CN101237517A - Image processing method and device - Google Patents
Image processing method and device Download PDFInfo
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- CN101237517A CN101237517A CNA2007100077094A CN200710007709A CN101237517A CN 101237517 A CN101237517 A CN 101237517A CN A2007100077094 A CNA2007100077094 A CN A2007100077094A CN 200710007709 A CN200710007709 A CN 200710007709A CN 101237517 A CN101237517 A CN 101237517A
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Abstract
The invention provides a picture processing method. A digital picture is output via a sensor, and comprises M pixels. An ith pixel of the M pixels has the ith group primitive gray scale value, wherein, i is an integer indicator between 1 to M. The method first produces M groups of log kows; the ith group of log kow of the M groups log kows is produced according to a group of adjusting parameters related to the sensor and the ith group of primitive gray scale value. Then the picture processing method statistics the M group of log kows and determines the target color temperature of the digital picture according to the statistic results.
Description
Technical field
The invention relates to a kind of image processing method and device, and especially, the invention relates to a kind of image processing method and image processing apparatus that is used for white balance correction.
Background technology
Generally speaking, the color of object can change to some extent along with the color of irradiation light thereon.Human eyes can be revised this change that produces because of light automatically, but the photoreceptor of digital camera (opticalsensor) does not possess such function.Therefore, the photo of shooting under different light can present different colour temperature (color temperature).For example, the photo of taking in the environment with tungsten lighting may be yellow partially, and the photo of taking in the sun then may be blue partially.
Many image processing systems all have the function that white balance (white balance) is proofreaied and correct.The purpose of white balance correction is the brightness of adjusting Red Green Blue in the digital picture, and to revise the color error that light causes, the photo that makes digital camera take out can be more near the human eye finding.
The colour temperature of the light source of decision image is normally carried out first step of white balance correction.The most traditional colour temperature determining method is to be based on nineteen forty-six to be supposed by the grey boundary (gray world) that R.M.Evans proposes.Digital picture is made up of a plurality of pixels.Each pixel has red GTG value, green GTG value and blue GTG value again separately.According to grey boundary hypothesis, under normal colour temperature, the average pixel value of redgreenblue should roughly equate in the image.Therefore, if the mean value of some colors is higher than the mean value of other two colors in the image, represent that the color of this image is subjected to the light influence and deviation is arranged.
The colour temperature determining method that is assumed to be theoretical foundation with grey boundary is the average red value that at first calculates all pixels in the digital picture, average green value and average blue valve.Then, this method is selected the soprano in these three mean values.If the average red value of a certain image is higher than green mean value and blue average values, then this image is judged as red partially.Easy speech, this method judge that the colour temperature of light source of this image is on the low side.
Yet above-mentioned this colour temperature determining method does not separate consideration with the color of object in the image itself with the influence that light causes.If the main object itself in the image is red, and unprovoked extraneous light influence is and red partially, and this method just may be judged the colour temperature of the light of this image by accident, carries out incorrect white balance correction then.
Except RGB color space (RGB color space), the CIE color space also be a kind of can in order to the expression color pattern.See also Fig. 1, Fig. 1 is the schematic diagram of CIE color space.The color of the light source of various different temperatures is indicated in the CIE coordinate diagram, again these is indicated point and link together, can obtain curve 100 as shown in Figure 1.Curve 100 is commonly called black body locus (black body locus) or Planckian locus (Plankian locus).In general, lower corresponding to the colour temperature of the light source of curve 100 right-hand members, higher corresponding to the colour temperature of the light source of curve 100 left ends.
In order to solve the problem of above-mentioned erroneous judgement colour temperature, a kind of colour temperature determining method is arranged at present when the colour temperature of the light source of judging image, only consider to be positioned in this image near the pixel the curve 100, that is only consider to be arranged in the pixel of scope 110.This colour temperature determining method is at first the RGB GTG value of pixels all in the image to be converted to the CIE color space, and statistics is arranged in the quantity of the pixel of scope 110 again.The pixel of supposing the scope that is positioned at 110 right-hand members is more, and this colour temperature determining method judges that promptly the colour temperature of light source of this image is on the low side.Relatively, if it is more to be positioned at the pixel of scope 110 left ends, this colour temperature determining method judges that promptly the colour temperature of light source of this image is higher.
The shortcoming of this method is that the RGB GTG value of each pixel must be converted to the CIE color space earlier, causes the trouble in the calculating.Moreover, in practical application, judge whether pixel is arranged in scope 110 and normally how far has by calculating this pixel distance curve 100.Because curve 100 is not the straight line of rule, the distance of calculating between each pixel and the curve 100 very bothers.
In order to solve above-mentioned two problems, the U.S. the 4th, 663, No. 663 and the 4th, 685, No. 071 patent has proposed another colour temperature determining method.Planckian locus has index (exponential) characteristic.Therefore, after suitable logarithm (logarithm) conversion, Planckian locus can be converted into the straight line in the logarithmic coordinates.See also Fig. 2, the longitudinal axis of this coordinate diagram and transverse axis are respectively Log (G/R) and Log (G/B), and R wherein, G, B be the GTG value of the redgreenblue of represent pixel respectively.Curve 200 is to be converted by Planckian locus, and is roughly straight line.Relatively, the scope among Fig. 1 110 also is converted into the scope 210 among Fig. 2.
Above-mentioned two colour temperature determining methods that patent proposed are the quantity of the pixel in the scope of statistics 210.The pixel of supposing the scope that is positioned at 210 right-hand members is more, and this colour temperature determining method judges that promptly the colour temperature of light source of this image is on the low side.The advantage of this method do not need to be RGB GTG value is converted to the CIE color space, and shortcoming is that then the distance of calculating each pixel and curve 200 also quite bothers.
Summary of the invention
For addressing the above problem, the invention provides a kind of image processing method and image processing apparatus.The method according to this invention and device are with through the Planckian locus after the number conversion further is converted to horizontal linear, judge to simplify whether pixel is arranged in the program of a certain preset range.
Digital picture is by photoreceptor output and comprises M pixel.I pixel in this M pixel has i and organizes original GTG value, and wherein i is the integer index of scope between 1 to M.A preferred embodiment according to the present invention is an image processing method.This image processing method at first produces M group logarithm value.I group logarithm value in this M group logarithm value is to organize original GTG value according to one group of adjustment parameter relevant with this photoreceptor with this i to produce.According to the present invention, this group is adjusted parameter and can be before camera dispatches from the factory is produced in advance and be stored in this camera according to the characteristic of the photoreceptor of this camera.This image processing method is then added up this M group logarithm value, and determines the target colour temperature of this digital picture according to statistics.
Another preferred embodiment according to the present invention is a kind of image processing apparatus.This device comprises logarithm value generation module, statistical module, and the colour temperature decision module.This logarithm value generation module is in order to produce M group logarithm value.I group logarithm value in this M group logarithm value is to organize original GTG value according to one group of adjustment parameter relevant with this photoreceptor with this i to produce.This statistical module is in order to add up this M group logarithm value.This colour temperature decision module then determines the target colour temperature of this digital picture in order to the statistics according to this statistic device.
After the target colour temperature of this digital picture of decision, the method according to this invention and device also can further comprise the step/module of this digital picture being carried out white balance correction.
Can be about the advantages and spirit of the present invention by following detailed Description Of The Invention and appended graphic being further understood.
Description of drawings
Fig. 1 is the schematic diagram of CIE color space.
Fig. 2 is logarithmic coordinates and the logarithmic curve after conversion.
Fig. 3 is for producing the flow chart that produces the method for adjusting parameter according to the present invention.
Fig. 4 is the flow chart that illustrates according to the image processing method of first preferred embodiment of the present invention.
Fig. 5 (A) is the schematic diagram of the first logarithm plane and first logarithmic curve; Fig. 5 (B) is the schematic diagram of the second logarithm plane and second logarithmic curve; Fig. 5 (C) is the schematic diagram of a plurality of logarithm scopes; Fig. 5 (D) is the schematic diagram of a plurality of coordinate points and logarithm scope.
Fig. 6 is the flow chart that illustrates according to the image processing method of second preferred embodiment of the present invention.
Fig. 7 (A) is the calcspar that illustrates according to the image processing apparatus of the 3rd preferred embodiment of the present invention; The embodiment of Fig. 7 (B) for deriving by Fig. 7 (A); Fig. 7 (C) is the calcspar that illustrates according to the image processing apparatus of the 4th preferred embodiment of the present invention.
[main element label declaration]
100: Planckian locus 110: the Planckian locus peripheral extent
200: curve 210: the peripheral extent of curve 200
S30A～S30D: process step S31～S33: process step
510: the second logarithmic curves of 500: the first logarithmic curves
520A～520C: logarithm scope S601～S610: process step
70: image processing apparatus 80: photoreceptor
701: logarithm value generation module 702: statistical module
703: colour temperature decision module 704: parameter module
704A: receiving element 704B: to counting unit
704C: the first converting unit 704D: parameter generating unit
705: average module is selected module at 706: the first
707: gain generation module 708: multiplier module
709: the second selection modules 710: matrix multiplication module
Embodiment
The invention provides a kind of image processing method and image processing apparatus.Compared to prior art, the method according to this invention and device comprise colour temperature determination procedure more fast, also can be in conjunction with other white balance correction program.
The characteristic of the photoreceptor of various cameras is neither identical.The method according to this invention and device can be before camera dispatch from the factory, and produce one group according to the characteristic of the photoreceptor of this camera and adjust parameter, for the usefulness of white balance correction in the future.See also Fig. 3, Fig. 3 adjusts the flow chart of the method for parameter for producing this group.
In order to contain the corresponding situation of multiple light source, adopt the camera of this photoreceptor at first can be used under multiple different light source, take color correction plate (color checker), produce a plurality of sampled pixels by this.In step S30A, this method receives these sampled pixels by this photoreceptor.Each sampled pixel has one group of sample GTG value separately; Each group sample GTG value is each self-contained red sample GTG value (R again
S), green sample GTG value (G
S) and blue sample GTG value (B
S).
Step S30B produces first logarithmic curve according to this equal samples GTG value in the first logarithm plane.For instance, if the longitudinal axis on this first logarithm plane and transverse axis are respectively Log (G/R) and Log (G/B), then step S30B is the Log (G that calculates each sampled pixel respectively
S/ R
S) and Log (G
S/ B
S).After being shown in these result of calculations on this first logarithm plane, this first logarithmic curve can indicate the regression curve (regression curve) of point for these.See also Fig. 5 (A), curve 500 is the example of this first logarithmic curve.In practical application, the longitudinal axis on this first logarithm plane and transverse axis are not limited to Log (G/R) and Log (G/B), also can be respectively Log[R/ (R+G+B)] and Log[B/ (R+G+B)].
Shown in Fig. 5 (A), there is certain degree θ in this first logarithmic curve transverse axis common and this first logarithm plane.Reference axis by changing this first logarithm plane also produces the second logarithm plane, and step S30C can be converted to second logarithmic curve with this first logarithmic curve.Curve 510 among Fig. 5 (B) is the example of this second logarithmic curve.Shown in Fig. 5 (B), this second logarithmic curve is the transverse axis that is roughly parallel to this second logarithm plane.In an embodiment, the longitudinal axis (Y on this second logarithm plane
NEW) and transverse axis (X
NEW) can be respectively:
X
NEW＝Log(G)*cos(θ)-Log(R)*cos(θ)+Log(G)*sin(θ)-
Log(B)*sin(θ)，
Y
NEW＝Log(G)*cos(θ)-Log(B)*cos(θ)-Log(G)*sin(θ)+
Log(R)*sin(θ)。
Then, step S30D produces the adjustment parameter of this group corresponding to this photoreceptor promptly according to the difference between this first logarithmic curve and this second logarithmic curve.Adjust parameter according to this group, the RGB GTG value of pixel can directly be converted into the coordinate points on this second logarithm plane.
In addition, shown in Fig. 5 (C), before camera dispatched from the factory, the designer can define a plurality of logarithm scopes (520A～520C) for example according to second logarithmic curve of this camera.Each this logarithm scope corresponds respectively to a colour temperature.Because the characteristic of the photoreceptor of various cameras is neither identical, every kind of camera all has unique first logarithmic curve, second logarithmic curve, adjusts parameter and logarithm scope.
According to the present invention, after this camera dispatched from the factory and is used to take pictures, photoreceptor wherein can be exported the digital picture that comprises M pixel.Following embodiment is that i pixel in this M of hypothesis pixel has i and organize original GTG value.I is the integer index of scope between 1 to M.In practical application, this i organizes original GTG value can comprise the original red GTG value of i, the original green GTG value of i and the original blue GTG value of i.
First preferred embodiment according to the present invention is a kind of image processing method.See also Fig. 4, Fig. 4 is the flow chart that illustrates this image processing method.In step S31, this method at first produces M group logarithm value.I group logarithm value in this M group logarithm value is to adjust parameter according to one group to organize original GTG value generation with this i.This group is adjusted parameter and normally promptly is stored in this camera before this camera dispatches from the factory.Adjust parameter according to this group, the original GTG value of each pixel can be converted into one group of logarithm value, that is the coordinate figure on the previous described second logarithm plane.In practical application, this i group logarithm value can be organized original GTG value by i and directly convert.Step S31 also can be earlier each is organized original GTG value and is converted to one group of initial logarithm value corresponding to this first logarithm plane with this, adjust parameter according to this group again, this is organized initial logarithm value is converted to logarithm value on the second logarithm plane.
As mentioned above, the designer can be in advance defines a plurality of logarithm scopes according to second logarithmic curve of this camera.Each logarithm scope is separately corresponding to a colour temperature.In the example shown in Fig. 5 (D), each the black coordinate points that indicates in this coordinate diagram is one group of logarithm value representing in this M group logarithm value.Some coordinate points can drop in these logarithm scopes, and some coordinate points then is positioned at outside these logarithm scopes.
Step S32 is that each logarithm scope of statistics comprises how much organize logarithm value (that is what coordinate points) respectively.Shown in Fig. 5 (D), the coordinate points that comprises among the logarithm scope 520A is maximum.Therefore, in this example, step S33 selects logarithm scope 520A as target logarithm scope, and the pairing colour temperature of decision logarithm scope 520A is the colour temperature of this digital picture.
Because second logarithmic curve according to the present invention is the transverse axis that is parallel to the second logarithm plane, these logarithm scopes all can be rule, frame is parallel to the rectangle of reference axis.Therefore, the logarithm value that apex coordinate and the step S31 of colour temperature determining method according to the present invention by these logarithm scopes of direct comparison calculates can judge whether a certain group of logarithm value is positioned at certain logarithm scope.In other words, needs such as prior art are not calculated the distance of each coordinate figure and Planckian locus or first logarithmic curve with making or have much ado according to colour temperature determining method of the present invention.
In addition, image processing method shown in Figure 4 also can further comprise the program of other white balance correction.According to second preferred embodiment of the present invention also is image processing method.See also Fig. 6, Fig. 6 is the flow chart of this image processing method.Step S601 to S603 is identical with the step S31 to S33 of Fig. 4.After the target logarithm scope and target colour temperature of step S603 decision image, step S604 is that pairing these pixels of these many group logarithm value that will be contained in this target logarithm scope be set at object pixel.
Then, step S605 calculates average red GTG value, calculates average green GTG value according to these original green GTG values of these object pixels according to these original red GTG values of these object pixels, and calculates average blue GTG value according to these original blue GTG values of these object pixels.Step S606 then is the maximum of selecting in this average red GTG value, this average green GTG value and this average blue GTG value, as the highest mean value.In step S607, this highest mean value is obtained red gain divided by this average red GTG value, and this highest mean value is obtained green gain divided by this average green GTG value, and this highest mean value is obtained blue gain divided by this average blue GTG value.
Step S608 is that the original red GTG of each pixel in this digital picture is on duty with this red gain, obtains adjusting the red GTG value in back.Step S608 is also on duty with this green gain with the original green GTG of each pixel in this digital picture, obtain adjusting the green GTG value in back, and the original blue GTG of each pixel in this digital picture is on duty with this blue gain, obtain adjusting the blue GTG value in back.
In step S609, the target colour temperature of this method step S603 decision is selected objective matrix.Step S610 then is that this red GTG value in adjustment back, the blue GTG of this adjustment green GTG value in back and this adjustment back of each pixel in this M pixel is on duty with this objective matrix.Multiply by after this objective matrix, the GTG value of each pixel promptly is adjusted to the color ratio collocation that meets white balance in this digital picture.By above-mentioned steps, this method can be finished at the white balance of this digital picture and colour correction.
The 3rd preferred embodiment according to the present invention is a kind of image processing apparatus.See also Fig. 7 (A), Fig. 7 (A) is the calcspar that illustrates this image processing apparatus 70.Image processing apparatus 70 comprises logarithm value generation module 701, statistical module 702 and colour temperature decision module 703.After camera dispatched from the factory and is used to take pictures, the digital picture that photoreceptor 80 wherein can will comprise M pixel exported image processing apparatus 70 to.I pixel in this M pixel has i and organizes original GTG value.
Logarithm value generation module 701 is in order to produce M group logarithm value.I group logarithm value in this M group logarithm value is to organize original GTG value according to one group of adjustment parameter relevant with this photoreceptor with this i to produce.Statistical module 702 is in order to add up this M group logarithm value.703 of colour temperature decision module are the target colour temperatures that determines this digital picture in order to the statistics according to statistical module 702.
In practical application, image processing apparatus 70 can further comprise in order to produce this group and adjust the parameter module 704 of parameter shown in Fig. 7 (B).In this example, parameter module 704 comprise receiving element 704A, to counting unit 704B, the first converting unit 704C, with parameter generating unit 704D.
Receiving element 704A is in order to receive a plurality of sampled pixels by photoreceptor 80 outputs.Each this sampled pixel has one group of sample GTG value separately.To counting unit 704B is in order to according to the many group samples of being somebody's turn to do of these sampled pixels GTG values, produces first logarithmic curve in the first logarithm plane.The first converting unit 704C is in order to be converted to this first logarithmic curve second logarithmic curve in the second logarithm plane.This second logarithmic curve is a rough reference axis that is parallel to this second logarithm plane.Parameter generating unit 704D then is in order to according to the difference between this first logarithmic curve and this second logarithmic curve, produces for logarithm value generation module 701 these used groups and adjusts parameter.
In addition, in practical application, a plurality of logarithm scopes are to provide in advance.Each this logarithm scope corresponds respectively to a colour temperature.Statistical module 702 each these logarithm scope of statistics comprise the logarithm value of how much organizing in this M group logarithm value respectively.Colour temperature decision module 703 can select comprise maximum groups of logarithm value this logarithm scope as target logarithm scope, the pairing colour temperature of this target logarithm scope is this target colour temperature.
According to the 4th preferred embodiment of the present invention also is a kind of image processing apparatus.Compared to the embodiment shown in Fig. 7 (A), the image processing apparatus 70 among this embodiment further comprises other in order to carry out the module of white balance correction program.Shown in Fig. 7 (C), except logarithm value generation module 701, statistical module 702, with colour temperature decision module 703, the image processing apparatus 70 among this embodiment also comprises setting module 704, average module 705, first selects module 706, gain generation module 707, multiplier module 708, second to select module 709, matrix multiplication module 710.
Second selects module 709 in order to select objective matrix according to this target colour temperature.710 of matrix multiplication modules are in order to this red GTG value in adjustment back, the blue GTG of this adjustment green GTG value in back and this adjustment back of each pixel in this M pixel is on duty with this objective matrix.
As mentioned above, because therefore the method according to this invention and device will can be simplified and judge whether pixel is arranged in the program of a certain reference color temperature through the Planckian locus after the number conversion further is converted to horizontal linear.Compared to prior art, the method according to this invention and device provide better simply colour temperature determination procedure.In addition, the method according to this invention and device also can provide a complete white balance correction scheme further combined with color correction program.
By the above detailed description of preferred embodiments, be to wish to know more to describe feature of the present invention and spirit, and be not to come category of the present invention is limited with above-mentioned disclosed preferred embodiment.On the contrary, its objective is that hope can contain in the category of claim scope of being arranged in of various changes and tool equality institute of the present invention desire application.
Claims (26)
1. image processing method, digital picture be by photoreceptor output and comprise M pixel, and M is a positive integer, and i pixel in this M pixel has i and organize original GTG value, and i is the integer index of scope between 1 to M, and this method comprises:
(a) generation M group logarithm value, the i group logarithm value that this M organizes in logarithm value is to organize original GTG value generation according to one group of adjustment parameter relevant with this photoreceptor and this i;
(b) add up this M group logarithm value; And
(c), determine the target colour temperature of this digital picture according to the statistics of step (b).
2. image processing method according to claim 1, wherein this group adjustment parameter is to produce with the following step:
(d1) receive a plurality of sampled pixels of being exported by this photoreceptor, each this sampled pixel has one group of sample GTG value separately;
(d2) according to the many group samples of being somebody's turn to do of these sampled pixels GTG values, produce first logarithmic curve in the first logarithm plane;
(d3) this first logarithmic curve is converted to second logarithmic curve in the second logarithm plane, this second logarithmic curve is a rough reference axis that is parallel to this second logarithm plane; And
(d4), produce this group and adjust parameter according to the difference between this first logarithmic curve and this second logarithmic curve.
3. image processing method according to claim 2, wherein each organizes each self-contained red sample GTG value (R of this sample GTG value
S), green sample GTG value (G
S) and blue sample GTG value (B
S).
4. image processing method according to claim 3, wherein the longitudinal axis on this first logarithm plane and transverse axis are respectively Log (G
S/ R
S) and Log (G
S/ B
S).
5. image processing method according to claim 1, wherein step (a) comprises following substep:
(a1) organize original GTG value according to this i, calculate i and organize initial logarithm value; And
(a2) adjust parameter according to this group, this i is organized initial logarithm value be converted to this i group logarithm value.
6. image processing method according to claim 5, wherein this i organizes original GTG value and comprises the original red GTG value (R of i
i), the original green GTG value (G of i
i) and the original blue GTG value (B of i
i).
7. image processing method according to claim 6, wherein this i organizes initial logarithm value for [Log (G
i/ R
i), Log (G
i/ B
i)].
8. image processing method according to claim 1, wherein a plurality of logarithm scopes are to provide in advance, step (b) is that each this logarithm scope of statistics comprises the logarithm value of how much organizing in this M group logarithm value respectively.
9. image processing method according to claim 8, wherein each this logarithm scope corresponds respectively to colour temperature, step (c) be select comprise maximum groups of logarithm value this logarithm scope as target logarithm scope, the pairing colour temperature of this target logarithm scope is this target colour temperature.
10. image processing method according to claim 9, wherein this of each pixel in this M pixel organized original GTG value and comprised original red GTG value, original green GTG value and original blue GTG value.
11. image processing method according to claim 10, this method also comprises:
(e1) pairing these pixels of these many group logarithm value that will be contained in this target logarithm scope be set at a plurality of object pixels; And
(e2) calculate average red GTG value according to these original red GTG values of these object pixels, these original green GTG values according to these object pixels are calculated average green GTG value, calculate average blue GTG value according to these original blue GTG values of these object pixels.
12. image processing method according to claim 11, this method also comprises:
(f1) select the maximum in this average red GTG value, this average green GTG value and this average blue GTG value, as the highest mean value;
(f2) this highest mean value is obtained red gain divided by this average red GTG value, this highest mean value is obtained green gain divided by this average green GTG value, this highest mean value is obtained blue gain divided by this average blue GTG value; And
(f3) this original red GTG of each pixel in this M pixel is on duty with this red gain, obtain adjusting the red GTG value in back, this original green GTG of each pixel in this M pixel is on duty with this green gain, obtain adjusting the green GTG value in back, this original blue GTG of each pixel in this M pixel is on duty with this blue gain, obtain adjusting the blue GTG value in back.
13. image processing method according to claim 12, this method also comprises:
(g1) select objective matrix according to this target colour temperature; And
(g2) blue GTG after this red GTG value in adjustment back, this adjustment green GTG value in back and this adjustment of each pixel in this M pixel is on duty with this objective matrix.
14. an image processing apparatus, digital picture be by photoreceptor output and comprise M pixel, M is a positive integer, and i pixel in this M pixel has i and organize original GTG value, and i is the integer pointer of scope between 1 to M, and this device comprises:
The logarithm value generation module is organized logarithm value in order to produce M, and the i in this M group logarithm value organizes logarithm value system and organizes original GTG value generation according to one group of adjustment parameter relevant with this photoreceptor and this i;
Statistical module is in order to add up this M group logarithm value; And
The colour temperature decision module determines the target colour temperature of this digital picture in order to the statistics according to this statistical module.
15. image processing apparatus according to claim 14, this image processing apparatus also comprises:
Parameter module, adjust parameter in order to produce this group, and comprise:
Receiving element, in order to receive a plurality of sampled pixels of being exported by this photoreceptor, each this sampled pixel has one group of sample GTG value separately;
To counting unit,, produce first logarithmic curve in the first logarithm plane in order to according to the many group samples of being somebody's turn to do of these sampled pixels GTG values;
First converting unit, in order to this first logarithmic curve is converted to second logarithmic curve in the second logarithm plane, this second logarithmic curve is a rough reference axis that is parallel to this second logarithm plane; And
The parameter generating unit in order to according to the difference between this first logarithmic curve and this second logarithmic curve, produces this group and adjusts parameter.
16. image processing apparatus according to claim 15, wherein each organizes each self-contained red sample GTG value (R of this sample GTG value
S), green sample GTG value (G
S) and blue sample GTG value (B
S).
17. image processing apparatus according to claim 16, wherein the longitudinal axis on this first logarithm plane and transverse axis are respectively Log (G
S/ R
S) and Log (G
S/ B
S).
18. image processing apparatus according to claim 14, wherein this logarithm value generation module comprises:
First computing unit in order to organize original GTG value according to this i, calculates i and organizes initial logarithm value; And
Second converting unit in order to adjust parameter according to this group, is organized initial logarithm value with this i and is converted to this i group logarithm value.
19. image processing apparatus according to claim 18, wherein this i organizes original GTG value and comprises the original red GTG value (R of i
i), the original green GTG value (G of i
i) and the original blue GTG value (B of i
i).
20. image processing apparatus according to claim 19, wherein this i organizes initial logarithm value for [Log (G
i/ R
i), Log (G
i/ B
i)].
21. image processing apparatus according to claim 14, wherein a plurality of logarithm scopes are to provide in advance, and this statistical module is that each this logarithm scope of statistics comprises the logarithm value of how much organizing in this M group logarithm value respectively.
22. image processing apparatus according to claim 21, wherein each this logarithm scope corresponds respectively to colour temperature, this colour temperature decision module system select comprise maximum groups of logarithm value this logarithm scope as target logarithm scope, the pairing colour temperature of this target logarithm scope is this target colour temperature.
23. image processing apparatus according to claim 22, wherein this of each pixel in this M pixel organized original GTG value and comprised original red GTG value, original green GTG value and original blue GTG value.
24. image processing apparatus according to claim 23, this image processing apparatus also comprises:
Setting module be set at a plurality of object pixels in order to pairing these pixels of these many group logarithm value that will be contained in this target logarithm scope; And
Average module, in order to calculating average red GTG value according to these original red GTG values of these object pixels, to calculate average green GTG value, and calculate average blue GTG value according to these original blue GTG values of these object pixels according to these original green GTG values of these object pixels.
25. image processing apparatus according to claim 24, this image processing apparatus also comprises:
First selects module, in order to select the maximum in this average red GTG value, this average green GTG value and this average blue GTG value, as the highest mean value;
The gain generation module, in order to this highest mean value is obtained red gain, this highest mean value is obtained green gain divided by this average green GTG value divided by this average red GTG value, and this highest mean value is obtained blue gain divided by this average blue GTG value; And
Multiplier module, in order to obtain adjusting the red GTG value in back, to obtain adjusting green GTG value afterwards with this green gain with this original green GTG of each pixel in this M pixel is on duty with this red gain this original red GTG of each pixel in this M pixel is on duty, and this original blue GTG of each pixel in this M pixel is on duty with this blue gain, obtain adjusting the blue GTG value in back.
26. image processing apparatus according to claim 25, this image processing apparatus also comprises:
Second selects module, in order to select objective matrix according to this target colour temperature; And
The matrix multiplication module is in order on duty with this objective matrix with blue GTG after this red GTG value in adjustment back, this adjustment green GTG value in back and this adjustment of each pixel in this M pixel.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2007100077094A CN101237517B (en) | 2007-01-29 | 2007-01-29 | Image processing method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2007100077094A CN101237517B (en) | 2007-01-29 | 2007-01-29 | Image processing method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101237517A true CN101237517A (en) | 2008-08-06 |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102572206A (en) * | 2010-12-31 | 2012-07-11 | 比亚迪股份有限公司 | Color correction method |
| CN105847776A (en) * | 2016-03-31 | 2016-08-10 | 乐视控股（北京）有限公司 | White balance determination method based on high color temperatures |
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| US4685071A (en) * | 1985-03-18 | 1987-08-04 | Eastman Kodak Company | Method for determining the color of a scene illuminant from a color image |
| JP2000101860A (en) * | 1998-09-18 | 2000-04-07 | Fuji Photo Film Co Ltd | Image correction method, image correction device and recording medium |
| US6573932B1 (en) * | 2002-03-15 | 2003-06-03 | Eastman Kodak Company | Method for automatic white balance of digital images |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102572206A (en) * | 2010-12-31 | 2012-07-11 | 比亚迪股份有限公司 | Color correction method |
| CN102572206B (en) * | 2010-12-31 | 2015-05-13 | 比亚迪股份有限公司 | Color correction method |
| CN105847776A (en) * | 2016-03-31 | 2016-08-10 | 乐视控股（北京）有限公司 | White balance determination method based on high color temperatures |
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