disparity vector pair obtained described in the basis
The step of global disparity vector is modified be：
Whether judge the previous frame of video of present frame has carry out disparity estimation；
If so, then according to formulaTo the overall situation
Disparity vector is modified, wherein, GPV is global disparity vector, and the update times that i is GPV index, and APV is the flat of present frame
Equal disparity vector, Alpha are the time domain weights factor.
A kind of 5. disparity estimation device, it is characterised in that including：
Acquisition module, for obtaining and analyzing the disparity vector field of encoded frame, obtain global disparity vector；
Selecting module, the selecting module include setup unit and choose unit, and the setup unit is used for reference frame and treated
Coded frame is placed in identical reference frame, the relative position of the frame to be encoded and the reference frame is obtained, according to described
Global disparity vector sets each search center of macro block in the reference frame in the frame to be encoded, and the selection unit is used
In the hunting zone for choosing each macro block in the reference frame according to the search center and preset search width；
Estimation module, for carrying out disparity estimation to the frame to be encoded according to the hunting zone, obtain the frame to be encoded
Disparity vector.
6. disparity estimation device according to claim 5, it is characterised in that the acquisition module is additionally operable to obtain to have and regarded
The disparity vector of each macro block of the encoded frame of difference estimation, calculates the average value of the disparity vector, the average value is made
For the global disparity vector.
7. disparity estimation device according to claim 5, it is characterised in that described device also includes：
Correcting module, the disparity vector for being obtained according to are modified to the global disparity vector；
The estimation module is additionally operable to carry out disparity estimation according to revised global disparity vector.
8. disparity estimation device according to claim 7, it is characterised in that the correcting module includes：
Whether judging unit, the previous frame of video for judging present frame have carry out disparity estimation；
Amending unit, for according to formulaTo institute
State global disparity vector to be modified, wherein GPV is global disparity vector, and the update times that i is GPV index, and APV is present frame
Mean parallax vector, Alpha is the time domain weights factor.
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