CN102238315A - Video stream contrast regulation method - Google Patents
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Abstract
The invention discloses a video stream contrast regulation method, which comprises the following steps of: firstly, computing an average pixel luminance value of a current frame of a video stream; secondly, defining an average value parameter and an initial learning parameter according to the average pixel luminance value of the current frame; thirdly, defining a projected curve according to the initial learning parameter, the average value parameter and the smallest pixel luminance value in the current frame; fourthly, computing a learning parameter according to the projected curve; fifthly, regulating the projected curve according to the learning parameter; and finally, regulating the contrast of the current frame according to the regulated projected curve.
Description
Technical field
The invention relates to a kind of image treatment method, and particularly relevant for a kind of contrast method of adjustment of video flowing.
Background technology
Along with people are more and more high for the requirement of digitized video quality, the progress of digitized video treatment technology is also maked rapid progress.Thereby develop and many digitized video treatment technologies, no matter for crossing dark or bright excessively image, as long as handle, just can promote contrast (Contrast), the brightness (Luminance) and color saturation (Saturation) of digitized video through suitable digitized video ... Deng.
Then often utilize change (Histogram Equalization) technology such as histogram to strengthen the image contrast in the conventional art, also can adjust image brilliance simultaneously.Changes such as histogram briefly are exactly the picture element brightness value of redistributing whole image, make the brightness of whole image and contrast obtain the more distribution of balance.In other words can allow originally dark partially or bright partially image obtains than color range normally.For example cross dark image, the brightness that can improve image after the changes such as use histogram, thereby the contrast of raising image; Otherwise cross bright image, can reduce the brightness of image after the changes such as use histogram, thereby improve the contrast of image.
Fig. 1 illustrates and is traditional contrast method of adjustment flow chart.Please refer to Fig. 1, at first, the histogram of input image is divided into the zone (step S102) of three different pixels brightness.What wherein pixel intensity was minimum 1/3rd is a zone, and what pixel intensity was the highest 1/3rd is a zone, and remaining partly is a zone.Then, respectively the histogram of zones of different is carried out histogram etc. and change (step S104).Then, calculate each regional weighted factor (step S106).At last, according to weighted factor and etc. the image brilliance of the histogram adjustment input image after changing to strengthen the contrast (step S108) of input image.
Though the practice of conventional art has promoted the image contrast, has adjusted image brilliance, occurs the problem of image distortion easily.Therefore traditional image contrast's enhancement techniques still has sizable space of improving.
Summary of the invention
The invention provides a kind of contrast method of adjustment of video flowing, the contrast of scalable video stream, and guarantee the stability of video streaming image quality simultaneously.
The present invention proposes a kind of contrast method of adjustment of video flowing, comprising: at first, calculate the pixel intensity average of the present frame of video flowing.Then, according to equal value defined Mean Parameters of the pixel intensity of present frame and initial learn parameter, wherein Mean Parameters is the upper limit that the pixel intensity of present frame strengthens pixel brightness value in the zone.Then, define a mapping curve according to the minimum pixel brightness value in initial learn parameter, Mean Parameters and the present frame.Afterwards, obtain a learning parameter according to mapping curve, wherein learning parameter definition pixel intensity strengthens the pixel intensity enhancing amplitude in the zone, and the initial learn parameter is the initial value of learning parameter.Then, adjust mapping curve according to learning parameter.At last, adjust the contrast of present frame according to adjusted mapping curve.
In one embodiment of this invention, the step of the contrast of above-mentioned adjustment present frame more comprises: make pixel brightness value mapping look-up table according to adjusted mapping curve earlier, and then adjust the contrast of present frame according to pixel brightness value mapping look-up table.
In one embodiment of this invention, more comprise after the above-mentioned step: the learning parameter and the present frame of present frame are carried out an average calculating operation at the learning parameter of the preceding N frame of video flowing according to the channel calculation learning parameter that former frame entered, to obtain learning parameter, wherein N is default positive integer.
In one embodiment of this invention, above-mentioned average calculating operation is the weighted average computing, wherein the pairing weighted value of present frame is greater than the pairing weighted value of each frame wherein of N frame before above-mentioned, and the N frame is wherein big more near the pairing weighted value of the frame of present frame more before above-mentioned.
In one embodiment of this invention, the step of equal value defined Mean Parameters of above-mentioned pixel intensity according to present frame and initial learn parameter comprises: when the pixel intensity average of present frame during less than a lower limit, enter one first channel, Mean Parameters equals the pixel intensity average of present frame in first channel.When the pixel intensity average of present frame during greater than a higher limit, enter a second channel, Mean Parameters equals the pixel intensity average of present frame in second channel.When the pixel intensity average of present frame is between lower limit and higher limit, enter one the 3rd channel, in the 3rd channel Mean Parameters be present frame the pixel intensity average 1/2nd, also or according to the pixel intensity average of present frame 1/2nd and calculate and produce.
In one embodiment of this invention, wherein in first channel, the initial learn parameter is 1, and in second channel, the initial learn parameter is-1, and in the 3rd channel, the initial learn parameter is-1.
In one embodiment of this invention, the step according to the equal value defined Mean Parameters of the pixel intensity of present frame more comprises in the 3rd channel: earlier Mean Parameters is set at present frame the pixel intensity average 1/2nd.Calculate pixel brightness value in the present frame accounts for all pixel numbers less than the pixel number of Mean Parameters a proportion afterwards again.Wherein when proportion during less than a default value, Mean Parameters repeatedly be multiply by a proportion parameter, greater than default value, wherein the proportion parameter is the real number greater than 1 up to proportion.
In one embodiment of this invention, the contrast method of adjustment of video flowing more comprises: when the pixel intensity average of present frame and present frame when the absolute difference of the pixel intensity average of the former frame of video flowing is less than or equal to a reference value, according to the channel calculation learning parameter that former frame entered, and according to learning parameter adjustment mapping curve, to adjust the contrast of present frame according to adjusted mapping curve.
In one embodiment of this invention, the above-mentioned step of obtaining learning parameter according to mapping curve comprises: obtain learning parameter according to the pixel brightness value of the pixel brightness value between an a starting point on the mapping curve and the critical point between the pairing pixel number of present frame and starting point and Mean Parameters at the ratio of the pairing pixel number of present frame, wherein critical point is that slope begins point greater than 1 on the mapping curve.
In one embodiment of this invention, above-mentioned in first channel and second channel starting point be the pairing point of minimum pixel brightness value of present frame, starting point is the breakover point that slope turns negative number to positive number in the 3rd channel.
In one embodiment of this invention, the expression of above-mentioned mapping curve is:
Outdat=indat+g*k* (indat-min_pix_v) * (m-indat), wherein indat is the input pixel brightness value of present frame, outdat is the output pixel brightness value of present frame, g is a learning parameter, k is a reference parameter, min_pix_v is a pixel brightness value minimum in the present frame, and m then is a Mean Parameters, and wherein reference parameter k is got by calculating by pixel brightness value min_pix_v minimum in Mean Parameters m and the present frame.
Based on above-mentioned, the mapping curve that the present invention utilizes adjustment to be tried to achieve by Mean Parameters that present frame defined and initial learn parameter is adjusted the contrast of video flowing.Average computing at the learning parameter of the preceding N frame of video flowing in addition and by learning parameter and present frame, to guarantee the stability of video streaming image quality to present frame.
For above-mentioned feature and advantage of the present invention can be become apparent, embodiment cited below particularly, and conjunction with figs. is described in detail below.
Description of drawings
Fig. 1 illustrates and is traditional contrast method of adjustment flow chart.
Fig. 2 illustrates the contrast method of adjustment flow chart into the video flowing of one embodiment of the invention.
Fig. 3 illustrates the contrast method of adjustment flow chart into the video flowing of another embodiment of the present invention.
Fig. 4 A～Fig. 4 E illustrates and is the pairing brightness histogram example of different pixels brightness average.
Fig. 5 A～Fig. 5 E illustrates the adjusted brightness histogram example into corresponding diagram 4A～Fig. 4 E.
Fig. 6 illustrates the flow chart into the adjustment proportion parameter of one embodiment of the invention.
Fig. 7 A illustrates and is the mapping curve example before the adjustment of first channel of present embodiment.
Fig. 7 B illustrates and is the mapping curve example before the adjustment of the second channel of present embodiment.
Fig. 7 C～7E illustrates and is the mapping curve before the adjustment of the 3rd channel of present embodiment.
Fig. 8 A illustrates the adjusted mapping curve example into first channel of corresponding diagram 7A.
Fig. 8 B illustrates the adjusted mapping curve example into the second channel of corresponding diagram 7B.
Fig. 8 C～8E illustrates the adjusted mapping curve into the 3rd channel of corresponding diagram 7C～7E respectively.
Fig. 9 illustrates the contrast method of adjustment flow chart into the video flowing of another embodiment of the present invention.
[primary clustering symbol description]
S102～S108: the step of traditional contrast method of adjustment
S202～S212, S302～S324: the step of contrast method of adjustment
S502～S510: the method step of adjusting the proportion parameter
Sup_p: starting point
Enh_p: critical point
M: Mean Parameters
Embodiment
Fig. 2 illustrates the contrast method of adjustment flow chart into the video flowing of one embodiment of the invention.Please refer to Fig. 2, at first, calculate the pixel intensity average (step S202) of the present frame of video flowing.Wherein, the pixel intensity average of present frame is meant all pixel brightness values average of present frame, and pixel brightness value can for example be the Y component (that is brightness) in color coded systems such as YIQ, YDbDr, YCg, Cr, YPbPr, YUV, YCbCr.Then, according to equal value defined Mean Parameters of the pixel intensity of present frame and initial learn parameter (step S204).Wherein Mean Parameters is the upper limit that the pixel intensity of present frame strengthens pixel brightness value in the zone, and the initial learn parameter is the initial value of learning parameter, and pixel intensity that its definition pixel intensity strengthens in the zone strengthens amplitude.Mean Parameters and initial learn parameter for example can be divided into a plurality of different channels according to different pixel brightness value distribution scenario and define Mean Parameters and initial learn parameter for according to the setting of pixel brightness value distribution scenario in brightness (GTG) histogram of present frame.
Continue it, define a mapping curve (step S206) according to the minimum pixel brightness value in initial learn parameter, Mean Parameters and the present frame.Then, obtain learning parameter (step S208) according to mapping curve, wherein learning parameter strengthens amplitude in order to the pixel intensity that the definition pixel intensity strengthens in the zone.Adjust mapping curve (step S210) according to learning parameter more afterwards.That is the learning parameter substitution mapping curve by obtaining, to obtain mapping curve through adjusting.At last, adjust the contrast (step S212) of present frame again according to adjusted mapping curve.Just the pixel brightness value of present frame is shone upon and obtain new pixel brightness value according to adjusted mapping curve, make part dark excessively in the present frame improve brightness (that is to the expansion of bright place), and bright excessively local dimming (that is to dark place expansion), so that the distribution of pixel brightness value tends to balance, allow the contrast of present frame be improved.
Fig. 3 illustrates the contrast method of adjustment flow chart into the video flowing of another embodiment of the present invention.Please refer to Fig. 3, present embodiment is judged histogram whether similar (step S316) according to the pixel intensity average of present frame and present frame in the difference of the pixel intensity average of the former frame of video flowing after the pixel intensity average (step S302) of the present frame that calculates video flowing.For instance, if the absolute value of the difference of the pixel intensity average of the pixel intensity average of present frame and former frame then judge the histogram of present frame and the histogram dissmilarity of former frame, that is histogram has produced bigger variation greater than default reference value.And when the absolute value of the difference of the pixel intensity average of the pixel intensity average of present frame and former frame is less than or equal to above-mentioned reference value, judge that the histogram of present frame is similar to the histogram of former frame, histogram does not produce bigger variation.
Wherein, when the histogram of the histogram of judging present frame and former frame is dissimilar, just follow execution in step S304, according to equal value defined Mean Parameters of the pixel intensity of present frame and initial learn parameter.For instance, rejudge channel, can allow present frame enter three different channels such as first～the 3rd channel, define Mean Parameters and initial learn parameter according to the pixel intensity average size of present frame.Fig. 4 A～Fig. 4 E illustrates and is the brightness histogram example before above three pairing adjustment of different channels.Please refer to Fig. 4 A～4E, Fig. 4 A is the brightness histogram example before the pairing adjustment of first channel, in first channel, the pixel intensity average of present frame is less than a default lower limit, the brightness that can be found out present frame by Fig. 4 A is dark partially, that is the brightness of most pixel is dark all partially in the present frame, therefore needs to increase the brightness of pixel dark partially in the present frame, to promote the contrast of present frame.Set the pixel intensity average that Mean Parameters equals present frame this moment, and the initial learn parameter setting is 1.
Fig. 4 B is the pairing brightness histogram example of second channel, in second channel, the pixel intensity average of present frame is greater than a default higher limit, the brightness that can be found out present frame by Fig. 4 B is bright partially, that is the brightness of most pixel is bright all partially in the present frame, therefore need reduce the brightness (that is to dark place expansion) of pixel bright partially in the present frame, to promote the contrast of present frame.Set the pixel intensity average that Mean Parameters equals present frame this moment, and the initial learn parameter is-1.
Fig. 4 C～4E is the pairing brightness histogram example of the 3rd channel, in the 3rd channel, the pixel intensity average of present frame can be found out that by Fig. 4 C and 4D the contrast of present frame is good than Fig. 4 A and 4B between lower limit and higher limit, but still has the space of reinforcement.As in Fig. 4 C and Fig. 4 D, the pixel in the elliptic region scope can being dimmed (that is to dark place expansion), to promote the contrast of present frame.In addition, in Fig. 4 E,, and make that the darker zone of brightness does not have corresponding pixel in the histogram, the pixel in the elliptic region scope can be dimmed this moment, to promote the contrast of present frame because the pixel brightness of present frame too concentrates on histogrammic centre.
The Mean Parameters deciding means of the 3rd channel can be shown in the flow chart of the adjustment proportion parameter of Fig. 6.At first, setting Mean Parameters is 1/2nd (step S602) of the pixel intensity average of present frame.Then, calculate pixel brightness value in the present frame accounts for all pixel numbers less than the pixel number of Mean Parameters proportion (step S604).Then, judge that whether this proportion is greater than a default value (step S606).If proportion greater than a default value, is then set the Mean Parameters that this Mean Parameters is the 3rd channel (step S608).If proportion is during less than a default value, then Mean Parameters be multiply by a proportion parameter (step S610), and get back to step S606, up to obtaining the Mean Parameters of proportion greater than default value, wherein the proportion parameter is the real number greater than 1, and the initial learn parameter of the 3rd channel is-1.
For instance, suppose that above-mentioned default value is 0.1, the proportion parameter is 1.25, and pixel brightness value is 0.05 o'clock less than the proportion that the pixel number of Mean Parameters accounts for all pixel numbers in the present frame, then Mean Parameters is repeated multiply by the proportion parameter, so that multiply by the pairing proportion of Mean Parameters after the proportion parameter greater than default value (0.1), and product that will this moment is as Mean Parameters.
After having determined Mean Parameters and initial learn parameter, then according to initial learn parameter and Mean Parameters definition mapping curve (step S306).Wherein, the expression of mapping curve can be as shown in following:
outdat＝indat+g*k*(indat-min_pix_v)*(m-indat) (1)
Wherein indat is the input pixel brightness value of present frame, pixel brightness value before just adjusting, outdat is the output pixel brightness value of present frame, just adjusted pixel brightness value, g is a learning parameter, and aforesaid initial learn parameter is the initial value of g, and k is a reference parameter, min_pix_v is a pixel brightness value minimum in the present frame, and m then is a Mean Parameters.Wherein reference parameter k can following formula try to achieve:
k＝1/(m-min_pix_v) (2)
And then with each the pixel brightness value substitution mapping curve in the pixel brightness value scope of present frame obtaining initial mapping curve (step S308), and obtain real learning parameter g (step S310) according to this mapping curve.For instance, Fig. 7 C～7E illustrates and is the mapping curve before the adjustment of the 3rd channel of present embodiment.Fig. 8 C～8E illustrates the adjusted mapping curve into the 3rd channel of corresponding diagram 7C～7E respectively.Please refer to Fig. 7 C, the pixel brightness value scope of supposing present frame is 0～255, with the above-mentioned formula of pixel brightness value 0～255 substitution (1), and with after the initial learn parameter substitution g, can obtain the mapping curve of Fig. 7 C.The mapping curve of Fig. 7 C comprises the point of a starting point sup_p, a critical point enh_p and Mean Parameters m correspondence, and wherein starting point sup_p is the lower limit that the pixel intensity of present frame strengthens pixel brightness value in the zone.Starting point sup_p is the breakover point that the slope of mapping curve turns negative number to positive number in the present embodiment, and just slope is zero position, and critical point enh_p is that slope begins point greater than 1 on the mapping curve.Above-mentioned learning parameter g utilizes the pixel brightness value of pixel brightness value between the pairing pixel number of present frame and starting point sup_p and Mean Parameters m between starting point sup_p and the critical point enh_p to obtain at the ratio of the pairing pixel number of present frame, and its detailed formula is as follows:
g＝2*rate-1 (3)
Wherein rate is the pixel brightness value of pixel brightness value between the pairing pixel number of present frame and starting point sup_p and Mean Parameters m between starting point sup_p and the critical point enh_p at the ratio of the pairing pixel number of present frame.Afterwards, just can adjust mapping curve (step S312) according to learning parameter g.The learning parameter g substitution mapping function (1) that also is about to formula (3) gained just can obtain the adjusted mapping curve shown in Fig. 8 C.Can be found out that by Fig. 8 C the pixel brightness value between starting point sup_p and Mean Parameters m obviously is enhanced, pixel brightness value 0 is then dragged down to the pixel brightness value between the starting point sup_p.Thus, just can adjust the contrast (step S314) of present frame according to adjusted mapping curve.
Fig. 5 A～Fig. 5 E illustrates the adjusted brightness histogram example into corresponding diagram 4A～Fig. 4 E.After the pixel brightness value distribution scenario of pixel is readjusted in the present frame, shown in Fig. 5 C, can find out the situation of launching the oriented dark place of the pixel that is distributed among Fig. 4 C in the elliptic region scope (that is brightness deepening of the interior pixel of elliptic region scope), and make the pixel balance more of each pixel brightness value correspondence in the whole pixel brightness value zone, the contrast of present frame thereby raising.
In addition, the mapping curve of Fig. 7 D and Fig. 7 E can also identical mode be adjusted and is obtained the adjusted mapping curve of Fig. 8 D and Fig. 8 E respectively, adjusts the corresponding brightness histogram in back then shown in Fig. 5 D and Fig. 5 E.Also can find out the situation of launching the oriented dark place of the pixel that is distributed among Fig. 4 D and the 4E in the elliptic region scope (that is brightness deepening of the interior pixel of elliptic region scope) by Fig. 5 D and 5E, and make that the contrast of present frame is promoted.
Fig. 7 A and Fig. 7 B illustrate respectively and are the mapping curve example before the adjustment of first and second channel of present embodiment.The method place different with the 3rd channel of adjusting mapping curve in first channel and the second channel be, first and second channel in, starting point sup_p is the pairing point of minimum pixel brightness value in the present frame in the present embodiment.Remainder is similar to the 3rd channel paradigm of Fig. 7 C and Fig. 8 C, just elder generation is with the mapping function of initial learn parameter g substitution formula (1), obtain initial mapping curve, calculate real learning parameter g with formula (3), then with the learning parameter g substitution mapping function (1) of formula (3) gained to obtain adjusted mapping curve.And by the adjusted mapping curve figure shown in Fig. 8 A and Fig. 8 B, promote with the contrast that also can find out present frame as brightness histogram corresponding after Fig. 5 A and the adjustment shown in Fig. 5 B.Wherein the situation of launching at the oriented bright place of the pixel that is distributed among Fig. 4 A in the elliptic region scope (that is the brightness of pixel brightens in the elliptic region scope) can be found out, and the situation of launching the oriented dark place of the pixel that is distributed among Fig. 4 B in the elliptic region scope (that is brightness deepening of the interior pixel of elliptic region scope) can be found out by Fig. 5 B by Fig. 5 A.
Get back to step S316, when judging present frame when similar, then according to channel calculation learning parameter (step S318) that former frame entered to the histogram of former frame.That is to say, the channel that decides present frame to enter according to the pixel intensity average of present frame not, but allow present frame enter the channel identical with former frame, determine the learning parameter g of Mean Parameters m and formula (3) according to this.Next, the learning parameter that will get according to formula (3) calculating and the learning parameter of preceding N frame average computing (step S320), and wherein N is default positive integer.For instance, the learning parameter of being tried to achieve among the learning parameter of preceding 4 frames and the step S318 can be averaged computing to obtain a new learning parameter.Above-mentioned further average calculating operation can be the weighted average computing, and wherein the pairing weighted value of present frame is greater than the pairing weighted value of each frame wherein of N frame before above-mentioned, and the N frame is wherein big more near the pairing weighted value of the frame of present frame more before above-mentioned.Thus, can make the frame far away more more little to the influence degree of present frame apart from present frame.Above-mentioned learning parameter average calculating operation can allow the contrast adjustment of video flowing tend towards stability, and avoids flicker.
It should be noted that in addition, step S320 is the step of just carrying out when the histogram of present frame is similar to the histogram of former frame, also even step S316 judges the histogram of present frame and the histogram dissmilarity of former frame, then can execution in step S320, and the frame that averages computing all has similar histogram, if when execution in step S320, have similar histogrammic frame number when not reaching the N frame, can average computing according to having similar histogrammic frame number at present.For example, 3 frames are only arranged, just the learning parameter of present frame and preceding 3 frames can be averaged computing, to obtain new learning parameter and have similar histogrammic frame number if setting N is 4.
After determining learning parameter, just can follow according to learning parameter and adjust mapping curve (step S312).Under the similar situation of the histogram of the histogram of present frame and former frame, present embodiment is that the learning parameter g substitution formula (1) of above-mentioned average calculating operation gained is obtained adjusted mapping curve.
No matter whether the histogram of the histogram of present frame and former frame is similar, next is the contrast (step S314) of adjusting present frame according to adjusted mapping curve.Step S314 can be divided into two steps in the present embodiment, at first, make pixel brightness value mapping look-up table (step S322) according to adjusted mapping curve, each input pixel brightness value indat and its output pixel brightness value outdat corresponding on mapping curve of this look-up table record present frame.Then adjust the contrast (step S324) of present frame according to pixel brightness value mapping look-up table, just each pixel brightness value with present frame converts corresponding outdat to from indat.And in part embodiment, also the way of step S314 also can be able to be utilized in Fig. 3 step pixel brightness value minimum in resulting input pixel brightness value indat, learning parameter g, reference parameter k and the present frame etc., be calculated the output pixel brightness value outdat of present frame according to formula (1).
It should be noted that in addition, in Fig. 3 embodiment, the step of step S320 for when the histogram of present frame is similar to the histogram of former frame, just carrying out, so in part embodiment, also can whether similar to the histogram of former frame regardless of the histogram of present frame, all the learning parameter that will get according to formula (3) calculating and the learning parameter of preceding N frame average computing.The contrast method of adjustment flow chart of the video flowing of another embodiment as shown in Figure 9, the difference of the embodiment of itself and Fig. 3 is that step S320 is between step S310 and step S312.That is to say, the learning parameter of obtaining according to mapping curve in step S310 will average computing (that is step S320) with the learning parameter of preceding N frame, and then then adjust mapping curve (that is step S312) according to averaging the learning parameter of trying to achieve after the computing.So can increase the stability of video flowing, make the quality of image more stable.
No matter be the frame that bright or too dark brightness are crossed in brightness, utilize the contrast method of adjustment of the embodiment of the invention all can obviously improve the contrast that promotes picture, make the more approaching real scene of picture.
In sum, the present invention utilizes Mean Parameters and initial learn parameter to try to achieve mapping curve, utilizes the shape of mapping curve and the number of pixels ratio of present frame to adjust mapping curve then.Adjusted mapping curve can make the pixel of present frame more be evenly distributed on each pixel brightness value, and makes the contrast of present frame improve.Have similar histogrammic successive frame and enter same channel in addition and by allowing, and the learning parameter of successive frame is averaged computing,, avoid the flicker problem of conventional art to guarantee the stability of video streaming image quality.The present invention can be applicable to the display unit of Portable media player, network media player or projecting apparatus and so on.
Though the present invention discloses as above with embodiment; right its is not in order to limit the present invention; have in the technical field under any and know the knowledgeable usually; without departing from the spirit and scope of the present invention; when doing a little change and retouching, so protection scope of the present invention is worked as with being as the criterion that claim was defined.
Claims (11)
1. the contrast method of adjustment of a video flowing comprises:
Calculate the pixel intensity average of a present frame of a video flowing;
According to equal value defined one Mean Parameters of the pixel intensity of this present frame and an initial learn parameter, wherein this Mean Parameters is the upper limit that a pixel intensity of this present frame strengthens pixel brightness value in the zone;
Define a mapping curve according to the minimum pixel brightness value in this initial learn parameter, this Mean Parameters and this present frame;
Obtain a learning parameter according to this mapping curve, wherein this learning parameter defines the pixel intensity enhancing amplitude in this pixel intensity enhancing zone, and the initial value that this initial learn parameter is this learning parameter;
Adjust this mapping curve according to this learning parameter; And
Adjust the contrast of this present frame according to adjusted this mapping curve.
2. contrast method of adjustment as claimed in claim 1 is characterized in that, the step of adjusting the contrast of this present frame more comprises:
Make pixel brightness value mapping look-up table according to adjusted this mapping curve; And
Adjust the contrast of this present frame according to this pixel brightness value mapping look-up table.
3. contrast method of adjustment as claimed in claim 1 is characterized in that, more comprises adjust the step of this mapping curve according to this learning parameter before:
Learning parameter and this present frame of this present frame are carried out an average calculating operation at the learning parameter of the preceding N frame of this video flowing, and to obtain this learning parameter, wherein N is default positive integer.
4. contrast method of adjustment as claimed in claim 3, it is characterized in that, this average calculating operation is the weighted average computing, the pairing weighted value of this present frame is greater than the pairing weighted value of each frame wherein of N frame before above-mentioned, and the N frame is wherein big more near the pairing weighted value of the frame of this present frame more before above-mentioned.
5. contrast method of adjustment as claimed in claim 1 is characterized in that, comprises according to the step of this Mean Parameters of the equal value defined of the pixel intensity of this present frame and this initial learn parameter:
When the pixel intensity average of this present frame during less than a lower limit, enter one first channel, this Mean Parameters equals the pixel intensity average of this present frame in this first channel;
When the pixel intensity average of this present frame during greater than a higher limit, enter a second channel, this Mean Parameters equals the pixel intensity average of this present frame in this second channel; And
When the pixel intensity average of this present frame is between this lower limit and this higher limit, enter one the 3rd channel, in the 3rd channel this Mean Parameters be this present frame the pixel intensity average 1/2nd, also or according to the pixel intensity average of this present frame 1/2nd and calculate and produce.
6. contrast method of adjustment as claimed in claim 5 is characterized in that, in this first channel, this initial learn parameter is 1, and in this second channel, this initial learn parameter is-1, and in the 3rd channel, this initial learn parameter is-1.
7. contrast method of adjustment as claimed in claim 5 is characterized in that, in the 3rd channel, more comprises according to the step of equal this Mean Parameters of value defined of the pixel intensity of this present frame:
This Mean Parameters is set at this present frame the pixel intensity average 1/2nd;
Calculate pixel brightness value in this present frame accounts for all pixel numbers less than the pixel number of this Mean Parameters a proportion; And
When this proportion during less than a default value, this Mean Parameters repeatedly be multiply by a proportion parameter, greater than this default value, wherein this proportion parameter is the real number greater than 1 up to this proportion.
8. contrast method of adjustment as claimed in claim 5 is characterized in that, more comprises;
When the pixel intensity average of this present frame and this present frame when the absolute difference of the pixel intensity average of the former frame of this video flowing is less than or equal to a reference value, according to this learning parameter of channel calculation that this former frame entered, and adjust this mapping curve according to this learning parameter, to adjust the contrast of this present frame according to adjusted this mapping curve.
9. contrast method of adjustment as claimed in claim 5 is characterized in that, the step of obtaining this learning parameter according to this mapping curve comprises:
Obtain this learning parameter according to the pixel brightness value of the pixel brightness value between an a starting point on this mapping curve and the critical point between the pairing pixel number of this present frame and this starting point and this Mean Parameters at the ratio of the pairing pixel number of this present frame, wherein this critical point begins point greater than 1 for slope on this mapping curve.
10. contrast method of adjustment as claimed in claim 5, it is characterized in that, this starting point is the pairing point of minimum pixel brightness value of this present frame in this first channel and this second channel, and this starting point is the breakover point that slope turns negative number to positive number in the 3rd channel.
11. contrast method of adjustment as claimed in claim 1 is characterized in that, the expression of this mapping curve is:
outdat＝indat+g*k*(indat-min_pix_v)*(m-indat)
Wherein indat is the input pixel brightness value of this present frame, outdat is the output pixel brightness value of this present frame, g is this learning parameter, k is a reference parameter, min_pix_v is a pixel brightness value minimum in this present frame, m is this Mean Parameters, and wherein this reference parameter k serves as reasons, and minimum pixel brightness value min_pix_v calculates and gets in this Mean Parameters m and this present frame.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103780892A (en) * | 2012-10-25 | 2014-05-07 | 鸿富锦精密工业（深圳）有限公司 | White balancing adjustment method |
| CN108241868A (en) * | 2016-12-26 | 2018-07-03 | 浙江宇视科技有限公司 | The objective similarity of image is to the mapping method and device of subjective similarity |
| CN110049225A (en) * | 2018-01-15 | 2019-07-23 | 瑞昱半导体股份有限公司 | Contrast enhanced method and device thereof based on Histogram adjustment |
| CN112465729A (en) * | 2020-12-11 | 2021-03-09 | 四川长虹电器股份有限公司 | Method for dynamically adjusting image contrast based on television histogram |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103780892A (en) * | 2012-10-25 | 2014-05-07 | 鸿富锦精密工业（深圳）有限公司 | White balancing adjustment method |
| CN108241868A (en) * | 2016-12-26 | 2018-07-03 | 浙江宇视科技有限公司 | The objective similarity of image is to the mapping method and device of subjective similarity |
| CN108241868B (en) * | 2016-12-26 | 2021-02-02 | 浙江宇视科技有限公司 | Method and device for mapping objective similarity to subjective similarity of image |
| CN110049225A (en) * | 2018-01-15 | 2019-07-23 | 瑞昱半导体股份有限公司 | Contrast enhanced method and device thereof based on Histogram adjustment |
| CN110049225B (en) * | 2018-01-15 | 2021-01-05 | 瑞昱半导体股份有限公司 | Contrast enhancement method and device based on histogram adjustment |
| CN112465729A (en) * | 2020-12-11 | 2021-03-09 | 四川长虹电器股份有限公司 | Method for dynamically adjusting image contrast based on television histogram |
| CN112465729B (en) * | 2020-12-11 | 2022-07-08 | 四川长虹电器股份有限公司 | Method for dynamically adjusting image contrast based on television histogram |
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