CN101593484A - Adaptive subfield coding of alternating current plasma display panels driving method and generation device - Google Patents

Abstract

The invention discloses a kind of adaptive subfield coding of alternating current plasma display panels driving method and generation device.Adopt simple accumulation formula light-emitting mode to realize that gray scale shows, the sub-field code weights carry out adaptively selected according to the intensity profile of input picture, intensity profile probability density by calculating input image, calculate can each sub-gray area of representing input images information between, between the group gray area in the gray-scale value number of samples more after a little while, between the antithetical phrase gray area in gray scale cumulative probability density carry out sampling processing; Otherwise, gray level is carried out sampling processing between the antithetical phrase gray area, finally can make each the sub-field code weights that produces by the sampling gray-scale value give expression to the abundantest input image information, carry out corresponding addressing and keep light emission operation according to the sub-field code weights that calculate.The present invention then is better than the similar approach in the existing document on gray level representation power except can eliminating AC PDP dynamic false outline phenomenon, can reproduce original image information better.

Description

Adaptive subfield coding of alternating current plasma display panels driving method and generation device

Technical field

The present invention is a kind of driving method and generation device that is applied to alternating-current plasma display (hereinafter to be referred as AC PDP), be particularly related to a kind of dynamic false outline phenomenon can eliminate AC PDP and show moving image the time, the driving method and the generation device that have good GTG ability to express again simultaneously.

Background technology

In AC PDP, adopt a son driving method of addressing display separation usually.Have dual mode to realize gray level display in a son driving method: a kind of is " combination " formula light-emitting mode, for example at US5541618 (T.Shinoda.Method and a circuit for gradationally driving a flat display device.UnitedStates Patent, 5541618, July 30,1996) method that proposes in the patent adopts this light-emitting mode to realize that gray scale shows exactly; Another kind is " simple accumulation " formula light-emitting mode, for example at EP0952569A2 (T.Takunaga, T.Shigeta, M.Suzuki.Method of driving plasma display panel[P] .European Patent, 0952569 A2, April 21,1999) method that proposes in the patent, adopt this light-emitting mode to realize that gray scale shows exactly." combination " formula of employing light-emitting mode realizes that the gray scale demonstration can show still image preferably, but the dynamic false outline phenomenon can occur when showing moving image, has a strong impact on the moving image display quality.

In AC PDP, adopt each height field to keep luminous " simple accumulation " light-emitting mode, different with " combination " formula light-emitting mode is: in a field picture in the time, each display unit is preparatory stage and an address discharge for once, remove first son outside the venue, all the other sons before carrying out address discharge on phase of keeping one of son establish a capital and carried out keeping luminous, all unit that carried out address discharge are no longer luminous in the phase of keeping.Adopt " simple accumulation " formula light-emitting mode to realize that gray scale shows, can eliminate the dynamic false outline phenomenon fully, ' CLEAR ' driving method that proposes among the document EP 0952569A2 is exactly to adopt each height field to keep luminous " simple accumulation " to realize that gray scale shows, its son weights are chosen according to the inverse gamma correction curve, but exist gray scale to show not enough problem equally.General dither method and the error diffusion method of adopting realized the more demonstration of multi-grey level.The major defect of tradition " simple accumulation " formula light-emitting mode is that the sub-field code weights are predetermined, and is irrelevant with shown image information, therefore will inevitably occur because gray scale shows the not enough static false contouring phenomenon that causes.For this reason, CN1652181A (Liu Zujun, Wang Hongguang, Li Yongdong etc. adaptive subfield coding of alternating current plasma display panels driving method and device [P]. Chinese patent, 1652181A, 2005-08-10) patent has proposed a kind of adaptive sub-field coding driving method, and this method has remedied tradition " simple accumulation " formula light-emitting mode gray scale to a certain extent and has shown not enough problem, but still there is shortcoming in it, promptly all adopts equimolecular gray scale interval method for the sampling between all sub-gray areas.This method certainly will cause the unreasonable image displaying quality reduction that causes because gray-scale value is sampled between certain a little gray area.For example, between certain a little gray area, can be chosen on the high gray level of gray probability density by the gray-scale value of will sampling, thereby make image information loss reduce.

Summary of the invention

One of purpose of the present invention is to propose a kind of adaptive subfield coding of alternating current plasma display panels driving method, and this method can be eliminated AC PDP dynamic false outline phenomenon, has high-quality GTG ability to express again.

Two of purpose of the present invention is to propose a kind of adaptive subfield coding of alternating current plasma display panels weights generation device, and it is simple in structure, cost is low, can increase substantially the display quality of AC PDP, especially the dynamic image display quality.

Technical scheme of the present invention is achieved in that

Adopt each height field to keep luminous " simple accumulation " and realize that gray scale shows, being used to control the sub-field code weights of keeping pulse number produces according to the intensity profile probability density self-adaptation of input picture, this method is by the intensity profile probability density of calculating input image, calculate can representing input images information the sampling gray-scale value, thereby select the sub-field code weights that are applied to corresponding input picture; Carry out corresponding addressing and keep operation according to the sub-field code weights that calculate simultaneously;

Concrete treatment step is as follows:

At first, select between main gray area, when P (k)＞Ps, gray-scale value k belongs to L between main gray area, P (k), (k=0,1 ..., H-1) be the probability density of gray scale k, be the number of times that occurs in input picture of gray scale k and the ratio of input picture total pixel number, H is the gray shade scale that input picture has, and Ps is the threshold parameter relevant with the intensity profile probability density of input picture, with the value of the intensity profile probability density P (k) of input picture by ordering from big to small, store among the P ', P ' is a length intermediate variable identical with P (k), and threshold parameter Ps is for satisfying formula $\underset{m=0}{\overset{n}{\mathrm{\Σ}}}{P}_m^{\′}\≥\mathrm{PA},$ The P ' of the minimum n correspondence of (0≤n≤H-1,0＜PA＜1) _n, between main gray area, comprise L between Ns sub-gray area in the L _j=(k _2j-1, k _2j) (j=1,2 ..., Ns), between this a little gray area in the probability density of gray level all greater than threshold parameter Ps;

Secondly, calculate L between each sub-gray area _jTonal range proportion in the L between main gray area ${\mathrm{PL}}_j=a_j\·(k_{2j}-k_{2j-1})/\underset{i=1}{\overset{\mathrm{Ns}}{\mathrm{\Σ}}}[a_i\·(k_{2i}-k_{2i-1})],(j=\mathrm{1,2},...,\mathrm{Ns}),$ A wherein _jBe the weight of sampling between j sub-gray area, a _j=A, if (k _2j-G _a)≤(G _a-k _2j-1); 1, else, A are the constant greater than 1, G _aBe the preset threshold value parameter; According to PL _jCalculate between each sub-gray area gray-scale value number, in this course, at first calculate the preliminary gray-scale value number of samples M ' between each sub-gray area sampling _j=Round ((N-1) PL _j) (j=1,2 ..., Ns), Round is the computing that is rounded up to nearest integer, N is sub-number of fields order; Secondly, guaranteeing that final gray-scale value sampling adds up under the prerequisite of N-1, obtains the final gray-scale value number of samples between each sub-gray area $M_j=\mathrm{Round}((N-1)\·M_j^{\′}/\underset{i=1}{\overset{\mathrm{Ns}}{\mathrm{\Σ}}}{M}_i^{\′}),(j=\mathrm{1,2},...,\mathrm{Ns});$

Then, according to the gray-scale value number of samples M between each sub-gray area _j, calculate sampling step length interior between each sub-gray area, in this course, to handle in two kinds of situation, first kind of situation is to calculate the sampling step length ST of interior gray scale cumulative probability density between each sub-gray area _j=SDF _j/ (M _j+ 1) (j=1,2 ..., Ns), wherein, SDF _jBe the gray probability density sum of interior all pixels between j sub-gray area, promptly ${\mathrm{SDF}}_j=\underset{i=k_{2j-1}}{\overset{k_{2j}}{\mathrm{\Σ}}}{n}_i/\mathrm{num},(j=\mathrm{1,2},...,\mathrm{Ns}),$ n _iFor having the pixel count of gray level i, num is the total pixel number of a field picture; Second kind of situation is to calculate gray-scale value sampling step length ST ' in each sub-range _j=(k _2j-k _2j-1)/(M _j+ 1);

Then, according to the sampling step length calculating sampling gray-scale value between each sub-gray area, handle equally in two kinds of situation in this course, first kind of situation be, begins sampling step length ST by separately from the cumulative probability density of left margin gray-scale value correspondence between each sub-gray area _jChoose M _jIndividual sampled point can obtain N-1 sampled point after handling between all sub-gray areas, the cumulative probability density according to sampled point obtains N-1 sampling gray-scale value, G again _I+1=j, ifCDF _j≤ P _i≤ CDF _J+1(i=1,2 ..., N-1; J=0,1 ..., 254), wherein, CDF _jBe the cumulative probability density of gray scale j, ${\mathrm{CDF}}_j=\underset{i=0}{\overset{j}{\mathrm{\Σ}}}{n}_i/\mathrm{num},$ P _iBe the cumulative probability density of i sampled point; Second kind of situation be, begins sampling step length ST ' by separately from the left margin gray-scale value between each sub-gray area _jDirectly choose M _jIndividual gray-scale value after handling between all sub-gray areas, can obtain N-1 sampling gray-scale value; After obtaining two groups of sampling gray-scale values, according to M _jThe sampling gray-scale value finally chosen in selecting between each sub-gray area of size, work as M _j≤ M _aThe time, M _aBe the preset threshold value parameter, choose sampling gray-scale value that first kind of situation obtain as the sampling gray-scale value of finally choosing between j sub-gray area, otherwise, choose sampling gray-scale value that second kind of situation obtain as the sampling gray-scale value of finally choosing between j sub-gray area; Adding at last is zero gray-scale value and gray-scale value k _2Ns, can obtain N+1 required gray-scale value G=[G ₁..., G _N+1];

Next, according to the N+1 that calculates a required gray-scale value G=[G ₁..., G _N+1], calculate N sub-field code weights SF=[SF according to " simple accumulation " formula light-emitting mode ₁, SF ₂..., SF _N], finish to the calculating of these adaptive sub-field coding weights.

At last, scan electrode driving circuit and keep the sub-field code weights SF of electrode drive circuit according to present image, produce each height field corresponding maintenance drive waveforms and control signal, scan electrode driving circuit and keep electrode drive circuit and adjust the pulse number of keeping of each height field according to sub-field code weights SF is promptly according to the pulse number of keeping of each son of proportional distribution of each height field weights; Simultaneously the addressing electrode driving circuit receives the view data that is used to show by sub-field code, and with scanning with keep electrode drive circuit and work in coordination and finish the addressing operation of AC PDP according to " simple accumulation " light-emitting mode.

A kind of adaptive subfield coding of alternating current plasma display panels weights generation device, this device input picture intensity profile probability density counting circuit is connected with main gray scale interval selection circuit with the threshold parameter counting circuit respectively, the threshold parameter counting circuit is connected with main gray scale interval selection circuit, the proportion counting circuit is connected between main gray scale interval selection circuit and each sub-gray area, between each sub-gray area between proportion counting circuit and each sub-gray area gray-scale value number of samples counting circuit be connected, gray-scale value number of samples counting circuit sampling step length counting circuit one respectively and between each sub-gray area between each sub-gray area, sampling step length counting circuit two selects circuit to be connected with the sampling gray-scale value between each sub-gray area, between each sub-gray area between sampling step length counting circuit one and each sub-gray area the sampled point selecting circuit be connected, the sampled point selecting circuit is connected with sampling gray-scale value counting circuit one between each sub-gray area, sampling step length counting circuit two is connected with sampling gray-scale value counting circuit two between each sub-gray area, sampling gray-scale value counting circuit one and sampling gray-scale value counting circuit two are connected to the sampling gray-scale value simultaneously and select circuit, and the sampling gray-scale value selects circuit to be connected with sub-field code weights counting circuit.

Received image signal GIN delivers to input picture intensity profile probability density counting circuit, input picture intensity profile probability density counting circuit calculates this gray distribution of image probability density P according to the received image signal GIN that receives, then it is delivered to threshold parameter counting circuit and main gray scale interval selection circuit respectively, the intensity profile probability density P that the threshold parameter counting circuit is sent here according to input picture intensity profile probability density counting circuit calculates the threshold parameter Ps that is applied to this image, then it is sent to main gray scale interval selection circuit, main gray scale interval selection circuit receives from the intensity profile probability density P of input picture intensity profile probability density counting circuit and the threshold parameter Ps of threshold parameter counting circuit, thereby select L between the main gray area of this image, and be sent to proportion counting circuit between each sub-gray area, proportion PL during L calculates between each sub-gray area between main gray area between the main gray area that the proportion counting circuit is sent here according to main gray scale interval selection circuit between each sub-gray area _j, and it is sent to gray-scale value number of samples counting circuit between each sub-gray area, between each sub-gray area gray-scale value number of samples counting circuit according between each sub-gray area between main gray area in proportion PL _jCalculate gray-scale value number of samples M between each sub-gray area _jAnd result of calculation delivered between each sub-gray area sampling step length counting circuit two between sampling step length counting circuit one and each sub-gray area respectively, next divide two parts to carry out simultaneously, on the one hand, sampling step length counting circuit one receives gray-scale value number of samples M between each sub-gray area that gray-scale value number of samples counting circuit is sent here between each sub-gray area between each sub-gray area _j, calculate between each sub-gray area in the sampling step length ST of gray scale cumulative probability density _j, and result of calculation delivered to sampled point selecting circuit between each sub-gray area, the sampled point selecting circuit is according to the sampling step length ST of gray scale cumulative probability density between each sub-gray area between each sub-gray area _jCalculate the gray scale cumulative probability density P of sampled point _i, and being sent to sampling gray-scale value counting circuit one, sampling gray-scale value counting circuit one is according to the gray scale cumulative probability density P of each sampled point _iCalculate sampling gray-scale value G, and result of calculation is sent to the sampling gray-scale value selects circuit, on the other hand, sampling step length counting circuit two receives gray-scale value number of samples M between each sub-gray area that gray-scale value number of samples counting circuit is sent here between each sub-gray area between each sub-gray area _j, calculate between each sub-gray area in the sampling step length ST ' of gray level _j, and result of calculation being sent to sampling gray-scale value counting circuit two, sampling gray-scale value counting circuit two is according to the sampling step length ST ' of gray level between each sub-gray area _jCalculate another group sampling gray-scale value G ', and result of calculation is sent to the sampling gray-scale value selects circuit, the sampling gray-scale value selects circuit to receive from the sampling gray-scale value G of sampling gray-scale value counting circuit one and the sampling gray-scale value G ' of sampling gray-scale value counting circuit two, and gray-scale value number of samples M between each sub-gray area of sending here according to gray-scale value number of samples counting circuit between each sub-gray area _jSelect the sampling gray-scale value of finally selecting for use between each sub-gray area, be combined into zero gray-scale value and gray-scale value k again _2NsFinally obtain N+1 sampling gray-scale value G _f, being sent to sub-field code weights counting circuit then, sub-field code weights counting circuit is according to sampling gray-scale value G _fCalculate the sub-field code weights SF that is applied to corresponding input picture.

The present invention proposes adaptive sub-field coding driving method and the generation device of a kind of AC of being applied to PDP, dynamic false outline phenomenon when this method and device can be eliminated AC PDP demonstration dynamic image fully, avoided again simultaneously showing not enough problem by the luminous gray scale of bringing of " simple accumulation " formula, make display image when the dynamic false outline phenomenon not occurring, have high-quality GTG expression effect.

Description of drawings

Fig. 1 is an adaptive sub-field coding weights generation device circuit block diagram of the present invention;

Fig. 2 is an adaptive sub-field coding weights calculation flow chart of the present invention;

Fig. 3 is the present invention carries out the gray-scale value sampling according to gray scale cumulative probability density a schematic diagram;

Fig. 4 is the sampled result figure that is obtained by first kind of situation in the calculating sampling gray-scale value process of the present invention;

Fig. 5 is the sampled result figure that is obtained by second kind of situation in the calculating sampling gray-scale value process of the present invention;

Fig. 6 is the gray-scale value sampled result figure that the present invention finally obtains;

Fig. 7 is the computer artificial result comparison diagram of the method that proposes of the method that proposes of the present invention and document CN1652181A.

Fig. 8 is the method that proposes of the present invention and the computer artificial result comparison diagram of ' CLEAR ' method.

Below in conjunction with accompanying drawing content of the present invention is described in further detail.

Embodiment

With reference to shown in Figure 1, the adaptive sub-field coding weights generation device that the present invention proposes is made up of following several modules: input picture intensity profile probability density counting circuit 1, threshold parameter counting circuit 2, main gray scale interval selection circuit 3, proportion counting circuit 4 between each sub-gray area, gray-scale value number of samples counting circuit 5 between each sub-gray area, sampling step length counting circuit 1 between each sub-gray area, sampling step length counting circuit 27 between each sub-gray area, sampled point selecting circuit 8 between each sub-gray area, sampling gray-scale value counting circuit 1, sampling gray-scale value counting circuit 2 10, the sampling gray-scale value is selected circuit 11, sub-field code weights counting circuit 12.Received image signal GIN delivers to input picture intensity profile probability density counting circuit 1.Input picture intensity profile probability density counting circuit 1 calculates this gray distribution of image probability density P according to the received image signal GIN that receives, and then it is delivered to threshold parameter counting circuit 2 and main gray scale interval selection circuit 3 respectively.The intensity profile probability density P that threshold parameter counting circuit 2 is sent here according to input picture intensity profile probability density counting circuit 1 calculates the threshold parameter Ps that is applied to this image, then it is sent to main gray scale interval selection circuit 3.Main gray scale interval selection circuit 3 receives from the intensity profile probability density P of input picture intensity profile probability density counting circuit 1 and the threshold parameter Ps of threshold parameter counting circuit 2, thereby select L between the main gray area of this image, and be sent to proportion counting circuit 4 between each sub-gray area.Proportion PL during L calculates between each sub-gray area between main gray area between the main gray area that proportion counting circuit 4 is sent here according to main gray scale interval selection circuit 3 between each sub-gray area _j, and it is sent to gray-scale value number of samples counting circuit 5 between each sub-gray area.Between each sub-gray area gray-scale value number of samples counting circuit 5 according between each sub-gray area between main gray area in proportion PL _jCalculate gray-scale value number of samples M between each sub-gray area _j, and result of calculation delivered between each sub-gray area sampling step length counting circuit 27 between sampling step length counting circuit 1 and each sub-gray area respectively.Next divide two parts to carry out simultaneously, on the one hand, sampling step length counting circuit 1 receives gray-scale value number of samples M between each sub-gray area that gray-scale value number of samples counting circuit 5 is sent here between each sub-gray area between each sub-gray area _j, calculate between each sub-gray area in the sampling step length ST of gray scale cumulative probability density _j, and result of calculation delivered to sampled point selecting circuit 8 between each sub-gray area.Sampled point selecting circuit 8 is according to the sampling step length ST of interior gray scale cumulative probability density between each sub-gray area between each sub-gray area _jCalculate the gray scale cumulative probability density P of sampled point _i, and be sent to sampling gray-scale value counting circuit 1.Sampling gray-scale value counting circuit 1 is according to the gray scale cumulative probability density P of each sampled point _iCalculate sampling gray-scale value G, and result of calculation is sent to the sampling gray-scale value selects circuit 11.On the other hand, sampling step length counting circuit 27 receives gray-scale value number of samples M between each sub-gray area that gray-scale value number of samples counting circuit 5 is sent here between each sub-gray area between each sub-gray area _j, calculate between each sub-gray area in the sampling step length ST ' of gray level _j, and result of calculation is sent to sampling gray-scale value counting circuit 2 10.Sampling gray-scale value counting circuit 2 10 sampling step length ST ' according to interior gray level between each sub-gray area _jCalculate another group sampling gray-scale value G ', and result of calculation is sent to the sampling gray-scale value selects circuit 11.The sampling gray-scale value selects circuit 11 to receive from the sampling gray-scale value G of sampling gray-scale value counting circuit 1 and the sampling gray-scale value G ' of sampling gray-scale value counting circuit 2 10, and gray-scale value number of samples M between each sub-gray area of sending here according to gray-scale value number of samples counting circuit 5 between each sub-gray area _jSelect the sampling gray-scale value of finally selecting for use between each sub-gray area, be combined into zero gray-scale value and gray-scale value k again _2NsFinally obtain N+1 sampling gray-scale value G _f, be sent to sub-field code weights counting circuit 12 then.Sub-field code weights counting circuit 12 is according to sampling gray-scale value G _fCalculate the sub-field code weights SF that is applied to corresponding input picture.

With reference to shown in Figure 2, the calculating of adaptive sub-field coding weights mainly is divided into six big steps.

At first, the view data GIN according to input calculates the intensity profile probability density P (k) of an input picture, (k=0,1 ..., H-1), H is the gray shade scale that input picture has, i.e. the number of times that occurs in input picture of gray scale k and the ratio (step S1) of input picture total pixel number.

Determine L (step S2) between input picture master gray area according to input picture intensity profile probability density.

Among the step S2, earlier determine threshold value Ps (step S21), the value of the intensity profile probability density P (k) of input picture by ordering from big to small, is stored among the P ' according to input picture intensity profile probability density, P ' is a length intermediate variable identical with P (k), and Ps is for satisfying formula $\underset{m=0}{\overset{n}{\mathrm{\Σ}}}{P}_m^{\′}\≥\mathrm{PA},$ The P ' of the minimum n correspondence of (0≤n≤H-1,0＜PA＜1) _n

Determine between Ns sub-gray area according to Ps again and L (step S22) between main gray area, when P (k)＞Ps, k belongs between main gray area, promptly $k\⋐L,$ Then between Ns sub-gray area be

$\left\{\begin{array}{c}{\mathrm{<figure-callout\; id="1"\; label="L"\; filenames="A2009100231160021H1.png,A2009100231160022H1.png"\; state="\{\{state\}\}">L</figure-callout>}}_1,L_2,...,L_{\mathrm{Ns}}\\ L_j=(k_{2j-1},k_{2j}),1\&le;j\&le;\mathrm{Ns}\end{array}\right.$

According to determining L between main gray area between Ns sub-gray area, i.e. L=L ₁∪ L ₂... L _Ns

When determining between main gray area behind the L, calculate between each sub-gray area proportion (step S3) between main gray area, ${\mathrm{PL}}_j=a_j\&CenterDot;(k_{2j}-k_{2j-1})/\underset{i=1}{\overset{\mathrm{Ns}}{\mathrm{\&Sigma;}}}[a_i\&CenterDot;(k_{2i}-k_{2i-1})],(j=\mathrm{1,2},...,\mathrm{Ns}),$ A wherein _jBe the weight of sampling between j sub-gray area,

$a_j=\left\{\begin{array}{cc}A,& (k_{2j}-G_a)\&le;(G_a-k_{2j-1})\\ 1,& (k_{2j}-G_a)>(G_a-k_{2j-1})\end{array}\right.$

A＞1，j＝1，2，...，Ns

According to PL _jCalculate between each sub-gray area interior with the gray-scale value number of samples of choosing (step S4).In step S4, at first calculate the preliminary gray-scale value number of samples M ' between each sub-gray area _j=Round ((N-1) PL _j) (j=1,2 ..., Ns), Round is the computing that is rounded up to nearest integer, secondly, is guaranteeing that final gray-scale value sampling adds up under the prerequisite of N-1, obtains the final gray-scale value number of samples between each sub-gray area $M_j=\mathrm{Round}((N-1)\&CenterDot;M_j^{\&prime;}/\underset{i=1}{\overset{\mathrm{Ns}}{\mathrm{\&Sigma;}}}{M}_i^{\&prime;}),(j=\mathrm{1,2},...,\mathrm{Ns}).$

According to gray-scale value number of samples M interior between each sub-gray area _j, calculate N+1 the sampling gray-scale value (step S5) that to adopt.

In step S5, handle simultaneously in two kinds of situation.First kind of situation (step S51), the sampling step length (step S511) of gray scale cumulative probability density at first calculating between each sub-gray area, ST _j=SDF _j/ (M _j+ 1) (j=1,2 ..., Ns), wherein, SDF _jBe the gray probability density sum of interior all pixels between j sub-gray area, promptly ${\mathrm{SDF}}_j=\underset{i=k_{2j-1}}{\overset{k_{2j}}{\mathrm{\&Sigma;}}}{n}_i/\mathrm{num},(j=\mathrm{1,2},...,\mathrm{Ns}),$ n _iFor having the pixel count of gray level i, num is the total pixel number of a field picture.Then begin sampling step length ST by separately from the cumulative probability density of left margin gray-scale value correspondence between each sub-gray area _jChoose M _jIndividual sampled point (step S512), sampling process is as follows,

n＝1；

For?j＝1?to?N _s

For?i＝1?to?M _j

$P_n={\mathrm{CDF}}_{k_{2j-1}}+{\mathrm{iST}}_j;$

n＝n+1；

End

End

Wherein, P _nBe the cumulative probability density of sample point gray-scale value,

Be gray level k _2j-1Cumulative probability density, ${\mathrm{CDF}}_j=\underset{i=0}{\overset{j}{\mathrm{\&Sigma;}}}{n}_i/\mathrm{num}.$

After handling between all sub-gray areas, can obtain N-1 sampled point.Then, obtain N-1 sampling gray-scale value (step S513), g according to the cumulative probability density of sampled point again _I+1=j, if CDF _j≤ P _i≤ CDF _J+1(i=1,2 ..., N-1; J=0,1 ..., 254).

Second kind of situation (step S52) at first calculated interior gray-scale value sampling step length (step S521), i.e. ST ' between each sub-gray area _j=(k _2j-k _2j-1)/(M _j+ 1), begins by corresponding sampling step length ST ' from left margin gray-scale value between each sub-gray area then _jChoose M _jIndividual gray-scale value (step S522) after handling between all sub-gray areas, can obtain N-1 sampling gray-scale value.

After obtaining two groups of sampling gray-scale values, according to M _jThe sampling gray-scale value (step S53) finally chosen in selecting between each sub-gray area of size, work as M _j≤ M _aThe time, M _aBe the preset threshold value parameter, choose sampling gray-scale value that first kind of situation obtain as the sampling gray-scale value of finally choosing between j sub-gray area, otherwise, choose sampling gray-scale value that second kind of situation obtain as the sampling gray-scale value of finally choosing between j sub-gray area.

Adding at last is zero gray-scale value and gray-scale value k _2Ns, then can obtain N+1 required gray-scale value (step S54), i.e. G=[G ₁..., G _N+1].

After obtaining a needed N+1 gray-scale value, calculate N the sub-field code weights SF=[SF that is used for " simple accumulation " light-emitting mode ₁, SF ₂..., SF _N] (step S6),

SF _i＝G _i+1-G _i(1≤i≤N)。

With reference to shown in Figure 3, be in the calculating sampling gray-scale value process of the present invention, under first kind of situation, carry out the schematic diagram of gray-scale value sampling, the step S512 in the corresponding figures 2 according to gray scale cumulative probability density.Horizontal ordinate is represented gray level among Fig. 3, ordinate is represented gray scale cumulative probability density value, curve ' a ' is the gray scale cumulative probability densimetric curve of input picture, vertically straight line is represented sub-gray scale interval endpoint gray-scale value with the transverse axis intersection point, laterally straight line and curve ' intersection point of a ' is illustrated in the sampled point of (step S512) acquisition under first kind of situation.

With reference to shown in Figure 4, be the sampled result figure that obtains by first kind of situation in the calculating sampling gray-scale value process of the present invention.Horizontal ordinate is represented gray level among Fig. 4, and ordinate is represented gray probability density value, curve ' a ' is the gray probability density profile of input picture, vertically straight line and transverse axis intersection point are the sampling gray-scale value.Can obviously find out, under first kind of situation, in the sampling gray-scale value of acquisition has dropped between sub-gray area on the higher gray level of gray probability density value.

With reference to shown in Figure 5, be the sampled result figure that obtains by second kind of situation in the calculating sampling gray-scale value process of the present invention.With Fig. 4 relatively, the sampling gray-scale value that is obtained by second kind of situation is characterized in being between each sub-gray area and is spacedly distributed.

With reference to shown in Figure 6, be the gray-scale value sampled result figure that the present invention finally obtains.Fig. 6 is according to gray-scale value number of samples M between each sub-gray area _jSize chosen the sampling gray-scale value that calculates under the different situations respectively, for example, in between the sub-gray area of 9-45, what select for use is the sampling gray-scale value that obtains under first kind of situation, in the gray-scale value that is characterized in sampling has dropped between sub-gray area on the higher gray level of gray probability density value, in between the sub-gray area of 100-193, what select for use is the sampling gray-scale value that obtains under second kind of situation, and the gray-scale value that is characterized in sampling is between sub-gray area and is spacedly distributed.

With reference to shown in Figure 7, the computer artificial result comparison of the method that to be the method that proposes of the present invention propose with document CN1652181A.Fig. 7 (a) and Fig. 7 (d) are original input pictures.In the simulation process, the method that method that the present invention proposes and document CN1652181A propose all adopts 14 sons (being N=14).Fig. 7 (b) and Fig. 7 (e) are the simulation results that the present invention proposes method, and Fig. 7 (c) Fig. 7 (f) is the simulation result of document CN1652181A proposition method.The simulation result that compares two kinds of methods, as can be seen, for the original input picture shown in Fig. 7 (a), at first, pocket lid (sign 1) and clothing seam (sign 2) on the clothes are all displayed in Fig. 7 (b), and Fig. 7 (c) does not provide such detailed information.Secondly, for the highlighted part (sign 3) of sky and distant place buildings, Fig. 7 (b) also is better than Fig. 7 (c), as can be seen, because the disappearance of highlighted gray level causes sky and buildings shortage gray-level sense at a distance among Fig. 7 (c).For the original input picture shown in Fig. 7 (d), the result that Fig. 7 (f) provides is in cap front end (sign 4), forehead (sign 5), shoulder place (sign 6) gray level transitions gets all unsmooth, compares with Fig. 7 (e), and the static false contouring phenomenon among Fig. 7 (f) is more obvious.

With reference to shown in Figure 8, the computer artificial result comparison of ' CLEAR ' method that to be the method that proposes of the present invention propose with document EP 0952569A2.In the emulation, as original input picture, two kinds of methods all adopt 14 son fields with Fig. 7 (d).For the display effect in the artificial actual application, two kinds of methods have all been carried out the error diffusion processing.Wherein, the sub-field code weights of ' CLEAR ' method employing are [1,3,5,8,10,13,16,19,22,25,28,32,35,39].Relatively the simulation result of two kinds of methods can obviously be found out, error diffusion noise is apparent in view among Fig. 8 (b), and this is to have produced bigger quantization error when owing to the sub-field code weights in ' CLEAR ' method of employing original input picture being carried out encoding process to cause.

Claims (2)

1, the adaptive subfield coding of alternating current plasma display panels driving method is characterized in that,

At first, select between main gray area, when P (k)＞Ps, gray-scale value k belongs to L between main gray area, P (k), (k=0,1 ..., H-1) be the probability density of gray scale k, be the number of times that occurs in input picture of gray scale k and the ratio of input picture total pixel number, H is the gray shade scale that input picture has, and Ps is the threshold parameter relevant with the intensity profile probability density of input picture, with the value of the intensity profile probability density P (k) of input picture by ordering from big to small, store among the P ', P ' is a length intermediate variable identical with P (k), and threshold parameter Ps is for satisfying formula $\underset{m=0}{\overset{n}{\mathrm{\&Sigma;}}}{P}_m^{\&prime;}\&GreaterEqual;\mathrm{PA},$ The P ' of the minimum n correspondence of (0≤n≤H-1,0＜PA＜1) _n, between main gray area, comprise L between Ns sub-gray area in the L _j=(k _2j-1, k _2j) (j=1,2 ..., Ns), between this a little gray area in the probability density of gray level all greater than threshold parameter Ps;

Secondly, calculate L between each sub-gray area _jTonal range proportion in the L between main gray area ${\mathrm{PL}}_j=a_j\&CenterDot;(k_{2j}-k_{2j-1})/\underset{i=1}{\overset{\mathrm{Ns}}{\mathrm{\&Sigma;}}}[a_i\&CenterDot;(k_{2i}-k_{2i-1})](j=\mathrm{1,2},...,\mathrm{Ns}),$ A wherein _jBe the weight of sampling between j sub-gray area, a _j=A, if (k _2j-G _a)≤(G _a-k _2j-1); 1, else, A are the constant greater than 1, G _aBe the preset threshold value parameter; According to PL _jCalculate between each sub-gray area gray-scale value number, in this course, at first calculate the preliminary gray-scale value number of samples M ' between each sub-gray area sampling _j=Round ((N-1) PL _j) (j=1,2 ..., Ns), Round is the computing that is rounded up to nearest integer, N is sub-number of fields order; Secondly, guaranteeing that final gray-scale value sampling adds up under the prerequisite of N-1, obtains the final gray-scale value number of samples between each sub-gray area $M_j=\mathrm{Round}((N-1)\&CenterDot;M_j^{\&prime;}/\underset{i=1}{\overset{\mathrm{Ns}}{\mathrm{\&Sigma;}}}{M}_i^{\&prime;})(j=\mathrm{1,2},...,\mathrm{Ns});$

Then, according to the gray-scale value number of samples M between each sub-gray area _j, calculate sampling step length interior between each sub-gray area, in this course, to handle in two kinds of situation, first kind of situation is to calculate the sampling step length ST of interior gray scale cumulative probability density between each sub-gray area _j=SDF _j/ (M _j+ 1) (j=1,2 ..., Ns), wherein, SDF _jBe the gray probability density sum of interior all pixels between j sub-gray area, promptly ${\mathrm{SDF}}_j=\underset{i=k_{2j-1}}{\overset{k_{2j}}{\mathrm{\&Sigma;}}}{n}_i/\mathrm{num}(j=\mathrm{1,2},...,\mathrm{Ns}),$ n _iFor having the pixel count of gray level i, num is the total pixel number of a field picture; Second kind of situation is to calculate interior gray-scale value sampling step length ST ' between each sub-gray area _j=(k _2j-k _2j-1)/(M _j+ 1);

Then, according to the sampling step length calculating sampling gray-scale value between each sub-gray area, handle equally in two kinds of situation in this course, first kind of situation be, begins sampling step length ST by separately from the cumulative probability density of left margin gray-scale value correspondence between each sub-gray area _jChoose M _jIndividual sampled point can obtain N-1 sampled point after handling between all sub-gray areas, the cumulative probability density according to sampled point obtains N-1 sampling gray-scale value, G again _I+1=j, ifCDF _j≤ P _i≤ CDF _J+1(i=1,2 ..., N-1; J=0,1 ..., 254), wherein, CDF _jBe the cumulative probability density of gray scale j, ${\mathrm{CDF}}_j=\underset{i=0}{\overset{j}{\mathrm{\&Sigma;}}}{n}_i/\mathrm{num},$ P _iBe the cumulative probability density of i sampled point; Second kind of situation be, begins sampling step length ST ' by separately from the left margin gray-scale value between each sub-gray area _jDirectly choose M _jIndividual gray-scale value after handling between all sub-gray areas, can obtain N-1 sampling gray-scale value; After obtaining two groups of sampling gray-scale values, according to M _jThe sampling gray-scale value finally chosen in selecting between each sub-gray area of size, work as M _j≤ M _aThe time, M _aBe the preset threshold value parameter, choose sampling gray-scale value that first kind of situation obtain as the sampling gray-scale value of finally choosing between j sub-gray area, otherwise, choose sampling gray-scale value that second kind of situation obtain as the sampling gray-scale value of finally choosing between j sub-gray area; Adding at last is zero gray-scale value and gray-scale value k _2Ns, can obtain N+1 required gray-scale value G=[G ₁..., G _N+1];

At last, according to the N+1 that calculates a required gray-scale value G=[G ₁..., G _N+1], calculate N sub-field code weights SF=[SF according to simple accumulation formula light-emitting mode ₁, SF ₂..., SF _N], scan electrode driving circuit and keep the sub-field code weights SF of electrode drive circuit according to present image, produce each height field corresponding maintenance drive waveforms and control signal, scan electrode driving circuit and keep electrode drive circuit and adjust the pulse number of keeping of each height field according to sub-field code weights SF is promptly according to the pulse number of keeping of each son of proportional distribution of each height field weights; Simultaneously the addressing electrode driving circuit receives the view data that is used to show by sub-field code, and with scanning with keep electrode drive circuit and work in coordination and finish the addressing operation of AC PDP according to simple accumulation light-emitting mode.

2, a kind of adaptive subfield coding of alternating current plasma display panels generation device, comprise input picture intensity profile probability density counting circuit (1), threshold parameter counting circuit (2), main gray scale interval selection circuit (3), proportion counting circuit (4) between each sub-gray area, gray-scale value number of samples counting circuit (5) between each sub-gray area, the sampling step length counting circuit one (6) between each sub-gray area, the sampling step length counting circuit two (7) between each sub-gray area, sampled point selecting circuit (8) between each sub-gray area, sampling gray-scale value counting circuit one (9), sampling gray-scale value counting circuit two (10), the sampling gray-scale value is selected circuit (11), sub-field code weights counting circuit (12); It is characterized in that:

Input picture intensity profile probability density counting circuit (1) is connected with main gray scale interval selection circuit (3) with threshold parameter counting circuit (2) respectively, threshold parameter counting circuit (2) is connected with main gray scale interval selection circuit (3), proportion counting circuit (4) is connected between main gray scale interval selection circuit (3) and each sub-gray area, between each sub-gray area between proportion counting circuit (4) and each sub-gray area gray-scale value number of samples counting circuit (5) be connected, gray-scale value number of samples counting circuit (5) sampling step length counting circuit one (6) respectively and between each sub-gray area between each sub-gray area, sampling step length counting circuit two (7) selects circuit (11) to be connected with the sampling gray-scale value between each sub-gray area, between each sub-gray area between sampling step length counting circuit one (6) and each sub-gray area sampled point selecting circuit (8) be connected, sampled point selecting circuit (8) is connected with sampling gray-scale value counting circuit one (9) between each sub-gray area, sampling step length counting circuit two (7) is connected with sampling gray-scale value counting circuit two (10) between each sub-gray area, sampling gray-scale value counting circuit one (9) and sampling gray-scale value counting circuit two (10) are connected to the sampling gray-scale value simultaneously and select circuit (11), and the sampling gray-scale value selects circuit (11) to be connected with sub-field code weights counting circuit (12).

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