CN1809121A - Methods of Enhancing Image Contrast - Google Patents
- ️Wed Jul 26 2006
CN1809121A - Methods of Enhancing Image Contrast - Google Patents
Methods of Enhancing Image Contrast Download PDFInfo
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- CN1809121A CN1809121A CN200610004232.XA CN200610004232A CN1809121A CN 1809121 A CN1809121 A CN 1809121A CN 200610004232 A CN200610004232 A CN 200610004232A CN 1809121 A CN1809121 A CN 1809121A Authority
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Abstract
An image processing method is to count the number of the original gray values according to the original gray value difference between each pixel and its adjacent pixels in a picture, and to determine the contrast enhancement degree of the picture according to the counted number of the gray values and the contrast variation range of the two pictures.
Description
Technical field
The present invention relates to a kind of method of image processing, and particularly relevant for a kind of method of strengthening image contrast.
Background technology
The method of in the past strengthening image contrast only is number to occur by the gray value of adding up each pixel in the picture, decides the degree of strengthening this picture contrast.Yet this kind method only can promote the image contrast in the picture under certain specific situation.But need most under the situation of strengthening contrast at some, when for example watching the DVD film, can the tell on image of extreme difference of the method that this kind strengthened image contrast.Picture view when as shown in Figure 1, it is the DVD playing back film.The DVD film when playing mostly with 16: 9
ratio display frame100, so all can show black picture at the two part UP up and down and the DP of display frame 100 (for example lcd screen).Thus, the method for in the past strengthening image contrast can be because of adding up into UP when this
picture100 being done contrast and strengthen with the gray value of DP two black picture partly, and cause the strengthened
picture100 of contrast to seem that the utmost point is natural.In addition, when the gray value statistic curve difference of front and back two pictures is excessive, the method for reinforcement image contrast in the past will cause the phenomenon of image frame flicker.
Therefore, how can also keep the image natural characteristic when strengthening contrast and to avoid the phenomenon of image frame flicker is the problem that need solve at present.
Summary of the invention
In view of this, the purpose of this invention is to provide a kind of image treatment method, it is to strengthen the contrast of an image and keep the stable of image frame under the condition of keeping the image natural characteristic.
According to purpose of the present invention, a kind of image treatment method is proposed.This image is presented by one first picture f (N) at least.This first picture f (N) is made up of a plurality of pixel.Each pixel corresponds to an original gray value respectively, and image treatment method of the present invention is described below.Count original gray value according to the difference of adjacent two pixels original gray value to each other and number occurs, and represent with one first transfer function F (X).Calculate a gamma curve according to this first transfer function F (X), and optionally to adjust these original gray value according to this gamma curve be the whole back of many styles gray values.The step that number appears in wherein above-mentioned these original gray value of statistics also comprises: when one second original gray value difference of one first original gray value of one first pixel in these pixels and adjacent one second pixel during greater than n, n is 0 or positive integer, the statistics number of all original gray value between first original gray value and second original gray value or partly a statistics number average of original gray value add 1.
For above-mentioned purpose of the present invention, feature and advantage can be become apparent, a preferred embodiment cited below particularly, and be described with reference to the accompanying drawings as follows.
Description of drawings
Picture view when Fig. 1 is the DVD playing back film.
Fig. 2 is the flow chart of the image treatment method of preferred embodiment of the present invention.
Fig. 3 A is the schematic diagram of a certain existing picture (unspecified current frame).
Fig. 3 B is original gray value number statistics schematic diagram.
Fig. 3 C is original gray value number statistics schematic diagram.
Fig. 4 A is for calculating the flow chart of gamma curve.
Fig. 4 B is for calculating the schematic diagram of gamma curve.
Fig. 5 is for adjusting the partly schematic diagram of upper lower limit value of the 3rd transfer function.
Embodiment
The present invention proposes a kind of image treatment method, and it is to strengthen the contrast of an image and keep the stable of image frame under the condition of keeping the image natural characteristic.Image treatment method of the present invention is poor according to the original gray value that each pixel is adjacent between pixel, add up these original gray value and number occurs, also decide the contrast reinforcement degree of existing picture afterwards according to the contrast amplitude of fluctuation of gray value number that is counted and front and back two pictures.
Please refer to Fig. 2, it is the flow chart of the image treatment method of preferred embodiment of the present invention.One image is presented by many picture f (N), and N is a positive integer.Each picture f (N) is made up of a plurality of pixel, for example is made up of 1028*768 pixel.Each pixel corresponds to an original gray value (graylevel) GL respectively.Image treatment method of the present invention comprises the following steps.In step 200, poor according to the original gray value that each pixel is adjacent between pixel, add up that number appears in these original gray value and with the first transfer function F i(X) expression, i is the positive integer between 1 to N.In step 202, according to the first transfer function F i(X) calculate a gamma curve (Gamma Curve).In step 204, optionally adjusting these original gray value according to this gamma curve is the whole back of many styles gray value afterwards.
The statistical method of furthermore bright step 200.Please refer to Fig. 3 A, it is the schematic diagram of a certain existing picture (unspecified current frame).One first picture f (1) is a certain picture in the image.A pixel P is represented in each space among the first picture f (1), and the original gray value GL that each pixel P of the digitized representation that is indicated in the space is corresponded to.Illustrate that with upper left corner 3*3 pixel P (1) among the first picture f (1)~P (9) principle of number appears in the original gray value of statistics this first picture f (1).This principle is: " when each pixel and neighbor original gray value difference to each other during; n is 0 or a predetermined value of positive integer greater than n, the statistics number of all original gray value between the original gray value that original gray value that each pixel corresponded to and neighbor are corresponded to or partly a statistics number average of original gray value add 1." be 0 and be example explanation that with n the 9th pixel P9 and the 6th pixel P6 and the 8th pixel P8 are adjacent with the 9th pixel P9.The 9th pixel P9 and the 6th pixel P6 original gray value difference to each other are 21 gray scales (95-74=21>0), so with all original gray value of 74 to 95 of original gray value (74,75,76 ... 94,95) a statistics number average add 1, the solid arrow that is indicated as Fig. 3 B.Fig. 3 B is original gray value number statistics schematic diagram.And the 9th pixel P9 and the 8th pixel P8 original gray value difference to each other are 19 gray scales (93-74=19>0), so with all original gray value of 74 to 93 of original gray value (74,75 ... 92,93) the statistics number add 1 again, the dotted arrow that is indicated as Fig. 3 B.Every original gray value GL to pixel P1~P9 takes statistics and will obtain the part gray value number statistical chart of this first picture f (1) with this principle, and promptly shown in Fig. 3 C, it is original gray value number statistics schematic diagram.
Compared to way (number appears in the original gray value that promptly only is each pixel in the statistics picture) in the past, statistics principle of the present invention is considered neighbor original gray value difference to each other.So, the first transfer function F that comes out i(X) consider the grey value difference of image edge in the picture, make according to this first transfer function F i(X) gamma curve of being obtained, its image of revising is more natural in the performance of contrast.In addition, said n also can be 1 or other positive integer, and a statistics number average of the part original gray value between the original gray value that statistical can also be original gray value that each pixel is corresponded to and neighbor to be corresponded to adds 1.With the 9th pixel P9 and the 8th pixel P8 is example, the statistics number that can be 2 part original gray value with the difference of 74 to 95 of original gray value adds 1, for example 74,76,78...92,94,95, with this rule, can select the original gray value difference be 3,4 or the part original gray value of other difference be objects of statistics, the present invention does not limit to the value of difference.
Then explanation calculates the method for gamma curve.With above-mentioned statistical the original gray value of all pixels of the first picture f (1) is done statistics to obtain the first transfer function F 1(X) after, obtain a gamma curve G (X) via suitably calculating in step 202.Please be simultaneously with reference to Fig. 4 A and Fig. 4 B.Fig. 4 A is for calculating the flow chart of gamma curve.Fig. 4 B is for calculating the schematic diagram of
gamma curve.In step400, the linear transformation first transfer function F i(X).In order to limit the first transfer function F i(X) scope of output valve, the linear transformation first transfer function F i(X), for example to the first transfer function F 1(X) open radical sign.Then in
step402, (accumulate) first transfer function F after the linearity conversion adds up i(X), to obtain one second transfer function F ' i(X).In
step404, standardization (normalize) the second transfer function F ' i(X), to obtain one the 3rd transfer function F " i(X).For example with the second transfer function F ' of the first picture f (1) 1(X) statistics number is normalized to maximum gradation value (for example 255 gray scales), to obtain the 3rd transfer function F " 1(X).Then in
step406, with the 3rd transfer function F " i(X) be multiplied by K and add a parameter P (X) to obtain a gamma curve G (X).Wherein this parameter P (X) for example is the curve of 1-K for slope shown in Fig. 4 B, and K is the arbitrary value between 0~1, but chosen in advance.So far, can calculate the gamma curve G of the first picture f (1) 1(X).Calculate gamma curve G 1(X) after, just can be according to gamma curve G 1(X) the original gray value GL of the adjustment first picture f (1).
Because the first transfer function F 1(X) consider the grey value difference of image edge in the picture, therefore when the first picture f (1) is 16: 9 DVD film, according to this gamma curve G 1(X) the adjusted first picture f (1) will present preferable contrast effect.
In addition,, promptly avoid the violent change of picture brightness and cause the not phenomenon of nature or image flicker of image in order to keep the stationarity of picture, can be by the output valve of the above-mentioned various transfer function F of restriction (X) so that the rate of change of gamma curve be comparatively steady.For example adjust this 3rd transfer function F " i(X) part upper lower limit value is to obtain one the 4th transfer function F i(X).As shown in Figure 5, it is for adjusting the partly schematic diagram of upper lower limit value of the 3rd transfer function.The 3rd transfer function F " (X) for example be multiplied by two transfer function J1 (X) and J2 (X) to get one the 4th transfer function F i(X).As the 3rd transfer function F " during (X) greater than transfer function J1 (X), output transfer function J1 (X), and transfer function F " during (X) less than transfer function J2 (X), output transfer function J2 (X).Afterwards according to this 4th transfer function F i(X) produce another gamma curve G ' (X).For example via above-mentioned
steps406 handle the back be another gamma curve G ' (X).
Perhaps according to the second transfer function F ' i(X) judging whether will be according to the original gray value GL of the existing picture of gamma curve G (X) adjustment.The i.e. second transfer function F ' 1(X) the maximum that adds up is adjusted the original gray value of existing picture during greater than one first default value W1 according to gamma curve G (X).The second transfer function F ' that for example works as the first picture f (1) 1During (X) less than this first default value W1, the number that promptly adds up then defines this first picture f (1) and is level and smooth scene, otherwise be general scene not greater than this default value W1.Under level and smooth scene, do not use above-mentioned gamma curve G 1(X) adjust the original gray value GL of this first picture f (1) so that image frame keeps stable.And under general scene, then use above-mentioned gamma curve G 1(X) adjust the original gray value GL of this first picture f (1).In addition, also can be by gamma curve G 1' (X) adjust the original gray value GL of the first picture f (1) so that image frame keeps stable.
Perhaps, because image is to be presented by a plurality of picture f (N), each picture f (N) all can correspond to an original gray value number statistical chart, the i.e. first transfer function F respectively i(X).Two first transfer function F by two pictures before and after comparing i(X), to judge whether to adjust according to the gamma curve G (X) of the gamma curve G (X) of existing picture or last picture the original gray value GL of existing picture.The gray scale difference that the mode of this comparison can be the same pixel of two pictures before and after the comparison or same pixel region whether outside the predetermined tolerance value or within.With the first picture f (1) and the first picture f (a 1) picture before, one second picture f (0) is the example explanation.The first picture f (1) corresponds to the first transfer function F 1And the second picture f (0) corresponds to another first transfer function F (X), 0(X).At first, the first transfer function F of the integration first picture f (1) 1(X), to obtain a first integral value E1.Follow the first transfer function F with the first picture f (1) 1(X) deduct the first transfer function F of the second picture f (0) 0(X) after, get its absolute value and according to this integration go out a second integral value E2.As the ratio of second integral value E2 and first integral value E1 W2 during greater than one second default value, then look existing the first picture f (1) and have significant difference with the second picture f (0) and exist.When having significant difference, the original gray value GL of the first picture f (1) is according to the first transfer function F 1(X) the gamma curve G that is produced 1(X) adjust, otherwise the original gray value GL of the first picture f (1) is according to the first transfer function F of last picture 0(X) another gamma curve G that is produced 0(X) adjust.
In sum, said method all is according to various multi-form transfer function F i(X) adjust the rate of change of gamma curve or select the gamma curve of last picture, cause the not phenomenon of nature or image flicker of image with the violent change of avoiding picture brightness.
In addition, above-mentioned the third way is the first transfer function F of two picture correspondences before and after the comparison i(X), to judge whether to adjust according to the gamma curve G (X) of the gamma curve G (X) of existing picture or last picture the original gray value GL of existing picture.Also can be by two first pixel transfer function H of two pictures before and after comparing i(X), to judge whether to adjust according to the gamma curve G (X) of the gamma curve G (X) of existing picture or last picture the original gray value GL of existing picture.The first pixel transfer function H i(X) the original gray value number in order to represent that a picture is counted added up in the past promptly that number appears in the original gray value of each pixel in the picture.Furthermore, be that example is done explanation also with the first picture f (1) and the second picture f (0).Add up at first that number appears in every original gray value among the first picture f (1), and with one first pixel transfer function H 1(X) expression; And number appears in every original gray value of adding up the second picture f (0), and also with another second pixel transfer function H N-1(X) expression.Then, the integration first pixel transfer function H N(X), for another first integral value E1 ' afterwards, with the first pixel transfer function H 1(X) with the second pixel transfer function H 0(X) take absolute value after subtracting each other and, think a second integral value E2 ' its integration.When the ratio of second integral value E2 ' and first integral value E1 ' during, then look existing the first picture f (1) and have significant difference with last picture f (0) and exist greater than one the 3rd default value W2.The original gray value GL of the first picture f (1) is according to the first transfer function F at this moment N(X) the gamma curve G (X) that is produced is adjusted into and adjusts back gray value GL ', otherwise the original gray value GL of the first picture f (1) is according to the first transfer function F of last picture 0(X) another gamma curve G (X) that is produced is adjusted into and adjusts back gray value GL '.Therefore, the present invention also can be by statistical in the past, i.e. the first pixel transfer function H i(X), judge that the gamma curve that will use existing picture or last picture adjusts the original gray value GL of existing picture, cause the not phenomenon of nature or image flicker of image with the violent change of avoiding picture brightness.
In addition, no matter original gray value GL is with above-mentioned which kind of gamma curve, for example gamma curve G i(X), G ' i(X), G I-1(X) or G ' I-1(X) adjust after, all might cause some color of pixel to produce colour cast.For example originally present the pixel that is similar to redness, its original RGB gray value GL is (255,12,12).This pixel is after above-mentioned gamma curve is adjusted, and its RGB gray value GL is adjusted to (255,30,30), thereby changes and present pink.Therefore, need, for example reduce the ratio that contrast is strengthened, so that picture f (N) seems more natural via an adjustment that is called " colorimetric purity weight mechanism ".In other words, this mechanism is in order to guarantee: when any color in three kinds of colors of the RGB in the pixel when saturated, can not cause the phenomenon of colour cast because of above-mentioned image treatment method.Promptly avoid the original gray scale GL (255,12,12) of pixel to be adjusted to the situation of (255,30,30).This colorimetric purity weight mechanism is GL New=(GL*max (RGB)+GL ' * (B-max (RGB)))/B.Wherein B is a positive integer, and GL is an original gray value, and GL ' is for example through gamma curve G N(X), G ' N(X), G N-1(X) or G ' N-1(X) adjusted adjustment back gray value GL ', and the max in the formula (RGB) is for getting maximum gray value among the original gray value GL.With original gray value GL be (255,12,12), to adjust back gray value GL ' be that (255,30,30) and B 256 do explanation for example, L then New={ (255,12,12) X255+ (255,30,30) X (256-255) }/256, i.e. GL NewBe similar to (255,12,12).So, as original gray value GL (255,12,12) adjust through above-mentioned various gamma curves after, become by redness originally and to be similar to pink (255,30,30) time, be adjusted into the chroma performance that is similar to originally through colorimetric purity weight machine thus again, the gray value GL after promptly new adjustment is whole New(255,12,12) make picture seem more natural.
After some pixel is adjusted through above-mentioned " colorimetric purity weight mechanism ", the adjusted gray value GL that it is new NewContrast can also transfer higherly more in fact.Therefore the present invention also comprises another colorimetric purity weight mechanism.This colorimetric purity weight mechanism is described below:
GL’ new=(P LC*GL’+P L*GL)/B
Above-mentioned P L=n*max (RGB)+m*color_gap, m+n=1
And P LC=B-P L, color_gap=max (RGB)-min (RGB).Wherein B also is a positive integer, and color_gap gets among the original gray value GL to get the poor of minimum gray value among maximum gray value and the original gray value GL.This colorimetric purity weight mechanism in order to when some color of pixel near when white, promptly the gray value of RGB three looks all very approaching is each other, by this formula enhancing contrast ratio.Promptly by the second colorimetric purity weight mechanism, can be very approaching each other in the gray value of the RGB of some pixel three looks and the gray value of RGB three looks near 255 o'clock, the gray value of also adjusting RGB three looks is with enhancing degree contrast.In other words, this " second colorimetric purity weight mechanism through " first colorimetric purity weight mechanism " adjust after; when the ratio that the ratio of some contrast can be adjusted bigger gray value because " first colorimetric purity weight mechanism " is adjusted and cause contrast descends; again the ratio of contrast is heightened a bit again, so that the contrast of image is more obvious.For example as GL (200,198,202), it is near white.The contrast ratio of this GL (200,198,202) is assumed to be GL after " first colorimetric purity weight mechanism " is adjusted New(211,210,213).But, GL NewThe contrast ratio of (200,198,202) can be higher again, promptly that is to say, contrast is strengthened.Therefore adjust its ratio for bigger via " second colorimetric purity weight mechanism ", the contrast of image is more strengthened.
The image treatment method that the above embodiment of the present invention is disclosed, it is to strengthen the contrast of an image and keep the stable of image frame under the condition of keeping the image natural characteristic.
In sum; though the present invention discloses as above with a preferred embodiment; right its is not in order to limit the present invention; those skilled in the art can be used for a variety of modifications and variations under the premise without departing from the spirit and scope of the present invention, so protection scope of the present invention is as the criterion with claim of the present invention.
Claims (9)
1. image treatment method, this image is presented by one first picture f (N) at least, and this first picture f (N) is made up of a plurality of pixel, and each pixel corresponds to an original gray value respectively, and this image treatment method comprises:
Neighbor original gray value to each other according to each pixel and this pixel is poor, adds up the appearance number of these original gray value, and with one first transfer function F i(X) expression, i is the positive integer between 1 to N;
According to this first transfer function F i(X) calculate a gamma curve; And
Optionally adjusting these original gray value according to this gamma curve is the whole back of many styles gray value.
2. image treatment method as claimed in claim 1, wherein add up the step that number appears in these original gray value and also comprise:
When one second original gray value difference of one first original gray value of one first pixel in these pixels and adjacent one second pixel during greater than n, n is 0 or positive integer, the statistics number of all these original gray value between this first original gray value and this second original gray value or partly a statistics number average of these original gray value add 1.
3. image treatment method as claimed in claim 1, the step that wherein calculates this gamma curve also comprises:
This first transfer function of linear transformation F i(X);
This first transfer function F after linearity conversion adds up i(X), to obtain one second transfer function F ' i(X);
This second transfer function of standardization F ' i(X), to obtain one the 3rd transfer function F " i(X); And
With the 3rd transfer function F " i(X) be multiplied by K and add a parameter P (X) to obtain this gamma curve, this parameter P (X) is the transfer function of 1-K for slope, and K is between 0~1.
4. image treatment method as claimed in claim 1, the step that wherein calculates this gamma curve also comprises:
This first transfer function of linear transformation F i(X);
This first transfer function F after linearity conversion adds up i(X), to obtain one second transfer function F ' i(X);
This second transfer function of standardization F ' i(X), to obtain one the 3rd transfer function F " i(X);
Adjust the 3rd transfer function F " i(X) part upper lower limit value is to obtain one the 4th transfer function F i(X); And
With the 4th transfer function F i(X) be multiplied by K and add a parameter P (X) to obtain this gamma curve, this parameter P (X) is the transfer function of 1-K for slope, and K is between 0~1.
5. as claim 3 or 4 described image treatment methods, wherein adjust these original gray value and also comprise for these steps of adjusting the back gray value:
As this second transfer function F ' i(X) the maximum that adds up is during greater than one first default value, and these original gray value adjust according to this gamma curve.
6. image treatment method as claimed in claim 2, wherein, this image also comprises one second picture f (N-1), this second picture f (N-1) is in the preceding appearance of this first picture f (N), adjusts these original gray value and comprises for these steps of adjusting the back gray value:
This first transfer function F of integration this first picture f (N) N(X), think a first integral value; The first transfer function F with this first picture f (N) N(X) deduct the first transfer function F of this second picture f (N-1) N-1(X) after, take absolute value and according to this integration go out a second integral value; And
When the ratio of this second integral value and this first integral value during greater than one second default value, these original gray value of this first picture f (N) are first transfer function F according to this first picture N(X) be adjusted into these and adjust the back gray value, otherwise these original gray value of this first picture f (N) are first transfer function F according to this second picture f (N-1) N-1(X) be adjusted into these and adjust the back gray value.
7. image treatment method as claimed in claim 2, wherein, this image also comprises one second picture f (N-1), and this second picture f (N-1) is in the preceding appearance of this first picture f (N), adjusts these original gray value and also comprises for these steps of adjusting the back gray value:
Number appears in these original gray value of adding up this first picture f (N), with one first pixel transfer function H N(X) expression;
Number appears in these original gray value of adding up this second picture f (N-1), with one second pixel transfer function H N-1(X) expression;
This first pixel transfer function of integration H N(X), think a first integral value;
With this first pixel transfer function H N(X) with this second pixel transfer function H N-1(X) take absolute value after subtracting each other and, think a second integral value its integration; And
When the ratio of this second integral value and this first integral value during greater than one the 3rd default value, these original gray value of this first picture f (N) are this first transfer function F according to this first picture N(X) be adjusted into these and adjust the back gray value, otherwise these original gray value of this first picture f (N) are this first transfer function F according to this second picture f (N-1) N-1(X) be adjusted into these and adjust the back gray value.
8. image treatment method as claimed in claim 2, wherein, these original gray value correspond to an original red gray value, an original green gray value and an original blue gray value respectively, and this image treatment method also comprises:
According to this original red gray value, this original green gray value or this original blue gray value ratio corresponding to the standard maximum gradation value, adjusting this adjustment back gray value is that one first colorimetric purity weight mechanism is adjusted the back gray value.
9. image treatment method as claimed in claim 8, wherein, this image treatment method also comprises:
After adjusting this step of adjusting the back gray value, also according to this this original red gray value, this original green gray value and this original blue gray value proportionate relationship to each other, adjusting this first colorimetric purity weight mechanism, to adjust back gray value be gray value after one second colorimetric purity weight mechanism is adjusted.
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