CN103139554B - A kind of 3 D video Rate-distortion optimization method and optimization device - Google Patents

Abstract

The invention discloses a kind of 3 D video Rate-distortion optimization method to include: (1) uses texture information and side information combined calculation unicode rate；(2) texture information and side information combined calculation Combine distortion are used；(3) unicode rate is utilized to calculate associating rate distortion costs with Combine distortion；Described associating rate distortion costs is used for texture information and the combined coding of side information or the coding for side information.The invention also discloses a kind of 3 D video rate-distortion optimization device.Texture information in 3 D video and side information are joined together to carry out rate-distortion optimization by the present invention, texture information and the distortion performance potentiality in side information are fully excavated, improve the distortion performance of 3 D video compression, there is wide application and adaptability.

Description

A kind of 3 D video Rate-distortion optimization method and optimization device

Technical field

The present invention relates to the Encoder Optimization technology in a kind of coding and decoding video field, the particularly compressed encoding of 3 D video Rate-distortion optimization technology in technology.

Background technology

At present, joint video team (JVT, Joint Video Team) the H.264/AVC video compression standard generation formulated The state-of-the-art video image compression technology of table.Because which employs motion prediction based on rate-distortion optimization and model selection skill Art, and the video coding and decoding technology of other a series of advanced persons, the most H.264/AVC standard and other coding and decoding videos of same time Standard is compared outstanding distortion performance.Due to the excellent properties of rate-distortion optimization algorithm, its have become as one important Encoder Optimization technology, be widely applied in coding and decoding video field.

The method of conventional rate-distortion optimization is for calculating and optimizing Lagrange rate distortion costs function method.Select in mode On rate-distortion optimization as a example by, optimize process for search current coded unit, such as macro block, pattern, make following glug bright Day function is minimum:

J_T(k)=D (T, k)+λ R (T, k)

In above-mentioned function, J represents Lagrangian cost value；

T represents the elementary area of present encoding, such as current macro；

K is the coding mode of current coded unit, such as 8x8 pattern in frame；

D represents the distortion or its estimated value that current coded unit T k in mode brings when encoding；

R represents code check required when encoding for current coded unit T k in mode or its estimated value；

λ represents Lagrange multiplier, and in H.264/AVC standard, this value is determined by quantization parameter Qp.

Pattern k obtained through said process is in rate distortion sense optimum pattern, selects this pattern to make in coding For current coded unit coding mode in final code stream.That is, by the pattern that rate distortion costs is minimum, as rate-distortion optimization Result, be used for encoding.In some cases, optimization model is also likely to be the pattern that rate distortion costs is maximum.

Since the TV invention forties in 20th century, experienced by black-and-white television, color television and the numeral developed is high Definition television three phases, TV tech the most gradually develops to giant-screen, colorization, fine definition, multimedia direction.Three-dimensional TV (3DTV) has depth perception and telepresenc, it will makes spectators obtain third dimension to greatest extent and is subject to, thus will become and One new developing direction.Research to the compression coding technology of the 3 D video being applied to three-dimensional television is significant.

Texture information is i.e. the two-dimensional image sequence that currently used video camera obtains.Obtain texture information be one by three-dimensional Real world projects to the process of camera image plane.During this, the information of the third dimension is dropped so that only rely on stricture of vagina Reason information can not obtain all information of corresponding three-dimensional scenic.

Three-dimensional scenic is expressed, it is necessary to introduce the side information corresponding with texture information, to represent for perfect Three-dimensional information.It is, in general, that the resolution of each frame of side information is consistent with texture information or lower, and use gray-scale map Form, the gray value of each pixel characterizes the information such as degree of depth of this point in respective texture information.Utilize texture information and Corresponding side information and necessary camera parameters, can complete representation three-dimensional scenic.The most common supplementary letter Breath form is the depth information will expressed with gray value after the far and near information of corresponding point is direct or transformed on texture information.

Human eye produces third dimension and is based primarily upon binocular parallax (binocular parallax) and motion parallax (motion Parallax) two aspects.If using a device to make right and left eyes be respectively seen different anaglyphs, then will in brain Produce accurate three-dimensional body, and the location that this object is in the scene, here it is have the third dimension of the degree of depth.In order to reach this One effect, needs to utilize one or more pairs of texture and side information to generate corresponding single eye images respectively.

Under three-dimensional television applied environment, except the texture information via transmission, user side need to utilize benefit toward contact Fill information combined with texture information and synthesize the more virtual visual point image single eye images as confession spectators' viewing, to obtain preferably Three-dimensional sense is subject to.In three-dimensional television field, by different as being referred to as the projection of the three-dimensional scenic obtained under different cameras angle Visual point image；Here, video camera can be that reality exists, it is also possible to is virtual, the viewpoint under virtual video camera angle Image is referred to as virtual visual point image.For weighing the quality of 3 D video compressed encoding comprehensively, be considered as and assess may with Family end is decoded or the quality of each visual point image that is synthesized into.

On the other hand, be required for carrying out encoding after acquisition for the texture information of three-dimensional television and side information so as Channel.Fairly simple method is that texture information and side information are respectively with the existing coding techniques such as H.264/AVC Encode.In coding, texture information is carried out respectively with the rate-distortion optimization of side information, only considered coded views Image fault, and do not account for the virtual view distortion of synthesis；Only individually consider the coding code of texture information and side information Rate, and do not account for the optimization problem under the unicode rate of the two.

Therefore, the information consolidation of texture information in 3 D video and side information is used, both are combined Rate-distortion optimization, find under the rate distortion optimum meaning of virtual view distortion and texture and side information unicode rate texture and The optimization model of side information, can improve 3 d video encoding efficiency and final three-dimensional video-frequency viewing quality.

In existing 3 D video compressed encoding, the problem existing for rate-distortion optimization technology is as follows:

In three-dimensional television system, the texture information of 3 D video and side information have coordinated the table of three-dimensional scene information Reaching, only the two cooperating, is mutually matched, and could obtain the 3 D video display effect of optimum.But, existing rate distortion is excellent Change technology only accounts for texture information and side information respective rate distortion optimal cost when encoding 3 D video, and does not considers Texture information combines calculating and the optimization of rate distortion optimal cost with side information.

3 D video, in addition to transmission viewpoint, also needs to comprehensively utilize texture information at user side and obtains one with side information The virtual view video image information of series, shows preferably 3-D effect for three-dimensional display apparatus.Existing rate-distortion optimization Technology only accounts for transmitting the distortion of viewpoint when encoding 3 D video, and does not accounts for texture and complementary sequence regards in transmission The size of the distortion that the distortion of point may cause on more multiple views.Therefore in the angle that whole 3 D video is applied, existing Rate-distortion optimization method do not account for applying to the new composition of distortion during 3 d video encoding, be unable to this should It is issued to the optimal performance in rate distortion sense with environment.

In view of feature and the applied environment of 3 D video, the rate distortion considering texture information and side information is special Property, calculate and comprehensively weigh the encoder bit rate of texture information and side information and coded views that coding causes and virtual view Comprehensive distortion, and carry out comprehensive rate-distortion optimization on this basis, it is possible to obtain more fully rate more excellent than existing method Distortion coding efficiency.

Summary of the invention

An object of the present disclosure is to provide a kind of Rate-distortion optimization method for 3 D video.

A kind of 3 D video Rate-distortion optimization method, including: (1) uses texture information and the associating of side information combined calculation Code check；(2) texture information and side information combined calculation Combine distortion are used；(3) unicode rate is utilized to calculate with Combine distortion Associating rate distortion costs；Described associating rate distortion costs for texture information and the combined coding of side information or is believed for supplementing The coding of breath.

As preferably, described associating rate distortion costs refers to use connection for the combined coding of texture information and side information Close rate distortion costs and combine the coding mode determining texture information and side information；Determine in coding mode combining, by texture The combination of the N number of pattern in information coding mode and M pattern in side information coding mode is selected associating rate distortion generation The mode combinations that valency is optimum；Wherein: N is integer, 2 ＜=N ＜=K, K is the number of texture information coding mode；M is integer, 1 ＜=M ＜=L, L is the number of side information coding mode.

As preferably, described associating rate distortion costs refers to use connection for the combined coding of texture information and side information Close rate distortion costs and combine the optimization quantized value determining texture information and side information conversion coefficient；Conversion coefficient is determined combining Optimization quantized value in, by NL quantized value in texture information quantization of transform coefficients value and side information quantization of transform coefficients value In ML quantized value combination in select the quantized value combination that associating rate distortion costs is optimum；Wherein: NL is integer, 2 ＜= NL ＜=KL, KL is the number of texture information quantization of transform coefficients value to be selected；ML is integer, and 1 ＜=ML ＜=LL, LL is supplementary The number of information conversion coefficient quantization value to be selected.

As preferably, described unicode rate R_unionThe computational methods of (T, G) are R_union(T, G)=a_TR(T)+a_GR(G)；Its In: R_union(T, G) is unicode rate；T is texture information current coded unit；G is side information current coded unit；R (T) is Following one of both: (1) texture information current coded unit encoder bit rate；(2) texture information current coded unit encoder bit rate Estimated value；R (G) is following one of both: (1) side information current coded unit encoder bit rate；(2) side information present encoding In cell encoding rate estimation value；a_TFor real number, for texture information current coded unit encoder bit rate weighted value；a_GFor real number, for Side information current coded unit encoder bit rate weighted value.

As preferably, described Combine distortion D_unionThe computational methods of (T, G) areIts In: D_union(T, G) is Combine distortion；T is texture information current coded unit；G is side information current coded unit；D_i(T, G) it is distortion corresponding to target view i；b_iFor real number, for target view i weight；P=1,2 ... for target view number；I= 1,2 ... P is target view label.

As preferably, the distortion D that described target view i is corresponding_iThe computational methods of (T, G) are one of following four method: (1) the distortion D that described target view i is corresponding_iThe computational methods of (T, G) are D_i(T, G)=E (W_i(T, G), V_i(T ', G '))；Its In: D_i(T, G) is the distortion of target view i；T is texture information current coded unit；G is side information current coded unit； T ' is that texture information current coded unit is with the reconstruction coding unit obtained after present encoding parameter coding, decoding；G ' is supplementary Information current coded unit is with the reconstruction coding unit obtained after present encoding parameter coding, decoding；W_i(x, y) and V_i(x y) is profit The method obtaining viewpoint i respective image information with side information y with texture x；(x, y) for calculating the method for difference between x and y for E； (2) the distortion D that described target view i is corresponding_iThe computational methods of (T, G) are D_i(T, G)=F (T, T ', H (G, G '))；Wherein: D_i(T, G) it is the distortion of target view i；T is texture information current coded unit；G is side information current coded unit；T ' is texture letter Breath current coded unit is with the reconstruction coding unit obtained after present encoding parameter coding, decoding；G ' is side information present encoding Unit is with the reconstruction coding unit obtained after present encoding parameter coding, decoding；(x, y) for calculating the method for difference between x and y for H； (x, y, z) for utilizing side information coding distortion z to rebuild the method for difference between texture y after calculating texture x and coding for F；(3) institute State current coded unit and include the most described T of respective image of multiple viewpoint to be encoded by multiple T_jComposition, described G is by multiple G_j Composition, the distortion D that described target view i is corresponding_iThe computational methods of (T, G) areIts In: D_i(T, G) is the distortion that target view i is corresponding；T_jFor the corresponding unit to be encoded of texture information in viewpoint j to be encoded；G_jFor treating The corresponding unit to be encoded of side information in coded views j；D_{I, u}(T_j, G_j) for utilizing viewpoint j to be encoded to generate corresponding target view i Distortion corresponding to pixel u；c_{I, j, u}For real number, viewpoint j to be encoded during for calculating the Combine distortion of pixel u of target view i Weight；I=1,2 ... P is target view label；P=1,2 ... for target view number；J=1,2 ... Q is to be encoded regarding Piont mark；Q=1,2 ... for viewpoint number to be encoded；U=1,2 ... V is respective pixel piont mark；V=1,2 ... for right Answer pixel number；(4) the distortion D that described target view i is corresponding_iThe computational methods of (T, G) areWherein: D_i(T, G) is the distortion of target view i；Tt is texture information present encoding Unit and the most each coding unit；G is side information current coded unit；T ' be texture information current coded unit with The reconstruction coding unit obtained after present encoding parameter coding, decoding；G ' is that side information current coded unit is with present encoding The reconstruction coding unit obtained after parameter coding, decoding；N is pixel n in current coded unit；S is in current coded unit Sum of all pixels；(x, y) for calculating the method for difference between x and y for H；(x, y) for the method calculating sensitive factor for I.

As preferably, described side information is depth information.

As preferably, Combine distortion D_unionThe computational methods of (T, G) areWherein: D_union(T, G) is Combine distortion；T is texture information current coded unit；G is side information current coded unit；D_i(T, G) is The distortion that target view i is corresponding；b_iFor real number, for target view i weight；P=1,2 ... for target view number；I=1, 2 ... P is target view label.

As preferably, the distortion D that described target view i is corresponding_iThe computational methods of (T, G) are one of following four method: (1) the distortion D that described target view i is corresponding_iThe computational methods of (T, G) are D_i(T, G)=E (W_i(T, G), W_i(T ', G '))；Its In: D_i(T, G) is the distortion of target view i；T is texture information current coded unit；G is side information current coded unit； T ' is that texture information current coded unit is with the reconstruction coding unit obtained after present encoding parameter coding, decoding；G ' is supplementary Information current coded unit is with the reconstruction coding unit obtained after present encoding parameter coding, decoding；W_i(x, y) for utilizing texture x The method obtaining viewpoint i respective image information with side information y；(x, y) for calculating the method for difference between x and y for E；(2) described mesh The distortion D that mark viewpoint i is corresponding_iThe computational methods of (T, G) are D_i(T, G)=F (T, T ', H (G, G '))；Wherein: D_i(T, G) is mesh The distortion of mark viewpoint i；T is texture information current coded unit；G is side information current coded unit；T ' is that texture information is worked as Front coding unit is with the reconstruction coding unit obtained after present encoding parameter coding, decoding；G ' is side information present encoding list Unit is with the reconstruction coding unit obtained after present encoding parameter coding, decoding；(x, y) for calculating the function of difference between x and y for H； (x, y z) rebuild the function of difference between texture y for combining after side information coding distortion z calculates texture x and coding to F；(3) institute State current coded unit and include the most described T of respective image of multiple viewpoint to be encoded by multiple T_jComposition, described G is by multiple G_j Composition, the distortion D that described target view i is corresponding_iThe computational methods of (T, G) areWherein: D_i(T, G) is the distortion that target view i is corresponding；T_jFor the corresponding unit to be encoded of texture information in viewpoint j to be encoded；G_jFor waiting to compile The corresponding unit to be encoded of side information in code viewpoint j；D_{I, u}(T_j, G_j) for utilizing viewpoint j to be encoded to generate the picture of corresponding target view i The distortion that element u is corresponding；c_{I, j, u}For real number, the weight of viewpoint j to be encoded during for calculating the Combine distortion of pixel u of target view i； I=1,2 ... P is target view label；P=1,2 ... for target view number；J=1,2 ... Q is viewpoint label to be encoded； Q=1,2 ... for viewpoint number to be encoded；U=1,2 ... V is respective pixel piont mark；V=1,2 ... for corresponding pixel points Number；(4) the distortion D that described target view i is corresponding_iThe computational methods of (T, G) are Wherein: D_i(T, G) is the distortion of target view i；Tt is texture information current coded unit and the most each coding unit； G is side information current coded unit；T ' is that texture information current coded unit is to obtain after present encoding parameter coding, decoding Reconstruction coding unit；G ' is that side information current coded unit is compiled with the reconstruction obtained after present encoding parameter coding, decoding Code unit；N is pixel n in current coded unit；S is sum of all pixels in current coded unit；H (x, y) for calculate x Yu y it Between the function of difference；(x, y) for calculating the function of sensitive factor for I.

The present invention the second purpose is to provide a kind of 3 D video rate-distortion optimization device.

This device is by encoding and rebuilding module, unicode rate computing module, Combine distortion computing module, combine rate distortion generation Valency computing module, poll optimize module composition；Described coding needs texture information current coded unit with supplementary with rebuilding module Information current coded unit or one of both are as input, and are connected with unicode rate computing module, Combine distortion computing module, Described unicode rate computing module is connected with combining rate distortion costs computing module, and described Combine distortion computing module needs shooting Machine parameter is as input, and is connected with combining rate distortion costs computing module, and associating rate distortion costs computing module is excellent with poll Changing module to be connected, poll optimizes module and is connected with rebuilding module with coding, and exports optimized parameter；Described coding and reconstruction module For carrying out texture information and side information or the coding of one of both according to the coding parameter of input, and obtain rebuilding image, Described unicode rate computing module is used for calculating texture information and side information combined coding code check, and described Combine distortion calculates mould Block is for calculating the Combine distortion of texture information and side information, and described associating rate distortion costs computing module is used for utilizing associating Code check calculates associating rate distortion costs with Combine distortion, and poll optimizes module and is used for judging rate distortion costs and making optimization certainly Plan, when optimal conditions not yet meets, the setting of adjusting and optimizing parameter, when optimal conditions meets, by optimum coding parameter Output.

Present invention beneficial effect compared with prior art:

1, the texture information in 3 D video and side information join together to carry out rate-distortion optimization innovatively, use The unicode rate of texture information and side information is as the code check in rate-distortion optimization；Use distortion weighing and the work of target view For the distortion in rate-distortion optimization.

2, by associating rate-distortion optimization, texture information and the distortion performance potentiality in side information have fully been excavated, Improve the distortion performance of 3 D video compression.

3, by position and its weight of in present invention target view are adjusted flexibly, can obtain regarding for different three-dimensionals Frequently the rate-distortion optimization result under applied environment, therefore the present invention has wide application and adaptability.

Accompanying drawing explanation

Rate-distortion optimization method for 3 D video a kind of to the present invention with embodiment is made with device below in conjunction with the accompanying drawings Further illustrate.

Fig. 1 is a kind of 3 D video rate-distortion optimization device embodiment schematic diagram of the present invention；

Fig. 2 is a kind of 3 D video rate-distortion optimization device embodiment schematic diagram of the present invention；

Fig. 3 is a kind of 3 D video rate-distortion optimization device embodiment schematic diagram of the present invention；

Detailed description of the invention

The solution that the present invention be directed to the problem existing for 3 D video rate distortion and propose.

The embodiment of a kind of typical utilization 3 D video of the present invention rate-distortion optimization device is as it is shown in figure 1, by compiling Code and reconstruction module, unicode rate computing module, Combine distortion computing module, to combine rate distortion costs computing module, poll excellent Change module composition.Described coding is connected with unicode rate computing module, Combine distortion computing module with rebuilding module, unicode rate Computing module with combine rate distortion costs computing module be connected, Combine distortion computing module need camera parameters as input, And be connected with combining rate distortion costs computing module, associating rate distortion costs computing module optimizes module with poll and is connected, poll Optimize and be connected with rebuilding module with coding.Described coding is used for carrying out texture information according to the coding parameter of setting with rebuilding module With the Video coding of side information, described unicode rate computing module is used for calculating texture information and side information combined coding code Rate, described Combine distortion computing module, for calculating the Combine distortion of texture information and side information, described combines rate distortion generation Valency computing module is used for utilizing unicode rate to calculate associating rate distortion costs with Combine distortion, and poll optimizes module and is used for judging rate Distortion cost also makes Optimal Decision-making, when optimal conditions not yet meets, and the setting of adjusting and optimizing parameter, meet in optimal conditions Time, by optimum coding parameter output.In actual applications, the phase that the coding parameter of regulation and control and value thereof, coding module use Pass technology, unicode rate and the computational methods of Combine distortion, rate distortion requirement the concrete grammar such as setting can be according to reality Situation sweetly disposition.

Introduce the embodiment of several utilization a kind of 3 D video Rate-distortion optimization method of the present invention in detail below:

Example one:

This example describes a kind of 3 D video Rate-distortion optimization method, and coding unit is image block in this instance；Side information For depth information.First the current coded unit to texture information coding uses independent rate-distortion optimization algorithm from texture information The K kind pattern of coding selects the N kind pattern (wherein K ＞ N) of optimum, then uses associating Rate-distortion optimization method to compile from current The pattern of all permissions of the texture information coding mode of this N kind optimum of code unit and the depth information of current coded unit Various combinations are chosen texture information coding mode and the combination of encoding depth information pattern of optimum, and by the pattern of this optimum United application on the coding of the texture of current coded unit and the depth information of current coded unit；Above-mentioned rate of combining is lost In true optimization, the computational methods of unicode rate are R_union(T, G)=R (T)+R (G), wherein R (T) is the stricture of vagina of current coded unit Reason information is with code check during current examination pattern-coding, and R (G) is that the depth information of current coded unit is compiled with current institute die trial formula Code check during code；In the associating rate-distortion optimization of this example, target view number is set to 1, and the computational methods of Combine distortion are D_union(T, G)=D₁(T, G)=E (W₁(T, G), W₁(T ', G ')), wherein D_union(T, G) is Combine distortion, D₁(T, G) is target The distortion that viewpoint is corresponding, T is texture information current block, and G is depth information sequence current block, and T ' is that texture information current block is to work as The reconstructed block obtained after premode coding, decoding, G ' is that depth information sequence current block is to obtain after present mode coding, decoding Reconstructed block, W₁(x, y) for utilizing texture x and depth information y to obtain the virtual regarding generation side of target view respective image information Method, (x, y) for calculating the function of total square error between x and y for E；The computational methods combining rate distortion costs in this example are J= D_union(T, G)+λ R_union(T, G), wherein λ is a fixing global parameter.

Example two:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is image macro in this instance；Mend The information of filling is parallax information.Use associating rate-distortion optimization to complete optimization model to select；In optimization model selects, use texture The rate-distortion optimization algorithm of information consolidation uncoded parallax information information obtains optimum from the K kind pattern that texture information encodes N kind pattern (wherein K ＞=N), use parallax information independence rate-distortion optimization algorithm from the L kind pattern that parallax information encodes Obtaining optimum M kind pattern (wherein L ＞ M), wherein texture information rate-distortion optimization algorithm is in texture information independence rate distortion On the basis of optimized algorithm, the distortion to diverse location carries out different weightings and obtains, position include interior of articles, background, Object boundaries etc., the judgement of position utilizes analysis parallax information to obtain, optimum in texture N kind optimization model and parallax M kind The combination of pattern is used associating rate-distortion optimization choose the mode combinations of optimum, and optimum mode combinations is applied to texture And on the coding of parallax current macro；In associating rate-distortion optimization, the computational methods of unicode rate are R_union(T, G)= a_TR(T)+a_GR (G), wherein R (T) is the texture information current macro estimated value with present mode encoder bit rate, and R (G) is parallax Information sequence current macro is with present mode encoder bit rate, a_T, a_GFor real number, selected by texture information and parallax information respectively During several optimization model, calculated distortion meansigma methods determines；In associating rate-distortion optimization, target view number is set to 2, The computational methods of Combine distortion are $D_{\mathrm{union}}(T,G)=\underset{i=1}{\overset{2}{\mathrm{\Σ}}}0.5D_i(T,G)=\underset{i=1}{\overset{2}{\mathrm{\Σ}}}0.5E(W_i(T,G),V_i(T^{\′},G^{\′})),$ Wherein D_union (T, G) is Combine distortion, D_i(T, G) is the distortion that target view i is corresponding, and T is texture information current macro, and G is parallax information Sequence current macro, T ' is texture information current macro with the reconstruction macro block obtained after present mode coding, decoding, and G ' is parallax Information sequence current macro is with the reconstruction macro block obtained after present mode coding, decoding, W_i(x, y) for utilizing texture x and parallax Information y obtains the virtual regarding generation method, V of target view i respective image information_i(x, y) for utilizing texture x and parallax information y Obtaining the simplification projecting method of target view i respective image information, (x, y) for calculating the letter of total absolute value error between x and y for E Number；The computational methods of associating rate distortion costs are J=D_union(T, G)+λ R_union(T, G), wherein λ is according to coded quantization parameter The global parameter determined.

Example three:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is image block in this instance；Use Side information be depth information；Use associating rate-distortion optimization to complete optimization model to select；Use in optimization model selects Texture information is combined the rate-distortion optimization algorithm of uncoded depth information information and is obtained from the K kind pattern that texture information encodes Optimum N kind pattern (wherein K ＞=N), the rate-distortion optimization using depth information to combine uncoded texture information information is calculated Method obtains the M kind pattern (wherein L ＞ M) of optimum, wherein texture information rate-distortion optimization from the L kind pattern of encoding depth information Distortion D=D in algorithm₁(T, G)=E (W₁(T, G), W₁(T ', G)), D₁(T, G) is the distortion of target view 1 correspondence, and T is stricture of vagina Reason information current block, G is depth information sequence current block, and T ' is that texture information current block is to obtain after present mode coding, decoding The reconstructed block arrived, W₁(x, y) virtual the regarding for utilizing texture x and depth information y to obtain target view 1 respective image information generates Method, (x, y) for calculating the function of total square error between x and y for E；Distortion D=D in depth information rate-distortion optimization algorithm₁ (T, G)=E (W₁(T, G '), W₁(T, G)), D₁(T, G) is the distortion of target view 1 correspondence, and T is texture information current block, and G is Depth information sequence current block, T ' is that texture information current block is with the reconstructed block obtained after present mode coding, decoding, W₁(x, Y) for utilizing texture x and depth information y to obtain the virtual regarding generation method of target view 1 respective image information, (x, y) for meter for E Calculate the function of total square error between x and y；Associating is used in the combination of texture N kind optimization model and degree of depth M kind optimization model Rate-distortion optimization chooses the mode combinations of optimum, and optimum mode combinations is applied on the coding of texture and degree of depth current block； In associating rate-distortion optimization, the computational methods of unicode rate are R_union(T, G)=a_TR(T)+a_GR (G), wherein R (T) is texture letter Breath current block is with the estimated value of present mode encoder bit rate, and R (G) is that depth information sequence current block is with present mode encoder bit rate Estimated value, a_T, a_GFor real number, determined by the quantization parameter of texture information and depth information respectively；In associating rate-distortion optimization, mesh Mark viewpoint number is set to 3, and the computational methods of Combine distortion are $D_{\mathrm{union}}(T,G)=\underset{i=1}{\overset{2}{\mathrm{\Σ}}}{b}_i{D}_i(T,G)=\underset{i=1}{\overset{2}{\mathrm{\Σ}}}{b}_{i}E(W_i(T,G),V_i(T^{\′},G^{\′})),$ Wherein D_union(T, G) is Combine distortion, D_i(T, G) is the distortion that target view i is corresponding, and T is texture information current block, and G is deep Degree information sequence current block, T ' is texture information current block with the reconstructed block obtained after present mode coding, decoding, and G ' is the degree of depth Information sequence current block is with the reconstructed block obtained after present mode coding, decoding, W_i(x, y) and V_i(x y) respectively utilizes texture X and depth information y obtains different virtual regarding generation method of two kinds of target view i respective image information, and (x, y) for calculating x for E And the function of average every pixel square error, b between y_iFor real number, for target view i weight, target view i regard with coding Between point, parallax size determines；The computational methods of associating rate distortion costs are J=D_union(T, G)+λ R_union(T, G), wherein λ is root Code check and distortion dynamics adjustment according to encoded sequence.

Example four:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is image block in this instance；Use Side information be depth information；Use associating rate-distortion optimization to complete optimization model to select；In optimization model selects, use The rate-distortion optimization algorithm of texture information independence obtains N kind pattern (the wherein K of optimum from the K kind pattern that texture information encodes ＞=N), use associating rate-distortion optimization to choose the mould of optimum in the combination of texture N kind optimization model and all patterns of the degree of depth Formula combines, and optimum mode combinations is applied on the coding of texture and degree of depth current block；In associating rate-distortion optimization, The computational methods of unicode rate are R_union(T, G)=R (T)+R (G), wherein R (T) is that texture information current block is compiled with present mode Code code check, R (G) is that depth information sequence current block is with present mode encoder bit rate；In associating rate-distortion optimization, target view Number is set to 1, and the computational methods of Combine distortion are R_union(T, G)=D₁(T, G)=F₁(T, T ', H (G, G ')), wherein: D₁(T, G) being the distortion of target view, T is that texture information works as block；G is side information current block；T ' is texture information current coded unit With the reconstructed block obtained after present mode coding, decoding；G ' is that side information current coded unit is with present mode coding, decoding After the reconstructed block that obtains；H (x, y) for calculate x and between the function of absolute value of each two corresponding point difference；F₁(x, y z) are Rebuild after calculating texture x and coding in conjunction with depth coding distortion z square error between texture y and function, concrete grammar is for depending on Big brief summary and camera parameters according to z, it is thus achieved that the project migration in target view that distortion z causes, recycles this side-play amount and looks for Knot and the position of corresponding point of degree of depth distortion calculate error between x with y；The computational methods of associating rate distortion costs are J =D_union(T, G)+λ R_union(T, G), wherein λ is a fixing global parameter.

Example five:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is the figure of two viewpoints in this instance As block；) side information that uses is depth information；Use associating rate-distortion optimization to complete optimization model to select；In optimization model In selection, the rate-distortion optimization algorithm of texture information independence is used to obtain two viewpoints from the K kind pattern that texture information encodes The N kind pattern (wherein K ＞=N) that current block is optimum, in the combination of texture N kind optimization model and the combination of all mode combinations of the degree of depth The middle mode combinations using associating rate-distortion optimization to choose optimum, and optimum mode combinations is applied to texture and the degree of depth two On the coding of individual viewpoint current block；In associating rate-distortion optimization, the computational methods of unicode rate are R_union(T, G)=R (T₁)+ R(T₂)+R(G₁)+R(G₂), wherein R (T₁) it is that the texture information current block of viewpoint 1 to be encoded is with present mode encoder bit rate, R (G₁) it is that the depth information sequence current block of viewpoint 1 to be encoded is with present mode encoder bit rate；R(T₂) it is the stricture of vagina of viewpoint 2 to be encoded Reason information current block is with present mode encoder bit rate, R (G₂) it is that the depth information sequence current block of viewpoint 2 to be encoded is to work as front mould Formula encoder bit rate；In associating rate-distortion optimization, target view number is set to 1, and the computational methods of Combine distortion are $D_{\mathrm{union}}(T,G)=D_1(T,G)=\underset{j=1}{\overset{Q}{\mathrm{\Σ}}}\underset{u=1}{\overset{V}{\mathrm{\Σ}}}{c}_{1,j,u}{D}_{1,u}(T_j,G_j)=\underset{j=1}{\overset{Q}{\mathrm{\Σ}}}\underset{u=1}{\overset{V}{\mathrm{\Σ}}}{c}_{1,j,u}{E}_u(W_1(T_j,G_j),W_1({T_j}^{\′},{G_j}^{\′})),$ Wherein: D_union(T, G) For Combine distortion, D₁(T, G) is the distortion that target view is corresponding, T_jFor the texture information current block of viewpoint j to be encoded, G_jFor treating The depth information sequence current block of coded views j, T_j' be viewpoint j to be encoded texture information current block with present mode coding, The reconstructed block obtained after decoding, G_j' be viewpoint j to be encoded depth information sequence current block with present mode coding, decoding after The reconstructed block obtained, W₁(x, y) for utilizing texture x and depth information y to obtain the virtual regarding raw of target view respective image information One-tenth method, E_u(x, y) for the function of the square error between pixel u of calculating x and y, c_{I, j, u}The mistake caused for viewpoint j to be encoded The very weight when calculating target view corresponding blocks pixel u, its computational methods are, when pixel u virtual regarding generation method W₁(x, Y) interpolation can be need not from viewpoint j to be encoded and directly obtain in, and can not directly obtain from another viewpoint, then c_{1, j, u}=1, if Interpolation can not be need not from viewpoint j to be encoded and directly obtain, can directly obtain from another viewpoint, then c_{1, j, u}=0, if being unsatisfactory for Any of the above-described, thenWherein h_jFor the parallax range between viewpoint j to be encoded and target view；Associating rate distortion The computational methods of cost are J=D_union(T, G)+λ R_union(T, G), wherein λ is a fixing global parameter.

Example six:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is image block in this instance；Use Side information be depth information；Use associating rate-distortion optimization to complete optimization model to select；In optimization model selects, use The rate-distortion optimization algorithm of texture information independence obtains N kind pattern (the wherein K of optimum from the K kind pattern that texture information encodes ＞=N), use associating rate-distortion optimization to choose the mould of optimum in the combination of texture N kind optimization model and all patterns of the degree of depth Formula combines, and optimum mode combinations is applied on the coding of texture and degree of depth current block；In associating rate-distortion optimization, The computational methods of unicode rate are R_union(T, G)=R (G), wherein R (G) is that depth information sequence current block is compiled with present mode Code code check；In associating rate-distortion optimization, target view number is set to 1, and the computational methods of Combine distortion areWherein D_union(T, G) is Combine distortion, D₁(T, G) is that target regards The distortion that point is corresponding, T is texture information current block and current block left side block and the right block, and G is depth information sequence current block, T ' is texture information current block with the reconstructed block obtained after present mode coding, decoding, G ' be depth information sequence current block with The reconstructed block that obtains after present mode coding, decoding, (x, y) for calculating the function of sensitive factor, the acting as of this function utilizes I X, y and surrounding pixel thereof are calculated the change complexity of this image-region, and image change complexity is the highest, and this value is more Greatly, I (T, T_n')=(T_n′-T_{N, l}])²+(T_n′-T_{N, r})², wherein T_n' for pixel u in reconstructed block, T_n.lFor T in original image_n′ One, the left side of respective pixel pixel, if T_n' on left picture boundary, then T_n.l=T_n, T_n.rFor T in original image_n' corresponding One, the right of pixel pixel, if T_n' on image right margin, then T_n.l=T_n, (x, y) for calculating difference between x and y for H Function, H (G_n, G_n')=| G_n′-G_n|；The computational methods of associating rate distortion costs are J=D_union(T, G)+λ R_union(T, G), its Middle λ is a fixing global parameter.

Example seven:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is image block in this instance；Use Side information be depth information；Use associating rate-distortion optimization to complete optimization model to select；In optimization model selects, use The rate-distortion optimization algorithm of texture information independence obtains N kind pattern (the wherein K of optimum from the K kind pattern that texture information encodes ＞=N), use associating rate-distortion optimization to choose the mould of optimum in the combination of texture N kind optimization model and all patterns of the degree of depth Formula combines, and optimum mode combinations is applied on the coding of texture and degree of depth current block；In associating rate-distortion optimization, The computational methods of unicode rate are R_union(T, G)=R (G), wherein R (G) is that depth information sequence current block is compiled with present mode Code code check；In associating rate-distortion optimization, target view number is set to 1, and the computational methods of Combine distortion areWherein D_union(T, G) is Combine distortion, D₁(T, G) is that target regards The distortion that point is corresponding, T is texture information current block and current block left side block and the right block, and G is depth information sequence current block, T ' is texture information current block with the reconstructed block obtained after present mode coding, decoding, G ' be depth information sequence current block with The reconstructed block that obtains after present mode coding, decoding, (x, y) for calculating the function of sensitive factor, the acting as of this function utilizes I X, y and surrounding pixel thereof are calculated the change complexity of this image-region, and image change complexity is the highest, and this value is more Greatly, $I(T,{T_n}^{\′})=\left\{\begin{array}{c}{({T_n}^{\′}-T_{n,l})}^2+{({T_n}^{\′}-T_{n,r})}^2,\mathrm{if}{G^{\′}}_n>G_n\\ {(T_n-{T^{\′}}_{n,l})}^2+{(T_n-{T^{\′}}_{n,r})}^2,\mathrm{else}\end{array}\right.,$ Wherein T_n' for pixel n in reconstructed block, T_n.lFor original T in image_nOne, the left side of ' respective pixel pixel, if T_n' on left picture boundary, then T_n.l=T_n, T_n.rFor original image Middle T_nOne, the right of ' respective pixel pixel, if T_n' on image right margin, then T_n.l=T_n, T_n.l' for T_n' respective pixel One, left side pixel, if T_n' on left picture boundary, then T_n.l'=T_n', T_n.r' for T_nOne, the right of ' respective pixel picture Element, if T_n' on current block right margin, then T_n.r'=T_n', (x, y) for calculating the function H (G of difference between x and y for H_n, G_n′) =(G_n′-G_n)²；The computational methods of associating rate distortion costs are J=D_union(T, G)+λ R_union(T, G), wherein λ is one fixing Global parameter.

Example eight:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is image block in this instance；Use Side information be depth information；The optimization quantized value using associating rate-distortion optimization to complete conversion coefficient selects；In conversion During the optimization quantized value of coefficient selects, the KL kind of the rate-distortion optimization algorithm texture information coding of texture information independence is used to become The quantized value changing coefficient obtains the quantized value (wherein KL ＞=NL) of optimum NL kind conversion coefficient, at texture NL kind optimal transformation The combination of the quantized value of the quantized value of coefficient and all conversion coefficients of the degree of depth is used associating rate-distortion optimization choose the mould of optimum Formula combines, and by the quantized value united application of optimum conversion coefficient on the coding of texture and degree of depth current block；In associating In rate-distortion optimization, the computational methods of unicode rate are R_union(T, G)=R (T)+R (G), wherein R (T) is that texture information is current Block is with the current quantisation value encoder bit rate of conversion coefficient, and R (G) is the depth information sequence current block current quantisation with conversion coefficient Value encoder bit rate；In associating rate-distortion optimization, target view number is set to 1, and the computational methods of Combine distortion are D_union(T, G) =D₁(T, G)=E (W₁(T, G), W₁(T ', G ')), wherein D_union(T, G) is Combine distortion, D₁(T, G) is that target view is corresponding Distortion, T is texture information current block, and G is depth information sequence current block, and T ' is that texture information current block is with Current Transform system The reconstructed block obtained after quantification value coding, decoding, G ' is that depth information sequence current block is compiled with current transform coefficient quantized value The reconstructed block obtained after code, decoding, W₁(x, y) for utilizing texture x and depth information y to obtain target view respective image information Virtual regarding generation method, (x, y) for calculating the function of total square error between x and y for E；The computational methods of associating rate distortion costs For J=D_union(T, G)+λ R_union(T, G), wherein λ is a fixing global parameter.

Example nine:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is image block in this instance；Use Side information be depth information；Use associating rate-distortion optimization to complete optimization model to select；In optimization model selects, use The rate-distortion optimization algorithm of texture information independence obtains optimum pattern, in the combination of all patterns of texture optimization model and the degree of depth The middle pattern using associating rate-distortion optimization to choose depth coding optimum, and optimum mode combinations is applied to degree of depth current block Coding on；In associating rate-distortion optimization, the computational methods of unicode rate are R_union(T, G)=R (G), wherein R (G) is deep Degree information sequence current block is with present mode encoder bit rate；In associating rate-distortion optimization, target view number is set to 1, associating The computational methods of distortion are D_union(T, G)=D₁(T, G)=E (W₁(T, G), W₁(T ', G ')), wherein D_union(T, G) is associating Distortion, D₁(T, G) is the distortion that target view is corresponding, and T is texture information current block, and G is depth information sequence current block, and T ' is Texture information current block is with the reconstructed block obtained after present mode coding, decoding, and G ' is that depth information sequence current block is with currently The reconstructed block obtained after pattern-coding, decoding, W₁(x, y) for utilizing texture x and depth information y to obtain target view respective image Information virtual regarding generation method, (x, y) for calculating the function of total square error between x and y for E；The meter of associating rate distortion costs Calculation method is J=D_union(T, G)+λ R_union(T, G), wherein λ is a fixing global parameter.

Example ten:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is image block in this instance；Use Side information be depth information；Use associating rate-distortion optimization to complete optimization model to select；In optimization model selects, use The rate-distortion optimization algorithm of texture information independence obtains optimum pattern, in the combination of all patterns of texture optimization model and the degree of depth The middle pattern using associating rate-distortion optimization to choose depth coding optimum, and optimum mode combinations is applied to degree of depth current block Coding on；In associating rate-distortion optimization, the computational methods of unicode rate are R_union(T, G)=R (G), wherein R (G) is deep Degree information sequence current block is with present mode encoder bit rate；In associating rate-distortion optimization, target view number is set to 2, associating The computational methods of distortion are $D_{\mathrm{union}}(T,G)=\underset{i=1}{\overset{2}{\mathrm{\Σ}}}0.5D_i(T,G)=\underset{i=1}{\overset{2}{\mathrm{\Σ}}}0.5E(W_i(T,G),V_i(T^{\′},G^{\′})),$ Wherein D_union(T, G) it is Combine distortion, D_i(T, G) is the distortion that target view i is corresponding, and T is texture information current macro, and G is parallax information sequence Current macro, T ' is texture information current macro with the reconstruction macro block obtained after present mode coding, decoding, and G ' is parallax information Sequence current macro is with the reconstruction macro block obtained after present mode coding, decoding, W_i(x, y) for utilizing texture x and parallax information y Obtain the virtual regarding generation method, V of target view i respective image information_i(x, y) for utilizing texture x and parallax information y to obtain mesh The simplification projecting method of mark viewpoint i respective image information, (x, y) for calculating the function of total absolute value error between x and y for E；Associating The computational methods of rate distortion costs are J=D_union(T, G)+λ R_union(T, G), wherein λ is according to coded quantization parameter determination Global parameter.

Example 11:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is image block in this instance；Use Side information be depth information；Use associating rate-distortion optimization to complete optimization model to select；In optimization model selects, use The rate-distortion optimization algorithm of texture information independence obtains optimum pattern, in the combination of all patterns of texture optimization model and the degree of depth The middle pattern using associating rate-distortion optimization to choose depth coding optimum, and optimum mode combinations is applied to degree of depth current block Coding on；In associating rate-distortion optimization, the computational methods of unicode rate are R_union(T, G)=R (G), wherein R (G) is deep Degree information sequence current block is with present mode encoder bit rate；In associating rate-distortion optimization, target view number is set to 3, associating The computational methods of distortion are $D_{\mathrm{union}}(T,G)=\underset{i=1}{\overset{2}{\mathrm{\Σ}}}{b}_i{D}_i(T,G)=\underset{i=1}{\overset{2}{\mathrm{\Σ}}}{b}_{i}E(W_i(T,G),V_i(T^{\′},G^{\′})),$ Wherein D_union(T, G) is for combining mistake Very, D_i(T, G) is the distortion that target view i is corresponding, and T is texture information current block, and G is depth information sequence current block, and T ' is Texture information current block is with the reconstructed block obtained after present mode coding, decoding, and G ' is that depth information sequence current block is with currently The reconstructed block obtained after pattern-coding, decoding, W_i(x, y) and V_i(x y) respectively utilizes texture x and depth information y to obtain target Different virtual regarding generation method of two kinds of viewpoint i respective image information, (x y) puts down for calculating average every pixel between x and y E The function of side's error, b_iFor real number, for target view i weight, parallax size between target view i and coded views determine；Connection The computational methods closing rate distortion costs are J=D_union(T, G)+λ R_union(T, G), the wherein code of encoded sequence according to λ Rate adjusts with distortion dynamics.

Example 12:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is image block in this instance；Use Side information be depth information；Use associating rate-distortion optimization to complete optimization model to select；In optimization model selects, use The rate-distortion optimization algorithm of texture information independence obtains optimum pattern, in the combination of all patterns of texture optimization model and the degree of depth The middle pattern using associating rate-distortion optimization to choose depth coding optimum, and optimum mode combinations is applied to degree of depth current block Coding on；In associating rate-distortion optimization, the computational methods of unicode rate are R_union(T, G)=R (G), wherein R (G) is deep Degree information sequence current block is with present mode encoder bit rate；In associating rate-distortion optimization, target view number is set to 1, associating The computational methods of distortion are D_union(T, G)=D₁(T, G)=F₁(T, T ', H (G, G ')), wherein: D₁(T, G) is target view Distortion, T is that texture information works as block；G is side information current block；T ' is that texture information current coded unit is compiled with present mode The reconstructed block obtained after code, decoding；G ' is that side information current coded unit is with the reconstruction obtained after present mode coding, decoding Block；H (x, y) for calculate x and between the function of absolute value of each two corresponding point difference；F₁(x, y, z) for combining depth coding Distortion z rebuild after calculating texture x and coding square error between texture y and function, concrete grammar be the big brief summary according to z and Camera parameters, it is thus achieved that the project migration in target view that distortion z causes, recycle this side-play amount find between x and y knot and The position of the corresponding point of degree of depth distortion also calculates error；The computational methods of associating rate distortion costs are J=D_union(T, G)+λ R_union(T, G), wherein λ is a fixing global parameter.

Example 13:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is image block in this instance；Use Side information be depth information；Use associating rate-distortion optimization to complete optimization model to select；In optimization model selects, use The rate-distortion optimization algorithm of texture information independence obtains optimum pattern, in the combination of all patterns of texture optimization model and the degree of depth The middle pattern using associating rate-distortion optimization to choose depth coding optimum, and optimum mode combinations is applied to degree of depth current block Coding on；In associating rate-distortion optimization, the computational methods of unicode rate are R_union(T, G)=R (G), wherein R (G) is deep Degree information sequence current block is with present mode encoder bit rate；In associating rate-distortion optimization, target view number is set to 1, associating The computational methods of distortion are $D_{\mathrm{union}}(T,G)=D_1(T,G)=\underset{j=1}{\overset{Q}{\mathrm{\Σ}}}\underset{u=1}{\overset{V}{\mathrm{\Σ}}}{c}_{1,j,u}{D}_{1,u}(T_j,G_j)=\underset{j=1}{\overset{Q}{\mathrm{\Σ}}}\underset{u=1}{\overset{V}{\mathrm{\Σ}}}{c}_{1,j,u}{E}_u(W_1(T_j,G_j),W_1({T_j}^{\′},{G_j}^{\′})),$ Wherein: D_union(T, G) is Combine distortion, D₁(T, G) is the distortion that target view is corresponding, T_jTexture for viewpoint j to be encoded is believed Breath current block, G_jFor the depth information sequence current block of viewpoint j to be encoded, T_j' it is the texture information current block of viewpoint j to be encoded With the reconstructed block obtained after present mode coding, decoding, G_j' it is that the depth information sequence current block of viewpoint j to be encoded is with currently The reconstructed block obtained after pattern-coding, decoding, W₁(x, y) for utilizing texture x and depth information y to obtain target view respective image Information virtual regarding generation method, E_u(x, y) for the function of the square error between pixel u of calculating x and y, c_{1, j, u}For waiting to compile The distortion that code viewpoint j the causes weight when calculating target view corresponding blocks pixel u, its computational methods are, when pixel u is virtual Depending on generation method W₁(x, y) in can need not interpolation from viewpoint j to be encoded and directly obtain, and directly can not obtain from another viewpoint , then c_{1, j, u}=1, if interpolation can not be need not from viewpoint j to be encoded and directly obtain, can directly obtain from another viewpoint, then c_{1, j, u}=0, if being unsatisfactory for any of the above-described point, thenWherein h_jFor the baseline between viewpoint j to be encoded and target view Distance；The computational methods of associating rate distortion costs are J=D_union(T, G)+λ R_union(T, G), wherein λ is a fixing overall situation ginseng Number.

Example 14:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is image block in this instance；Use Side information be depth information；Use associating rate-distortion optimization to complete optimization model to select；In optimization model selects, use The rate-distortion optimization algorithm of texture information independence obtains optimum pattern, in the combination of all patterns of texture optimization model and the degree of depth The middle pattern using associating rate-distortion optimization to choose depth coding optimum, and optimum mode combinations is applied to degree of depth current block Coding on；In associating rate-distortion optimization, the computational methods of unicode rate are R_union(T, G)=R (G), wherein R (G) is deep Degree information sequence current block is with present mode encoder bit rate；In associating rate-distortion optimization, target view number is set to 1, associating The computational methods of distortion are $D_{\mathrm{union}}(T,G)=D_1(T,G)=\underset{n}{\overset{S}{\mathrm{\Σ}}}I(T,{T_n}^{\′})H(G_n,{G_n}^{\′}),$ Wherein D_union(T, G) is for combining mistake Very, D₁(T, G) is the distortion that target view is corresponding, and T is texture information current block and current block left side block and the right block, and G is Depth information sequence current block, T ' is texture information current block with the reconstructed block obtained after present mode coding, decoding, and G ' is deep Degree information sequence current block with the reconstructed block that obtains after present mode coding, decoding, I (x, y) for calculating the function of sensitive factor, Act as utilizing x, y and the surrounding pixel thereof of this function are calculated the change complexity of this image-region, and image change is multiple Miscellaneous degree is the highest, and this value is the biggest, I (T, T_n')=(T_n′-T_{N, l}])²+(T_n′-T_{N, r})², wherein T_n' for pixel n in reconstructed block, T_n.lFor T in original image_nOne, the left side of ' respective pixel pixel, if T_n' on left picture boundary, then T_n.l=T_n, T_n.rFor T in original image_nOne, the right of ' respective pixel pixel, if T_n' on image right margin, then T_n.l=T_n, (x, y) for meter for H Calculate the function H (G of difference between x and y_n, G_n')=| G_n′-G_n|；The computational methods of associating rate distortion costs are J=D_union(T, G) +λR_union(T, G), wherein λ is a fixing global parameter.

Example 15:

This example describes a kind of 3 D video Rate-distortion optimization method, and current coded unit is image block in this instance；Use Side information be depth information；Use associating rate-distortion optimization to complete optimization model to select；In optimization model selects, use The rate-distortion optimization algorithm of texture information independence obtains optimum pattern, in the combination of all patterns of texture optimization model and the degree of depth The middle pattern using associating rate-distortion optimization to choose depth coding optimum, and optimum mode combinations is applied to degree of depth current block Coding on；In associating rate-distortion optimization, the computational methods of unicode rate are R_union(T, G)=R (G), wherein R (G) is deep Degree information sequence current block is with present mode encoder bit rate；In associating rate-distortion optimization, target view number is set to 1, associating The computational methods of distortion are $D_{\mathrm{union}}(T,G)=D_1(T,G)=\underset{n}{\overset{S}{\mathrm{\Σ}}}I(T,{T_n}^{\′})H(G_n,{G_n}^{\′}),$ Wherein D_union(T, G) is for combining mistake Very, D₁(T, G) is the distortion that target view is corresponding, and T is texture information current block and current block left side block and the right block, and G is Depth information sequence current block, T ' is texture information current block with the reconstructed block obtained after present mode coding, decoding, and G ' is deep Degree information sequence current block with the reconstructed block that obtains after present mode coding, decoding, I (x, y) for calculating the function of sensitive factor, Act as utilizing x, y and the surrounding pixel thereof of this function are calculated the change complexity of this image-region, and image change is multiple Miscellaneous degree is the highest, and this value is the biggest, $I(T,{T_n}^{\′})=\left\{\begin{array}{c}{({T_n}^{\′}-T_{n,l})}^2+{({T_n}^{\′}-T_{n,r})}^2,\mathrm{if}{G^{\′}}_n>G_n\\ {(T_n-{T^{\′}}_{n,l})}^2+{(T_n-{T^{\′}}_{n,r})}^2,\mathrm{else}\end{array}\right.,$ Wherein T_n' in reconstructed block Pixel n, T_n.lFor T in original image_nOne, the left side of ' respective pixel pixel, if T_n' on left picture boundary, then T_n.l= T_n, T_n.rFor T in original image_nOne, the right of ' respective pixel pixel, if T_n' on image right margin, then T_n.l=T_n, T_n.l' for T_nOne, the left side of ' respective pixel pixel, if T_n' on left picture boundary, then T_n.l'=T_n', T_n.r' for T_n' right Answer one, the right pixel of pixel, if T_n' on current block right margin, then T_n.r'=T_n', (x, y) for calculating between x and y for H Function H (the G of difference_n, G_n')=(G_n′-G_n)²；The computational methods of associating rate distortion costs are J=D_union(T, G)+λ R_union(T, G), wherein λ is a fixing global parameter.

What above example one to example 15 described is to use a kind of 3 D video Rate-distortion optimization method of the present invention Embodiment, the enforcement introducing several utilization a kind of 3 D video rate-distortion optimization device of the present invention in detail below is real Example.

Example 16:

A kind of 3 D video rate-distortion optimization device of the present invention, as shown in Figure 1: by coding and reconstruction module, connection Close code check computing module, Combine distortion computing module, associating rate distortion costs computing module, poll optimization module composition；Described Coding with rebuild module need texture information current coded unit and side information current coded unit as input, and with combine Code check computing module, Combine distortion computing module are connected；Described unicode rate computing module calculates mould with combining rate distortion costs Block is connected；Described Combine distortion computing module need camera parameters as input, and with combine rate distortion costs computing module It is connected；Described associating rate distortion costs computing module optimizes module with poll and is connected；Described poll optimizes module and coding and weight Modeling block is connected, and exports optimum code mode combinations.Wherein: the unit that (1) described device processes is image block；(2) described The 3 D video side information that device uses is depth information；(3) described parameters optimization is the volume of texture information and depth information Pattern combines；(4) described coding with rebuild module for according to currently processed coding mode combination carry out texture information with The Video coding of depth information current block, and obtain reconstruction image；(5) effect of the computing module of described unicode rate is to calculate Unicode rate, in this module, the computational methods of unicode rate are R_union(T, G)=R (T)+R (G), wherein R (T) is texture letter Breath current block is with present mode encoder bit rate, and R (G) is that depth information sequence current block is with present mode encoder bit rate；(6) described Combine distortion computing module act as calculate Combine distortion, in this module, target view number is set to 1, Combine distortion Computational methods are D_union(T, G)=D₁(T, G)=E (W₁(T, G), W₁(T ', G ')), wherein D_union(T, G) is Combine distortion, D₁ (T, G) is the distortion that target view is corresponding, and T is texture information current block, and G is depth information sequence current block, and T ' is texture letter Breath current block is with the reconstructed block obtained after present mode coding, decoding, and G ' is that depth information sequence current block is compiled with present mode The reconstructed block obtained after code, decoding, W₁(x, y) for utilizing texture x and depth information y to obtain target view respective image information Virtual regarding generation method, (x, y) for calculating the function of total square error between x and y for E；(7) described associating rate distortion costs calculates Module act as calculate associating rate distortion costs, in this module, combine rate distortion costs computational methods be J=D_union (T, G)+λ R_union(T, G), wherein λ is a fixing global parameter；(8) described poll optimize module act as control device Each mode combinations to be selected is carried out rate-distortion optimization and selects the optimization model combination that associating rate distortion costs is minimum, and will fortune For texture and the optimum mode combinations output of degree of depth current block.

Example 17:

A kind of 3 D video rate-distortion optimization device of the present invention, as shown in Figure 2: by pattern preliminary election module, coding With rebuild module, unicode rate computing module, Combine distortion computing module, combine rate distortion costs computing module, poll optimization Module forms.Described pattern preliminary election module optimizes module with coding with reconstruction module, poll and is connected；Described coding and reconstruction module Need texture information current coded unit and side information current coded unit as input, and with unicode rate computing module, Combine distortion computing module is connected；Described unicode rate computing module is connected with combining rate distortion costs computing module；Described Closing distortion computation module needs camera parameters as input and connected with combining rate distortion costs computing module；Described associating Rate distortion costs computing module optimizes module with poll and is connected；Described poll optimizes module and is connected with rebuilding module with coding, and Output optimum code mode combinations.Wherein: the unit that (1) described device processes is image block；(2) three-dimensional that described device uses Video side information is depth information；(3) effect of described pattern preliminary election module is the various coding modes to texture and the degree of depth Carry out primary election, in this module, use the rate-distortion optimization algorithm of texture information independence from the K kind pattern that texture information encodes Obtain optimum N kind pattern (wherein K ＞=N), using the combination of texture N kind optimization model and all patterns of the degree of depth as treating modeling Formula；(4) described coding is used for carrying out texture information and depth information according to currently processed coding mode combination with rebuilding module The Video coding of current block, and obtain reconstruction image；(5) effect of described unicode rate computing module is to calculate unicode rate, In this module, the computational methods of unicode rate are R_union(T, G)=R (T)+R (G), wherein R (T) is texture information current block With present mode encoder bit rate, R (G) is that depth information sequence current block is with present mode encoder bit rate；(6) described Combine distortion Computing module act as calculate Combine distortion, in this module, target view number is set to 1, the computational methods of Combine distortion For R_union(T, G)=D₁(T, G)=E (W₁(T, G), W₁(T ', G ')), wherein D_union(T, G) is Combine distortion, D₁(T, G) is mesh Mark distortion corresponding to viewpoint, T is texture information current block, and G is depth information sequence current block, T ' be texture information current block with The reconstructed block obtained after present mode coding, decoding, G ' is that depth information sequence current block is to obtain after present mode coding, decoding The reconstructed block arrived, W₁(x, y) virtual the regarding for utilizing texture x and depth information y to obtain target view respective image information generates Method, (x, y) for calculating the function of total square error between x and y for E；(7) effect of described associating rate distortion costs computing module For calculating associating rate distortion costs, in this module, the computational methods of associating rate distortion costs are J=D_union(T, G)+λ R_union (T, G), wherein λ is a fixing global parameter；(8) each is treated modeling by the control device that act as of described poll optimization module Formula combination carries out rate-distortion optimization and selects the minimum optimization model of associating rate distortion costs and combine, and will apply to texture and The optimum mode combinations output of degree of depth current block.

Example 18:

A kind of 3 D video rate-distortion optimization device of the present invention, as shown in Figure 2: by pattern preliminary election module, coding With rebuild module, unicode rate computing module, Combine distortion computing module, combine rate distortion costs computing module, poll optimization Module forms.Described pattern preliminary election module optimizes module with coding with reconstruction module, poll and is connected；Described coding and reconstruction module Need texture information current coded unit and side information current coded unit as input, and with unicode rate computing module, Combine distortion computing module is connected；Described unicode rate computing module is connected with combining rate distortion costs computing module；Described Closing distortion computation module needs camera parameters as input and connected with combining rate distortion costs computing module；Described associating Rate distortion costs computing module optimizes module with poll and is connected；Described poll optimizes module and is connected with rebuilding module with coding, and Output optimum code mode combinations.Wherein: the unit that (1) described device processes is image macro；(2) the three of described device use Dimension video side information is parallax information；(3) effect of described pattern preliminary election module is the various coding moulds to texture and parallax Formula carries out primary election, in this module, use texture information combine uncoded parallax information information rate-distortion optimization algorithm from The K kind pattern of texture information coding obtains the N kind pattern (wherein K ＞=N) of optimum, uses parallax information independence rate distortion excellent Change algorithm from the L kind pattern that parallax information encodes, obtain the M kind pattern (wherein L ＞ M) of optimum, wherein texture information rate distortion Optimized algorithm is that distortion to diverse location carries out different weightings on the basis of texture information independence rate-distortion optimization algorithm And obtain, position includes interior of articles, background, object boundary etc., and the judgement of position utilizes analysis parallax information to obtain, Using the combination of texture N kind optimization model and parallax M kind optimization model as treating lectotype；(4) described coding is used with rebuilding module In carrying out the Video coding of texture information and depth information current block according to currently processed coding mode combination, and obtain reconstruction Image；(5) effect of the computing module of described unicode rate is to calculate unicode rate, in this module, the calculating of unicode rate Method is R_union(T, G)=a_TR(T)+a_GR (G), wherein R (T) is that texture information current macro is with present mode encoder bit rate Estimated value, R (G) is that parallax information sequence current macro is with present mode encoder bit rate, a_T, a_GFor real number, respectively by texture information Determine with parallax information calculated distortion meansigma methods when selecting several optimization model；(6) described Combine distortion calculates mould Block act as calculate Combine distortion, in this module, target view number is set to 2, and the computational methods of Combine distortion are $D_{\mathrm{union}}(T,G)=\underset{i=1}{\overset{2}{\mathrm{\Σ}}}0.5D_i(T,G)=\underset{i=1}{\overset{2}{\mathrm{\Σ}}}0.5E(W_i(T,G),V_i(T^{\′},G^{\′})),$ Wherein D_union(T, G) is Combine distortion, D_i(T, G) is The distortion that target view i is corresponding, T is texture information current macro, and G is parallax information sequence current macro, and T ' is texture information Current macro is with the reconstruction macro block obtained after present mode coding, decoding, and G ' is that parallax information sequence current macro is to work as front mould The reconstruction macro block obtained after formula coding, decoding, W_i(x, y) in order to utilize texture x and parallax information y to obtain, target view i is corresponding to be schemed Virtual regarding generation method, V as information_i(x, y) for utilizing texture x and parallax information y to obtain target view i respective image information Simplification projecting method, (x, y) for calculating the function of total absolute value error between x and y for E；(7) described associating rate distortion costs meter That calculates module act as calculating associating rate distortion costs, and in this module, the computational methods of associating rate distortion costs are J=D_union (T, G)+λ R_union(T, G), wherein λ is the global parameter according to coded quantization parameter determination；(8) described poll optimizes module It act as controlling device each mode combinations to be selected is carried out rate-distortion optimization and selects the optimum that associating rate distortion costs is minimum Mode combinations, and the optimum mode combinations output of texture and degree of depth current block will be applied to.

Example 19:

A kind of 3 D video rate-distortion optimization device of the present invention, as shown in Figure 2: by pattern preliminary election module, coding With rebuild module, unicode rate computing module, Combine distortion computing module, combine rate distortion costs computing module, poll optimization Module forms.Described pattern preliminary election module optimizes module with coding with reconstruction module, poll and is connected；Described coding and reconstruction module Need texture information current coded unit and side information current coded unit as input, and with unicode rate computing module, Combine distortion computing module is connected；Described unicode rate computing module is connected with combining rate distortion costs computing module；Described Closing distortion computation module needs camera parameters as input and connected with combining rate distortion costs computing module；Described associating Rate distortion costs computing module optimizes module with poll and is connected；Described poll optimizes module and is connected with rebuilding module with coding, and Output optimum code mode combinations.Wherein: the unit that (1) described device processes is image block；(2) three-dimensional that described device uses Video side information is depth information；(3) effect of described pattern preliminary election module is the various coding modes to texture and the degree of depth Carry out primary election, in this module, use texture information to combine the rate-distortion optimization algorithm of uncoded depth information information from stricture of vagina The K kind pattern of reason information coding obtains the N kind pattern (wherein K ＞=N) of optimum, uses depth information to combine uncoded stricture of vagina The rate-distortion optimization algorithm of reason information obtains the M kind pattern (wherein L ＞ M) of optimum from the L kind pattern of encoding depth information, its Distortion D=D in middle texture information rate-distortion optimization algorithm₁(T, G)=E (W₁(T, G), W₁(T ', G)), D₁(T, G) is target The distortion of viewpoint 1 correspondence, T is texture information current block, and G is depth information sequence current block, T ' be texture information current block with The reconstructed block obtained after present mode coding, decoding, W₁(x, y) for utilizing texture x and depth information y to obtain target view 1 phase Answering the virtual regarding generation method of image information, (x, y) for calculating the function of total square error between x and y for E；Depth information rate is lost Distortion D=D in true optimized algorithm₁(T, G)=E (W₁(T, G '), W₁(T, G)), D₁(T, G) is the mistake of target view 1 correspondence Very, T is texture information current block, and G is depth information sequence current block, T ' be texture information current block with present mode coding, The reconstructed block obtained after decoding, W₁(x, y) for utilizing texture x and depth information y to obtain the void of target view 1 respective image information Intending regarding generation method, (x, y) for calculating the function of total square error between x and y for E；By texture N kind optimization model and degree of depth M kind The combination of optimization model is as treating lectotype；(4) described coding is used for according to currently processed coding mode group with rebuilding module Close the Video coding carrying out texture information with depth information current block, and obtain reconstruction image；(5) described unicode rate calculates mould Block act as calculate unicode rate, in this module, the computational methods of unicode rate are R_union(T, G)=a_TR(T)+a_GR (G), wherein R (T) is the texture information current block estimated value with present mode encoder bit rate, and R (G) is that depth information sequence is current Block is with the estimated value of present mode encoder bit rate, a_T, a_GFor real number, determined by the quantization parameter of texture information and depth information respectively Fixed；(6) described Combine distortion computing module act as calculate Combine distortion, in this module, target view number is set to 3, The computational methods of Combine distortion are $D_{\mathrm{union}}(T,G)=\underset{i=1}{\overset{2}{\mathrm{\Σ}}}{b}_i{D}_i(T,G)=\underset{i=1}{\overset{2}{\mathrm{\Σ}}}{b}_{i}E(W_i(T,G),V_i(T^{\′},G^{\′})),$ Wherein D_union (T, G) is Combine distortion, D_i(T, G) is the distortion that target view i is corresponding, and T is texture information current block, and G is depth information sequence Row current block, T ' is texture information current block with the reconstructed block obtained after present mode coding, decoding, and G ' is depth information sequence Current block is with the reconstructed block obtained after present mode coding, decoding, W_i(x, y) and V_i(x y) respectively utilizes texture x and the degree of depth Information y obtains different virtual regarding generation method of two kinds of target view i respective image information, and (x, y) for calculating between x and y for E The function of average every pixel square error, b_iFor real number, for target view i weight, by parallax between target view i and coded views Size determines；(7) described associating rate distortion costs computing module act as calculate associating rate distortion costs, in this module, The computational methods of associating rate distortion costs are J=D_union(T, G)+λ R_union(T, G), wherein encoded sequence according to λ Code check adjusts with distortion dynamics；(8) each mode combinations to be selected is entered by the control device that act as of described poll optimization module Row rate-distortion optimization also selects the optimization model combination that associating rate distortion costs is minimum, and will apply to texture and the degree of depth is current The optimum mode combinations output of block.

Example 20:

A kind of 3 D video rate-distortion optimization device of the present invention, as shown in Figure 2: by pattern preliminary election module, coding With rebuild module, unicode rate computing module, Combine distortion computing module, combine rate distortion costs computing module, poll optimization Module forms.Pattern preliminary election module optimizes module with coding with reconstruction module, poll and is connected；Described coding needs with rebuilding module Texture information current coded unit and side information current coded unit as input, and with unicode rate computing module, combine Distortion computation module is connected；Described unicode rate computing module is connected with combining rate distortion costs computing module；Described combine mistake True computing module needs camera parameters as input and connected with combining rate distortion costs computing module；Described rate of combining is lost True cost computing module optimizes module with poll and is connected；Described poll optimizes module and is connected with rebuilding module with coding, and exports Optimum code mode combinations.Wherein: the unit that (1) described device processes is image block；(2) 3 D video that described device uses Side information is depth information；(3) effect of described pattern preliminary election module is that the various coding modes to texture and the degree of depth are carried out Primary election, in this module, uses the rate-distortion optimization algorithm of texture information independence to obtain from the K kind pattern that texture information encodes Optimum N kind pattern (wherein K ＞=N), using the combination of texture N kind optimization model and all patterns of the degree of depth as treating lectotype； (4) described coding is current with depth information for carrying out texture information according to currently processed coding mode combination with reconstruction module The Video coding of block, and obtain reconstruction image；(5) effect of described unicode rate computing module is to calculate unicode rate, at this In module, the computational methods of unicode rate are R_union(T, G)=R (T)+R (G), wherein R (T) is that texture information current block is to work as Premode encoder bit rate, R (G) is that depth information sequence current block is with present mode encoder bit rate；(6) described Combine distortion calculates Module act as calculate Combine distortion, in this module, target view number is set to 1, and the computational methods of Combine distortion are D_union(T, G)=D₁(T, G)=F₁(T, T ', H (G, G ')), wherein: D₁(T, G) is the distortion of target view, and T is texture information Work as block；G is side information current block；T ' is that texture information current coded unit is with the weight obtained after present mode coding, decoding Build block；G ' is that side information current coded unit is with the reconstructed block obtained after present mode coding, decoding；(x, y) for calculating x for H The function of the absolute value of each two corresponding point difference between and；F₁(x, y, z) for combine depth coding distortion z calculate texture x with Rebuilding the function of square error sum between texture y after coding, concrete grammar is the big brief summary according to z and camera parameters, it is thus achieved that The project migration in target view that distortion z causes, recycles this side-play amount and finds between x with y the relative of knot and degree of depth distortion The position that should put also calculates error；(7) described associating rate distortion costs computing module act as calculate associating rate distortion costs, In this module, the computational methods of associating rate distortion costs are J=D_union(T, G)+λ R_union(T, G), wherein λ is one fixing Global parameter；(8) the control device that act as of described poll optimization module carries out rate-distortion optimization to each mode combinations to be selected And select the optimization model combination that associating rate distortion costs is minimum, and the optimum mould of texture and degree of depth current block will be applied to Formula combination output.

Example 21:

A kind of 3 D video rate-distortion optimization device of the present invention, as shown in Figure 2: by pattern preliminary election module, coding With rebuild module, unicode rate computing module, Combine distortion computing module, combine rate distortion costs computing module, poll optimization Module forms.Pattern preliminary election module optimizes module with coding with reconstruction module, poll and is connected；Described coding needs with rebuilding module Texture information current coded unit and side information current coded unit as input, and with unicode rate computing module, combine Distortion computation module is connected；Described unicode rate computing module is connected with combining rate distortion costs computing module；Described combine mistake True computing module needs camera parameters as input and connected with combining rate distortion costs computing module；Described rate of combining is lost True cost computing module optimizes module with poll and is connected；Described poll optimizes module and is connected with rebuilding module with coding, and exports Optimum code pattern.Wherein: the image block that unit is two viewpoints that (1) described device processes；(2) the three of described device use Dimension video side information is depth information；(3) effect of described pattern preliminary election module is the various coding moulds to texture and the degree of depth Formula carries out primary election, in this module, uses the rate-distortion optimization algorithm of texture information independence to obtain two viewpoint current blocks optimum NN kind mode combinations, using the combination of texture NN kind optimization model and the combination of all mode combinations of the degree of depth as treating lectotype；(4) Described coding regards with depth information two for carrying out texture information according to currently processed coding mode combination with rebuilding module The Video coding of some current block, and obtain reconstruction image；(5) effect of described unicode rate computing module is to calculate joint code Rate, in this module, the computational methods of unicode rate are R_union(T, G)=R (T₁)+R(T₂)+R(G₁)+R(G₂), wherein R (T₁) For the texture information current block of viewpoint 1 to be encoded with present mode encoder bit rate, R (G₁) it is the depth information of viewpoint 1 to be encoded Sequence current block is with present mode encoder bit rate；R(T₂) it is that the texture information current block of viewpoint 2 to be encoded is with present mode coding Code check, R (G₂) it is that the depth information sequence current block of viewpoint 2 to be encoded is with present mode encoder bit rate；(6) described Combine distortion Computing module act as calculate Combine distortion, in this module, target view number is set to 1, the computational methods of Combine distortion For $D_{\mathrm{union}}(T,G)=D_1(T,G)=\underset{j=1}{\overset{Q}{\mathrm{\Σ}}}\underset{u=1}{\overset{V}{\mathrm{\Σ}}}{c}_{1,j,u}{D}_{1,u}(T_j,G_j)=\underset{j=1}{\overset{Q}{\mathrm{\Σ}}}\underset{u=1}{\overset{V}{\mathrm{\Σ}}}{c}_{1,j,u}{E}_u(W_1(T_j,G_j),W_1({T_j}^{\′},{G_j}^{\′})),$ Wherein: D_union(T, G) For Combine distortion, D₁(T, G) is the distortion that target view is corresponding, T_jFor the texture information current block of viewpoint j to be encoded, G_jFor treating The depth information sequence current block of coded views j, T_j' be viewpoint j to be encoded texture information current block with present mode coding, The reconstructed block obtained after decoding, G_j' be viewpoint j to be encoded depth information sequence current block with present mode coding, decoding after The reconstructed block obtained, W₁(x, y) for utilizing texture x and depth information y to obtain the virtual regarding raw of target view respective image information One-tenth method, E_u(x, y) for the function of the square error between pixel u of calculating x and y, c_{1, j, u}The mistake caused for viewpoint j to be encoded The very weight when calculating target view corresponding blocks pixel u, its computational methods are, when pixel u virtual regarding generation method W₁(x, Y) interpolation can be need not from viewpoint j to be encoded and directly obtain in, and can not directly obtain from another viewpoint, then c_{1, j, u}=1, if Interpolation can not be need not from viewpoint j to be encoded and directly obtain, can directly obtain from another viewpoint, then c_{1, j, u}=0, if being unsatisfactory for Any of the above-described, thenWherein h_jFor the parallax range between viewpoint j to be encoded and target view；(7) described associating Rate distortion costs computing module act as calculate associating rate distortion costs, in this module, combine rate distortion costs calculating Method is J=D_union(T, G)+λ R_union(T, G), wherein λ is a fixing global parameter；(8) described poll optimizes module It act as controlling device and each is treated that lectotype carries out rate-distortion optimization and selects the optimization model that associating rate distortion costs is minimum, And the optimum mode combinations output of two viewpoint current blocks of the degree of depth will be applied to.

Example 22:

A kind of 3 D video rate-distortion optimization device of the present invention, as shown in Figure 2: by pattern preliminary election module, coding With rebuild module, unicode rate computing module, Combine distortion computing module, combine rate distortion costs computing module, poll optimization Module forms.Described pattern preliminary election module optimizes module with coding with reconstruction module, poll and is connected；Described coding and reconstruction module Need texture information current coded unit and side information current coded unit as input, and with unicode rate computing module, Combine distortion computing module is connected；Described unicode rate computing module is connected with combining rate distortion costs computing module；Described Closing distortion computation module needs camera parameters as input and connected with combining rate distortion costs computing module；Described associating Rate distortion costs computing module optimizes module with poll and is connected；Described poll optimizes module and is connected with rebuilding module with coding, and Output optimum code mode combinations.Wherein: the unit that (1) described device processes is image block；(2) three-dimensional that described device uses Video side information is depth information；(3) effect of described pattern preliminary election module is the various coding modes to texture and the degree of depth Carry out primary election, in this module, use the rate-distortion optimization algorithm of texture information independence to obtain texture information present encoding block Excellent pattern, using all for degree of depth patterns as treating lectotype；(4) described coding is used for current according to texture information with rebuilding module The pattern of encoding block optimum carries out the Video coding of texture information current block, carries out degree of depth letter according to currently processed coding mode The Video coding of breath current block, and obtain reconstruction image；(5) effect of described unicode rate computing module is to calculate joint code Rate, in this module, the computational methods of unicode rate are R_union(T, G)=R (T)+R (G), wherein R (T) is that texture information is current Block is with optimization model encoder bit rate, and R (G) is that depth information sequence current block is with present mode encoder bit rate；(6) described mistake is combined True computing module act as calculate Combine distortion, in this module, target view number is set to 1, the calculating side of Combine distortion Method is $D_{\mathrm{union}}(T,G)=D_1(T,G)=\underset{n}{\overset{S}{\mathrm{\Σ}}}I(T,{T_n}^{\′})H(G_n,{G_n}^{\′}),$ Wherein D_union(T, G) is Combine distortion, D₁(T, G) For the distortion that target view is corresponding, T is texture information current block and current block left side block and the right block, and G is depth information sequence Row current block, T ' is texture information current block with the reconstructed block obtained after present mode coding, decoding, and G ' is depth information sequence Current block is with the reconstructed block obtained after present mode coding, decoding, and (x, y) for calculating the function of sensitive factor, the work of this function for I With for utilizing x, y and surrounding pixel thereof are calculated the change complexity of this image-region, and image change complexity is the highest, This value is the biggest, I (T, T_n')=(T_n′-T_{N, l}])²+(T_n′-T_{N, r})², wherein T_n' for pixel u in reconstructed block, T_n.lFor original graph T in Xiang_nOne, the left side of ' respective pixel pixel, if T_n' on left picture boundary, then T_n.l=T_n, T_n.rFor in original image T_nOne, the right of ' respective pixel pixel, if T_n' on image right margin, then T_n.l=T_n, (x, y) for calculating between x and y for H The function of difference, H (G_n, G_n')=| G_n′-G_n|；(7) rate is combined in the calculating that act as of described associating rate distortion costs computing module Distortion cost, in this module, the computational methods of associating rate distortion costs are J=D_union(T, G)+λ R_union(T, G), wherein λ It it is a fixing global parameter；(8) each is treated that lectotype carries out rate mistake by the control device that act as of described poll optimization module Really optimize and select the optimization model that associating rate distortion costs is minimum, and by defeated for the optimum pattern that applies to degree of depth current block Go out.

Example 23:

A kind of 3 D video rate-distortion optimization device of the present invention, as shown in Figure 3: include coding with rebuild module, Unicode rate computing module, Combine distortion computing module, associating rate distortion costs computing module, poll optimize module.Described volume Code needs texture information current coded unit and side information current coded unit as input and joint code with rebuilding module Rate computing module, Combine distortion computing module are connected；Described unicode rate computing module with combine rate distortion costs computing module It is connected；Described Combine distortion computing module need camera parameters as input, and with combine rate distortion costs computing module phase Even；Described associating rate distortion costs computing module optimizes module with poll and is connected；Described poll optimizes module and coding and reconstruction Module, and export optimal transformation coefficient quantization value.Wherein: the unit that (1) described device processes is image block；(2) described device The 3 D video side information used is depth information；(3) described coding is used for according to currently processed conversion with rebuilding module The combination of coefficient quantization value carries out the Video coding of texture information and depth information current block, and obtains reconstruction image；(4) described The effect of the computing module closing code check is to calculate unicode rate, and in this module, the computational methods of unicode rate are R_union(T, G) =R (T)+R (G), wherein R (T) be texture information current block be that depth information sequence is current with present mode encoder bit rate, R (G) Block is with present mode encoder bit rate；(5) described Combine distortion computing module act as calculate Combine distortion, in this module, Target view number is set to 1, and the computational methods of Combine distortion are D_union(T, G)=D₁(T, G)=E (W₁(T, G), W₁(T ', G ')), wherein D_union(T, G) is Combine distortion, D₁(T, G) is the distortion that target view is corresponding, and T is texture information current block, G For depth information sequence current block, T ' is that texture information current block is to obtain after current transform coefficient quantized value coding, decoding Reconstructed block, G ' is that depth information sequence current block is with the reconstructed block obtained after current transform coefficient quantized value coding, decoding, W₁ (x, y) for utilizing texture x and depth information y to obtain the virtual regarding generation method of target view respective image information, (x y) is E Calculate the function of total square error between x and y；(6) rate is combined in the calculating that act as of described associating rate distortion costs computing module Distortion cost, in this module, the computational methods of associating rate distortion costs are J=D_union(T, G)+λ R_union(T, G), wherein λ It it is a fixing global parameter；(7) described poll optimize module act as control device to each quantization of transform coefficients to be selected Value combination carries out rate-distortion optimization and selects the optimal transformation coefficient quantization value combination that associating rate distortion costs is minimum, and will use In texture and the optimum quantization of transform coefficients value output of degree of depth current block.

It should be pointed out that, that the application of the present invention is extensive, method is very flexible, can not enumerate at this.In every case it is The algorithm utilizing the essence spirit of the present invention and design and the device of exploitation and system are all within the protection domain of this patent.

Claims (11)

1. a 3 D video Rate-distortion optimization method, it is characterised in that including: (1) uses texture information and side information associating Calculate unicode rate；(2) texture information and side information combined calculation Combine distortion are used；(3) utilize unicode rate and combine Distortion computation associating rate distortion costs；Described associating rate distortion costs is used for texture information and the combined coding of side information or use Coding in side information；Described associating rate distortion costs refers to use connection for the combined coding of texture information and side information Close rate distortion costs and combine the coding mode determining texture information and side information；Determine in coding mode combining, by texture The combination of the N number of pattern in information coding mode and M pattern in side information coding mode is selected associating rate distortion generation The mode combinations that valency is optimum；Wherein: N is integer, 2≤N≤K, K are the number of texture information coding mode；M is integer, 1 < =M≤L, L are the number of side information coding mode.

A kind of 3 D video Rate-distortion optimization method the most according to claim 1, it is characterised in that described side information is Depth information.

3. a 3 D video Rate-distortion optimization method, it is characterised in that including: (1) uses texture information and side information associating Calculate unicode rate；(2) texture information and side information combined calculation Combine distortion are used；(3) utilize unicode rate and combine Distortion computation associating rate distortion costs；Described associating rate distortion costs is used for texture information and the combined coding of side information or use Coding in side information；Described associating rate distortion costs refers to use connection for the combined coding of texture information and side information Close rate distortion costs and combine the optimization quantized value determining texture information and side information conversion coefficient；Conversion coefficient is determined combining Optimization quantized value in, by NL quantized value in texture information quantization of transform coefficients value and side information quantization of transform coefficients value In ML quantized value combination in select the quantized value combination that associating rate distortion costs is optimum；Wherein: NL is integer, 2≤NL ≤ KL, KL are the number of texture information quantization of transform coefficients value to be selected；ML is integer, and 1≤ML≤LL, LL are side information The number of quantization of transform coefficients value to be selected.

A kind of 3 D video Rate-distortion optimization method the most according to claim 3, it is characterised in that described side information is Depth information.

5. a 3 D video Rate-distortion optimization method, it is characterised in that including: (1) uses texture information and side information associating Calculate unicode rate；(2) texture information and side information combined calculation Combine distortion are used；(3) utilize unicode rate and combine Distortion computation associating rate distortion costs；Described associating rate distortion costs is used for texture information and the combined coding of side information or use Coding in side information；Described unicode rate R_unionThe computational methods of (T, G) are R_union(T, G)=a_TR(T)+a_GR(G)；Its In: R_union(T, G) is unicode rate；T is texture information current coded unit；G is side information current coded unit；R (T) is Following one of both: (1) texture information current coded unit encoder bit rate；(2) texture information current coded unit encoder bit rate Estimated value；R (G) is following one of both: (1) side information current coded unit encoder bit rate；(2) side information present encoding In cell encoding rate estimation value；a_TFor real number, for texture information current coded unit encoder bit rate weighted value；a_GFor real number, for Side information current coded unit encoder bit rate weighted value.

A kind of 3 D video Rate-distortion optimization method the most according to claim 5, it is characterised in that described side information is Depth information.

7. a 3 D video Rate-distortion optimization method, it is characterised in that including: (1) uses texture information and side information associating Calculate unicode rate；(2) texture information and side information combined calculation Combine distortion are used；(3) utilize unicode rate and combine Distortion computation associating rate distortion costs；Described associating rate distortion costs is used for texture information and the combined coding of side information or use Coding in side information；Described Combine distortion D_unionThe computational methods of (T, G) areWherein: D_union(T, G) is Combine distortion；T is texture information current coded unit；G is side information current coded unit；D_i(T, G) is The distortion that target view i is corresponding；b_iFor real number, for target view i weight；P=1,2 ... for target view number；I=1, 2 ... P is target view label.

A kind of 3 D video Rate-distortion optimization method the most according to claim 7, it is characterised in that described side information is Depth information.

A kind of 3 D video Rate-distortion optimization method the most according to claim 7, it is characterised in that described target view i Corresponding distortion D_iThe computational methods of (T, G) are one of following four method: the distortion D that (1) described target view i is corresponding_i(T, G) computational methods are D_i(T, G)=E (W_i(T,G),V_i(T',G'))；Wherein: D_i(T, G) is the distortion of target view i；T is Texture information current coded unit；G is side information current coded unit；T ' is that texture information current coded unit is compiled with current The reconstruction coding unit obtained after code parameter coding, decoding；G ' is that side information current coded unit is compiled with present encoding parameter The reconstruction coding unit obtained after code, decoding；W_i(x, y) and V_i(x, y) for utilizing texture x and side information y to obtain at viewpoint i The function of respective image information；(x, y) for calculating the function of difference between x and y for E；(2) distortion that described target view i is corresponding D_iThe computational methods of (T, G) are D_i(T, G)=F (T, T', H (G, G'))；Wherein: D_i(T, G) is the distortion of target view i；T is Texture information current coded unit；G is side information current coded unit；T ' is that texture information current coded unit is compiled with current The reconstruction coding unit obtained after code parameter coding, decoding；G ' is that side information current coded unit is compiled with present encoding parameter The reconstruction coding unit obtained after code, decoding；(x, y) for calculating the function of difference between x and y for H；(x, y z) supplement F for utilizing Information coding distortion z rebuilds the function of difference between texture y after calculating texture x and coding；(3) described current coded unit includes The respective image the most described T of multiple viewpoints to be encoded is by multiple T_jComposition, described G is by multiple G_jComposition, described target view i Corresponding distortion D_iThe computational methods of (T, G) areWherein: D_i(T, G) is target view i pair The distortion answered；T_jFor the corresponding unit to be encoded of texture information in viewpoint j to be encoded；G_jCorresponding for side information in viewpoint j to be encoded Unit to be encoded；D_i,u(T_j,G_j) for utilizing viewpoint j to be encoded to generate the distortion that pixel u of corresponding target view i is corresponding；c_i,j,u For real number, the weight of viewpoint j to be encoded during for calculating the Combine distortion of pixel u of target view i；I=1,2 ... P is target Viewpoint label；P=1,2 ... for target view number；J=1,2 ... Q is viewpoint label to be encoded；Q=1,2 ... for treating Coded views number；U=1,2 ... V is respective pixel piont mark；V=1,2 ... for corresponding pixel points number；(4) described mesh The distortion D that mark viewpoint i is corresponding_iThe computational methods of (T, G) areWherein: D_i(T, G) is target The distortion of viewpoint i；Tt is texture information current coded unit and the most each coding unit；G is that side information is currently compiled Code unit；T ' is that texture information current coded unit is with the reconstruction coding unit obtained after present encoding parameter coding, decoding；G’ For side information current coded unit with the reconstruction coding unit obtained after present encoding parameter coding, decoding；N is present encoding Pixel n in unit；S is sum of all pixels in current coded unit；(x, y) for calculating the function of difference between x and y for H；I(x,y) For calculating the function of sensitive factor.

A kind of 3 D video Rate-distortion optimization method the most according to claim 9, it is characterised in that described side information For depth information.

11. 1 kinds of 3 D video rate-distortion optimization devices, it is characterised in that this device is by encoding and rebuild module, unicode rate meter Calculate module, Combine distortion computing module, associating rate distortion costs computing module, poll optimization module composition；Described coding and weight Modeling block need texture information current coded unit and side information current coded unit or one of both as input, and with connection Close code check computing module, Combine distortion computing module is connected, and described unicode rate computing module calculates with combining rate distortion costs Module be connected, described Combine distortion computing module need camera parameters as input, and with combine rate distortion costs calculating mould Block is connected, and associating rate distortion costs computing module optimizes module with poll and is connected, and poll optimizes module and coding and rebuilds module It is connected, and exports optimized parameter；Described coding is used for carrying out texture information and benefit according to the coding parameter of input with rebuilding module Fill the coding of information or one of both, and obtain rebuilding image, described unicode rate computing module be used for calculating texture information and Side information combined coding code check, described Combine distortion computing module combines mistake for calculate texture information and side information Very, described associating rate distortion costs computing module is used for utilizing unicode rate to calculate associating rate distortion costs, wheel with Combine distortion Ask optimization module to be used for judging rate distortion costs and making Optimal Decision-making, when optimal conditions not yet meets, adjusting and optimizing parameter Setting, when optimal conditions meets, by optimum coding parameter output.