CN107197225B - White Balance Correction Method of Color Digital Camera Based on Chromatic Adaptation Model - Google Patents
White Balance Correction Method of Color Digital Camera Based on Chromatic Adaptation Model Download PDFInfo
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- CN107197225B CN107197225B CN201710442492.3A CN201710442492A CN107197225B CN 107197225 B CN107197225 B CN 107197225B CN 201710442492 A CN201710442492 A CN 201710442492A CN 107197225 B CN107197225 B CN 107197225B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
- H04N23/84—Camera processing pipelines; Components thereof for processing colour signals
- H04N23/88—Camera processing pipelines; Components thereof for processing colour signals for colour balance, e.g. white-balance circuits or colour temperature control
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Abstract
The invention discloses a kind of color digital camera white balance correctings based on chromatic adaptation model, the present invention calculates color correction matrix using radical sign polynomial regression (Root-Polynomial Regression) method, thus device-independent CIE1931 tristimulus values XYZ under the equipment relevant response value RGB under several common light sources (hereinafter referred to as Calibrating source) is converted to same light source.The RGB response of light source (hereinafter referred to as testing light source) unknown in actual scene is converted into XYZ color space using the color correction matrix demarcated in advance, and its correspondence color under reference light source is calculated using CAT02 chromatic adaptation transformation model, which is that observer generates the color that chromatic adaptation after-vision system is perceived to testing light source.
Description
Technical field
It the present invention relates to the use of the method that color digital camera white balance correction result is adjusted in chromatic adaptation model, it should
Method can make color digital camera realize the color rendition for more meeting human eye perception to photographed scene.
Background technique
Same object often has different chromatic values under different light sources.Since human visual system has color
Shape constancy, the difference in these colorations can be compensated automatically to a certain extent by human eye and brain, thus not sharing the same light
The color of object " true " is restored under source.In color digital camera image signal process process (ISP Pipeline)
White balance module, by calculating the difference between actual light source chromaticity and standard sources chromaticity, to the object under non-standard light source
Colour cast phenomenon is corrected, to simulate the color constancy of human visual system.
Current color digital camera is mainly derived from two ways to the acquisition of light source chromaticity: 1) empty in the storage of camera
Between in pre-set several type light source mode, the light source type as belonging to user's given scenario in actual photographed.
This kind of light source chromaticity acquisition modes are known as " manual white balance mode "；2) image taken is analyzed, passes through certain light
Source algorithm for estimating is predicted by color of the outer sensor to light source.This kind of light source chromaticity acquisition modes are known as " automatic
White balance mode ".No matter work in what mode, white balance correction module is usually all to utilize two or three gain coefficients
Linear regulation is carried out to red (Red), blue (Blue) or red, green (Green), blue channel of colour cast image, so that imaginary in scene
The reflecting surface (spectral reflectance perseverance at any wavelength be 1 improve reflecting surface) that improves have after white balance correction
Identical (or consistent with reference white point) triple channel response.
If especially certain chromaticities are more apparent to deviate the light source for referring to white point, all using unification to any lighting source
Reference light source can generate the image after white balance correction as following drawbacks as white balance correction target: 1) export image mistake
" white ", the reduction of color does not meet human eye perception in scene；2) light source is suppressed the rendering effect of scene atmosphere completely；3) will
The more serious light source of colour cast is corrected by force to reference light source, will increase (such as the camera lens of subsequent module in image signal process process
Shadow correction, color correction etc.) processing difficulty, even result in picture quality and deteriorate.
Summary of the invention
In order to make the white balance correction module of digital camera realize more true scene color reproduction, the present invention utilizes original
The gain coefficient obtained in beginning white balance correction moduleCalculate the color of light source in actual photographed scene.For table
For the sake of stating unification, light source colour is characterized using the object color for improving reflecting surface in the present invention, it can because improving reflecting surface
Without wavelength selectivity whole energy of reflection source.It is converted using the CAT02 chromatic adaptation in CIECAM02 colored quantum noise to this
Correspondence color of the object color under reference light source is calculated, to obtain the white balance correction gain coefficient after chromatic adaptationTo realize the white balance correction for carrying out being more in line with human eye visual perception to image.
The present invention calculates color correction using radical sign polynomial regression (Root-Polynomial Regression) method
Matrix, to converting the equipment relevant response value RGB under several common light sources (hereinafter referred to as Calibrating source) to same light
Device-independent CIE1931 tristimulus values XYZ under source.It will be to be corrected in actual scene using the color correction matrix demarcated in advance
The RGB response of unknown light source (hereinafter referred to as testing light source) convert into XYZ color space, and use CAT02 chromatic adaptation
Transformation model calculates its correspondence color under reference light source, which is that observer generates chromatic adaptation backsight to testing light source
The color that feel system is perceived.
Specific technical solution of the present invention is as follows:
Color digital camera white balance correcting based on chromatic adaptation model, steps are as follows:
S1: using radical sign polynomial regression color calibration method by the equipment relevant response value RGB under different Calibrating sources
It converts to tristimulus values CIE1931 XYZ device-independent under same light source；
S2: obtaining the white balance correction gain coefficient of the image shot under light source to be corrected, calculates light source to be corrected and existsCoordinate in plane, in cameraSearch and the nearest Calibrating source of the coordinate distance, call the mark in plane
Determine the corresponding color correction matrix of light source, the relevant camera response of the equipment of the light source is converted to CIE1931 XYZ space
In, light source colour is considered as object color；
S3: standard of the object color after chromatic adaptation is calculated using the chromatic adaptation transformation CAT02 in CIECAM02 colored quantum noise
Correspondence color under light source:
S4: corresponding color is remapped back camera rgb space using the inverse matrix of the color correction matrix, and is counted again
White balance correction gain coefficient after calculating chromatic adaptation.
Based on the above-mentioned technical proposal, each step can use following specific implementation:
Preferably, the S1 specifically:
S101: it is the Calibrating source L of P (λ) for spectral power distribution, constitutes model using camera response and calculate standard
Camera rgb value r of i-th of the color lump of colour atla under light source illuminationi、giAnd bi:
ρ in formulai(λ) indicates the spectral reflectance of i-th of color lump, SkThe spectral sensitivity in (λ) expression k-th of channel of camera
Function, k=R, G, B, Ω ' are the wave-length coverage of camera spectral response；For there is the standard color card of N number of color lump, it is calculated one
The camera response Matrix C (L) of a N × 3, wherein the camera rgb value of the corresponding color lump of every a line；
S102: the camera rgb value r that reflecting surface is improved under the Calibrating source is calculatedill、gillAnd bill:
And record itsCoordinate in plane
S103: it is the Calibrating source of P (λ) for spectral power distribution, uses 2 ° of standard observer's colour matchings of CIE1931
FunctionCalculate CIE1931 XYZ tristimulus values of i-th of the color lump of standard color card under light source illumination:
Ω is the wave-length coverage of visible light in formula；For there is the standard color card of N number of color lump, the three of N × 3 are calculated
It stimulates value matrix T (L), wherein the XYZ tristimulus values of the corresponding color lump of every a line；
S104: the dimension of camera response Matrix C (L) is extended to N × q, q > 3 by N × 3, wherein 4~q column correspond to
The radical sign multinomial of each color lump response；
S105: using least square method or other correction matrix optimization methods using color difference as objective function, C ' is calculated
(L) it converts to 6 × 3 color correction matrix M ' (L) of T (L):
When using the root-mean-square error between C ' (L) M ' (L) and T (L) as optimization aim, using pseudoinverse technique to M ' (L)
It is calculated:
M ' (L)=[C 'T(L)C′(L)]-1C′T(L)·T(L),
When using the color difference between C ' (L) M ' (L) and T (L) as optimization aim, using nonlinear optimization method to M '
(L) it is calculated:
M ' (L)=arg min △ E (C ' (L) M ' (L), T (L)),
△ E (A, B) is the function for calculating the color difference between A and B in formula；
S106: 3 × 3 color correction matrix M (L) under each Calibrating source are calculated using the method in S105；S107: right
In all Calibrating sources, respective color correction matrix M ' (L) and M (L) are calculated using the method for S101~S106, and deposit
It is stored in camera internal memory.
Preferably, the S2 specifically:
S201: manual setting obtains the white of the image shot under light source to be corrected using existing automatic white balance algorithm
Balance correction gain coefficient
S202: rgb value of the light source to be corrected on the domain camera raw is calculated:
In cameraIn plane search withIt is stored apart from nearest Calibrating source L, and from built in camera
Its corresponding color correction matrix M ' (L) is called in device；
S203: the camera response for improving reflecting surface under the scene light source is turned using color correction matrix M ' (L)
It shifts in CIE1931 XYZ space:
X in formulaill,Yill,ZillTristimulus values respectively in XYZ space.
Preferably, the S3 specifically:
Object color [X is calculated using the chromatic adaptation transformation CAT02 in CIECAM02 colored quantum noiseill,Yill,Zill] Jing Seshi
Correspondence color under standard sources after answering:
Chromatic adaptation transformation model f in formulaCAT02Four inputs be successively object color tristimulus values to be calculated, it is to be adapted to
Light source tristimulus values, reference light source tristimulus values and ambient brightness factor LA。
Further, the ambient brightness factor is calculated using two sigmoid functions:
In formula, light source chromaticity distance d is by calculating actual light source and reference light source chromaticity in CIELUV homogeneous color space
In Euclidean distance obtain, a1、b1、K1、a2、b2、K2Undetermined parameter as adjustment sigmoid function shape.
Preferably, the S4 specifically:
It inverts to corresponding 3 × 3 color correction matrix M (L) of Calibrating source L, and will be perfect anti-after chromatic adaptation
Beam tristimulus valuesIt remaps back in camera rgb space:
The white balance correction gain coefficient after chromatic adaptation is calculated as a result,
The present invention can be pierced the CIE1931 XYZ tri- after chromatic adaptation by inverting to calibrated color correction matrix
Sharp value converts back in camera RGB color, so that it is determined that the white balance correction gain coefficient after chromatic adaptation.
In order to which implementation process of the invention is understood more intuitively, an embodiment is cited below particularly, and cooperate appended diagram
It is described in detail.
Detailed description of the invention
Fig. 1 be Calibrating source used in the embodiment of the present invention byWithThe plane constituted as transverse and longitudinal coordinate
(hereinafter referred to asPlane) on coordinate distribution.
Fig. 2 is the flow chart demarcated in the present invention to the color correction matrix of several Calibrating sources.
Fig. 3 is CAT02 chromatic adaptation mode input parameter L used in the embodiment of the present inventionA(the ambient brightness factor) and d
Correspondence diagram between (Euclidean distance in CIELUV homogeneous color space), E (photographed scene illumination).
Fig. 4 is the process for carrying out the white balance correction gain coefficient after chromatic adaptation in the present invention to a certain testing light source and calculating
Figure.
Specific embodiment
The present invention is further elaborated and is illustrated with reference to the accompanying drawings and detailed description.
The white balance correction module of current most of color digital cameras corrects the neutral point under any light source to ginseng
The driving value under light source is examined, this white balance correction mode had not both met perception of the human eye for color in real scene, and held yet
It is easier that there is apparent distortion in the color after correction.The present invention proposes a kind of CAT02 using in CIECAM02 colored quantum noise
The method that chromatic adaptation transformation carries out chromatic adaptation adjusting to the original gain coefficient of digital camera white balance correction module, to make white
Image after balance correction is more in line with the color-aware of human eye.
The present invention uses radical sign polynomial regression color correction (Root-Polynomial Regression Color
Correction equipment is unrelated under) method converts the equipment relevant response value RGB under several common light sources to same light source
Tristimulus values CIE1931 XYZ.The color correction matrix as used in radical sign polynomial regression color correction depends on light
Source function of spectral power distribution, so the present invention needs in advance to carry out several exemplary light sources the calibration of color correction matrix.
Fig. 1 illustrates a kind of feasible Calibrating source choosing method, and depicts 39 kinds of Calibrating sources in camera
Coordinate distribution in plane.
Fig. 2 is the flow chart demarcated in the present invention to the color correction matrix of several Calibrating sources.Wherein, nominal light
The quantity and type in source can be limited in biggish application scenarios in certain pairs of storage overheads with flexible choice, can also only be chosen D65
Light source calculates color correction matrix as unique Calibrating source.
1. calibration process of the invention comprises the steps of:
To convert camera response RGB to device-independent tristimulus values XYZ, the present invention uses radical sign polynomial regression
Color calibration method.
It is the Calibrating source L of P (λ) for spectral power distribution, constitutes model using camera response and calculate standard color card
Camera rgb value of i-th of color lump under light source illumination:
ρ in formulai(λ) indicates the spectral reflectance of i-th of color lump, SkThe spectral sensitivity in (λ) expression k-th of channel of camera
Function (k=R, G, B) can obtain or utilize relevant spectral sensitivity algorithm for estimating meter from nominal data when camera factory
It calculates and obtains, Ω ' is the wave-length coverage of camera spectral response.For there is the standard color card of N number of color lump, a N can be calculated
× 3 camera response Matrix C (L), wherein the camera rgb value of the corresponding color lump of every a line.
Meanwhile calculating the camera rgb value that reflecting surface is improved under the Calibrating source:
And record itsCoordinate in plane
It is the Calibrating source of P (λ) for spectral power distribution, uses 2 ° of standard observer's color matching functions of CIE1931Calculate CIE1931 XYZ tristimulus values of i-th of the color lump of standard color card under light source illumination:
Ω is the wave-length coverage of visible light in formula.For there is the standard color card of N number of color lump, N × 3 can be calculated
Tristimulus values matrix T (L), wherein the XYZ tristimulus values of the corresponding color lump of every a line.
The dimension of camera response Matrix C (L) is extended to N × q (q > 3) by N × 3, wherein 4~q column have corresponded to respectively
The radical sign multinomial of a color lump response.By taking secondary radical sign multinomial as an example, there is q=6 at this time, the camera response square after extension
The i-th behavior of battle array C ' (L)
Using least square method or other correction matrix optimization methods using color difference as objective function, calculates C ' (L) and turn
Shift to 6 × 3 color correction matrix M ' (L) of T (L):
When using the root-mean-square error between C ' (L) M ' (L) and T (L) as optimization aim, pseudoinverse technique can be used to M '
(L) it is calculated:
M ' (L)=[C 'T(L)C′(L)]-1C′T(L)·T(L).
It is non-thread using Gauss-Newton method etc. when using the color difference between C ' (L) M ' (L) and T (L) as optimization aim
Property optimization method calculates M ' (L):
M ' (L)=arg min △ E (C ' (L) M ' (L), T (L))
△ E (A, B) is the function for calculating the color difference between A and B in formula；
Meanwhile using similar method, 3 × 3 color correction matrix M (L) under each Calibrating source are calculated.M (L) and M '
(L) the difference is that, M ' (L) be suitable for radical sign polynomial expansion after response Matrix C ' (L), and M (L) be suitable for it is original
Response Matrix C (L).
For all Calibrating sources, respective color correction matrix M ' (L) and M (L) are calculated using method as above, and
It is stored in camera internal memory.
2. the mistake that the present invention carries out the white balance correction based on chromatic adaptation model to the image shot under any unknown light source
Journey is as follows:
Manual setting or the white balance correction gain coefficient that the image is obtained using existing automatic white balance algorithm
Calculate rgb value of the light source on the domain camera raw in the scene:
In cameraIn plane search withIt is stored apart from nearest Calibrating source L, and from built in camera
Its corresponding color correction matrix M ' (L) is called in device.
Using color correction matrix M ' (L) by the camera response for improving reflecting surface under the scene light source convert to
In CIE1931 XYZ space:
Object color [X is calculated using the chromatic adaptation transformation CAT02 in CIECAM02 colored quantum noiseill,Yill,Zill] Jing Seshi
Correspondence color under standard sources after answering:
In formula, chromatic adaptation transformation model fCAT02Four inputs be successively object color tristimulus values to be calculated, wait adapt to
Light source tristimulus values, reference light source tristimulus values and LAThe ambient brightness factor.Since the present invention needs to calculate testing light source
Perception color after chromatic adaptation is equivalent to calculate the correspondence color for improving reflecting surface under testing light source, therefore before the model
Two inputs are the CIE1931 XYZ tristimulus values of testing light source.Select CIE D65 working flare as standard in the present embodiment
Working flare, therefore
Ambient brightness factor LACan comprehensively consider actual light source and reference light source chromaticity distance d and scene illumination E this
Two factors.Using two sigmoid functions to L in the present inventionAIt is calculated:
In formula, light source chromaticity distance d can be empty in CIELUV uniform color by calculating actual light source and reference light source chromaticity
Between in Euclidean distance obtain, a1、b1、K1、a2、b2、K2It, can be according to reality as the undetermined parameter of adjustment sigmoid function shape
Border demand is demarcated.A kind of corresponding relationship between the feasible ambient brightness factor and d, E is as shown in Figure 3.
Finally, 3 × 3 color correction matrix M (L) corresponding to the testing light source is inverted, and will be perfect anti-after chromatic adaptation
Beam tristimulus valuesIt remaps back in camera rgb space:
The white balance correction gain coefficient after chromatic adaptation is calculated as a result:
Using the gain coefficient to the white balance correction for carrying out being more in line with human eye visual perception to image can be realized.
It is as shown in Figure 4 that the flow chart that white balance correction gain coefficient after chromatic adaptation calculates is carried out to a certain testing light source.
Above-mentioned embodiment is only a preferred solution of the present invention, so it is not intended to limiting the invention.Have
The those of ordinary skill for closing technical field can also make various changes without departing from the spirit and scope of the present invention
Change and modification.Therefore all mode technical solutions obtained for taking equivalent substitution or equivalent transformation, all fall within guarantor of the invention
It protects in range.
Claims (5)
1. a kind of color digital camera white balance correcting based on chromatic adaptation model, which is characterized in that steps are as follows:
S1: the equipment relevant response value RGB under different Calibrating sources is converted using radical sign polynomial regression color calibration method
Device-independent tristimulus values CIE1931 XYZ under to same light source；
The S1 specifically:
S101: it is the Calibrating source L of P (λ) for spectral power distribution, constitutes model using camera response and calculate standard color card
Camera rgb value r of i-th of color lump under light source illuminationi、giAnd bi:
ρ in formulai(λ) indicates the spectral reflectance of i-th of color lump, Sk(λ) indicates the spectral sensitivity functions in k-th of channel of camera,
K=R, G, B, Ω ' are the wave-length coverage of camera spectral response；For there is the standard color card of N number of color lump, N × 3 are calculated
Camera response Matrix C (L), wherein the camera rgb value of the corresponding color lump of every a line；
S102: the camera rgb value r that reflecting surface is improved under the Calibrating source is calculatedill、gillAnd bill:
And record itsCoordinate in plane
S103: it is the Calibrating source of P (λ) for spectral power distribution, uses 2 ° of standard observer's color matching functions of CIE1931Calculate CIE1931 XYZ tristimulus values of i-th of the color lump of standard color card under light source illumination:
Ω is the wave-length coverage of visible light in formula；For there is the standard color card of N number of color lump, the tristimulus of N × 3 is calculated
Value matrix T (L), wherein the XYZ tristimulus values of the corresponding color lump of every a line；
S104: the dimension of camera response Matrix C (L) is extended to N × q, q > 3 by N × 3, wherein 4~q column correspondence is each
The radical sign multinomial of color lump response；
S105: using least square method or other correction matrix optimization methods using color difference as objective function, after calculating extension
Camera response Matrix C ' (L) conversion to T (L) 6 × 3 color correction matrix M ' (L):
When using the root-mean-square error between C ' (L) M ' (L) and T (L) as optimization aim, M ' (L) is carried out using pseudoinverse technique
It calculates:
M ' (L)=[C 'T(L)C′(L)]-1C′T(L)·T(L),
When using the color difference between C ' (L) M ' (L) and T (L) as optimization aim, using nonlinear optimization method to M ' (L) into
Row calculates:
M ' (L)=argmin Δ E (C ' (L) M ' (L), T (L)),
Δ E (A, B) is the function for calculating the color difference between A and B in formula；
S106: 3 × 3 color correction matrix M (L) under each Calibrating source are calculated using the method in S105；
S107: for all Calibrating sources, respective color correction matrix M ' (L) is calculated using the method for S101~S106
With M (L), and it is stored in camera internal memory；
S2: obtaining the white balance correction gain coefficient of the image shot under light source to be corrected, calculates light source to be corrected and existsIt is flat
Coordinate on face, in cameraSearch and the nearest Calibrating source of the coordinate distance, call the Calibrating source pair in plane
The color correction matrix answered is converted the relevant camera response of the equipment of the light source into CIE1931 XYZ space, by light source
Color is considered as object color；
S3: standard sources of the object color after chromatic adaptation is calculated using the chromatic adaptation transformation CAT02 in CIECAM02 colored quantum noise
Under correspondence color:
S4: corresponding color is remapped back camera rgb space using the inverse matrix of the color correction matrix, and recalculates color
White balance correction gain coefficient after adaptation.
2. as described in claim 1 based on the color digital camera white balance correcting of chromatic adaptation model, which is characterized in that
The S2 specifically:
S201: manual setting or the white balance that the image shot under light source to be corrected is obtained using existing automatic white balance algorithm
Correcting gain coefficient
S202: rgb value of the light source to be corrected on the domain camera raw is calculated:
In cameraIn plane search withApart from nearest Calibrating source L, and from camera internal memory
Call its corresponding color correction matrix M ' (L)；
S203: the camera response for improving reflecting surface under the light source to be corrected is converted using color correction matrix M ' (L)
Into CIE1931 XYZ space:
X in formulaill,Yill,ZillTristimulus values respectively in XYZ space.
3. as claimed in claim 2 based on the color digital camera white balance correcting of chromatic adaptation model, which is characterized in that
The S3 specifically:
Object color [X is calculated using the chromatic adaptation transformation CAT02 in CIECAM02 colored quantum noiseill,Yill,Zill] after chromatic adaptation
Standard sources under correspondence color:
Chromatic adaptation transformation model f in formulaCAT02Four inputs be successively object color tristimulus values to be calculated, light source to be adapted to
Tristimulus values, reference light source tristimulus values and ambient brightness factor LA。
4. as claimed in claim 3 based on the color digital camera white balance correcting of chromatic adaptation model, which is characterized in that
The ambient brightness factor is calculated using two sigmoid functions:
In formula, light source chromaticity distance d is by calculating actual light source and reference light source chromaticity in CIELUV homogeneous color space
Euclidean distance obtains, a1、b1、K1、a2、b2、K2As the undetermined parameter of adjustment sigmoid function shape, E is scene illumination.
5. as claimed in claim 4 based on the color digital camera white balance correcting of chromatic adaptation model, which is characterized in that
The S4 specifically:
It inverts to corresponding 3 × 3 color correction matrix M (L) of Calibrating source L, and reflector will be improved after chromatic adaptation
Tristimulus valuesIt remaps back in camera rgb space:
The white balance correction gain coefficient after chromatic adaptation is calculated as a result,
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| JP4960597B2 (en) * | 2005-02-22 | 2012-06-27 | キヤノン株式会社 | White balance correction apparatus and method, and imaging apparatus |
| JP2007141737A (en) * | 2005-11-21 | 2007-06-07 | Sharp Corp | LIGHTING DEVICE, LIQUID CRYSTAL DISPLAY DEVICE, LIGHTING DEVICE CONTROL METHOD, LIGHTING DEVICE CONTROL PROGRAM, AND RECORDING MEDIUM |
| CN100551081C (en) * | 2007-04-23 | 2009-10-14 | 北京中星微电子有限公司 | A kind of method and device of realizing white balance correction |
| CN103200410B (en) * | 2013-04-01 | 2015-07-08 | 上海富瀚微电子股份有限公司 | White balance control method and white balance control device |
| CN103905803B (en) * | 2014-03-18 | 2016-05-04 | 中国科学院国家天文台 | A kind of color calibration method of image and device |
| CN104010176B (en) * | 2014-03-26 | 2016-04-13 | 云南师范大学 | One utilizes human eye to realize from display to printer color calibration method |
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