CN105303515B - A kind of color misregistration correction method under special illumination condition in closed experimental box - Google Patents
A kind of color misregistration correction method under special illumination condition in closed experimental box Download PDFInfo
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- CN105303515B CN105303515B CN201510606556.XA CN201510606556A CN105303515B CN 105303515 B CN105303515 B CN 105303515B CN 201510606556 A CN201510606556 A CN 201510606556A CN 105303515 B CN105303515 B CN 105303515B
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- 238000005286 illumination Methods 0.000 title claims abstract description 9
- 238000012545 processing Methods 0.000 claims abstract description 9
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000002708 enhancing effect Effects 0.000 abstract description 3
- 210000001525 retina Anatomy 0.000 abstract description 2
- 210000003710 cerebral cortex Anatomy 0.000 abstract 1
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
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Abstract
The invention discloses a kind of methods for color cast correction under special illumination condition in closed experimental box,First to pixel R each in a width coloured image,G,The gray value of B triple channels is compared,To R,G,The pixel of channel B gray value maximum or G channels gray value maximum is not dealt in B triple channels,Rest of pixels R,G,The gray value of B triple channels is equal to the gray value of pixel G channels,Then treated, image is added with original image respective pixel averages,Obtain the image after a width preliminary corrections,Image after correction is transformed into hsv color space,Histogram equalization enhancing processing is carried out to V component,Then multiple dimensioned retina cerebral cortex theory is recycled to further enhance processing,Finally convert back RGB color,And entire image is slightly adjusted with Garmma curves,The final image obtained after a width color cast correction.The present invention is solved in closed experimental box due to the limitation image color cast phenomenon of light source, makes image more true, natural.
Description
Technical field
The present invention relates to a kind of method in partially red inclined half-light source hypograph color cast correction, suitable for Computer Image Processing
Field, especially suitable for space life science image processing field.
Background technology
To meet the normal growth and development of plant in airtight space experimental box, white and red light source are needed, special
Under illumination condition, specially treated only is carried out to the picture of shooting, can be only achieved good visual effect, space life science is ground
Study carefully just smooth.
The technology for being presently used for color cast correction is quite ripe, wherein there is histogram equalization method, Garmma corrections are calculated
Method, Retinex methods etc..But these methods respectively have limitation, and histogram equalization method can integrally improve the contrast of image, right
Preferable effect can be played in black white image, but for coloured image, histogram equalization is distinguished to R, G, B triple channel, due to
The correlation of each Color Channel is had ignored, the result finally handled will appear serious color offset phenomenon;Garmma correcting algorithms
The contrast of entire image can be non-linearly adjusted, but for coloured image, adjustment by a small margin can only be done, otherwise can gone out
Existing color offset phenomenon;Rgb color space is transformed at other color spaces (HSV color spaces) by color space transformation approach
Reason, wherein, H component representative image tones, S component representative image saturation degrees, V component representative image brightness, only pair with coloration without
The luminance component of pass is corrected, and therefore, it is possible to improve the brightness of image, while retains preferable colour information;Retina is big
Cortex (Retinex) method is mainly to decomposite the high frequency section of image, due to the details of high frequency section main representative image
Part, therefore this method keeps very effectively details, which extends three kinds of different types of algorithms, single scale
Retinex algorithm, multi-Scale Retinex Algorithm, the Retinex algorithm with color recovery.Due to single scale algorithm dynamic range
Compress it is poor, details holding on it is not good enough, therefore, improved on the basis of single scale Retinex, it is proposed that more rulers
Retinex enhancing algorithms are spent, multiple dimensioned Retinex detail sections enhancing is preferable, but cross-color, in order to solve this problem,
The multi-Scale Retinex Algorithm with color recovery is introduced on the basis of multiple dimensioned Retinex, with the multiple dimensioned of color recovery
Retinex algorithm can protect to a certain extent due to introducing the proportionate relationship in original image between three Color Channels
Image color is held, still, the algorithm is more complicated, and the parameter in algorithm is not easy to determine.Therefore, other color spaces are transformed into
It is handled, only a pair component unrelated with coloration is corrected, and could retain the color information of image, required for being color cast correction
One step of key.
Invention content
It is an object of the invention to solve the partially red inclined dim phenomenon of the image in airtight space plant incubator under special light sources,
The processing method can make image it is truer, naturally, with good visual effect.
A kind of processing step of color misregistration correction method under special illumination condition in closed experimental box is:
(1), piece image is read in the closed plant incubator with special illumination condition;
(2), R, G, B triple channel gray value size in each pixel of movement images, it is maximum for G channels gray value in pixel
Or the pixel of channel B gray value maximum is not dealt with, the gray value of each channel of rest of pixels is set as the G channels at the pixel
Gray value;
(3), step (2), treated that image is added with the image respective pixel in (1) averages;
(4), the image in step (3) is transformed into hsv color spatial manipulation;
(5), to the V component in step (4), i.e. luminance component carries out histogram equalization operation;
(6), multi-Scale Retinex Algorithm processing, i.e. three single scales are carried out to step (5) treated V component
Retinex algorithm weighted sum obtains W (x, y):
In formula:(x, y) be V component pixel position, i be single scale sequence number, ωiFor the weighting coefficient of i-th of scale,
Take ω1=ω2=ω3=1/3;Ri(x, y) calculation formula is:
In formula:I (x, y) is V component value at (x, y), σiFor the Gauss scale parameter of i-th of scale, i=1,2,3;Take σ1
=90, σ2=160, σ3=10;
(7), to step (6), treated, and image converts back RGB color;
(8), to step (7), treated that tri- channels of image R, G, B carry out respectively that identical Garmma is bent
Line corrects, and formula is:
Wherein, I2i(u, v) represents i-th of channel gray value in the pixel exported at image (u, v), I1i(u, v) represents defeated
Enter the gray value of i-th of channel in pixel at image (u, v).
Advantages of the present invention:
(1), the present invention reduces the partially red phenomenon of image, and can reduce red light source influences caused by picture quality.
(2), the present invention efficiently solves the inclined dim phenomenon of image, and even if in closed camera bellows can show good
Visual effect.
Description of the drawings
Fig. 1 is disposed of in its entirety method flow diagram.
Fig. 2 is confirmatory experiment result flow chart.
Specific embodiment
The present invention has carried out the plant in airtight space experimental box imaging experiment, and has carried out colour cast to formed image
Correction process, while a blank sheet of paper is put beside plant, with as a control group, handling result shows that picture quality has very big change
It is kind.The specific implementation step that image procossing is verified with handling result is:
(1), piece image is read in the closed plant incubator with special illumination condition;
(2), R, G, B triple channel gray value size in each pixel of movement images, it is maximum for G channels gray value in pixel
Or the pixel of channel B gray value maximum is not dealt with, the gray value of each channel of rest of pixels is set as the G channels at the pixel
Gray value;
(3), step (2), treated that image is added with the image respective pixel in (1) averages;
(4), the image in step (3) is transformed into hsv color spatial manipulation;
(5), to the V component in step (4), i.e. luminance component carries out histogram equalization operation;
(6), multi-Scale Retinex Algorithm processing, i.e. three single scales are carried out to step (5) treated V component
Retinex algorithm weighted sum obtains W (x, y):
In formula:(x, y) be V component pixel position, i be single scale sequence number, ωiFor the weighting coefficient of i-th of scale,
Take ω1=ω2=ω3=1/3;Ri(x, y) calculation formula is:
In formula:I (x, y) is V component value at coordinate (x, y), σiFor the Gauss scale parameter of i-th of scale, i=1,2,3;
Take σ1=90, σ2=160, σ3=10;
(7), to step (6), treated, and image converts back RGB color;
(8), to step (7), treated that tri- channels of image R, G, B carry out identical Garmma curvature corrections respectively, public
Formula is:
Wherein, I2i(u, v) represents i-th of channel gray value in the pixel exported at image (u, v), I1i(u, v) represents defeated
Enter the gray value of i-th of channel in pixel at image (u, v).
(9), the blank sheet of paper part of image and the blank sheet of paper part of original image not dealt with after interception step (8) is handled respectively;
(10), two blank sheet of paper images in step (9) are handled, to verify the color cast correction side proposed in this patent
The validity of method, processing step are:
(a), absolute value is sought after subtracting each other two-by-two to R, G, B triple channel gray value of pixel in two blank sheet of paper images respectively, is obtained
To three groups of channel gray value absolute differences;
(b), compare the mean value and variance of the same channels gray value absolute difference of this two blank sheet of paper images.
Claims (1)
- A kind of 1. method for color cast correction under special illumination condition in closed experimental box, it is characterised in that including following step Suddenly:(1), piece image is read in the closed plant incubator with special illumination condition;(2), R, G, B triple channel gray value size in each pixel of movement images, for G channels gray value in pixel it is maximum or The pixel of channel B gray value maximum is not dealt with, and the gray value of each channel of rest of pixels is set as the ash of the G channels at the pixel Angle value;(3), step (2), treated that image is added with the image respective pixel in (1) averages;(4), the image in step (3) is transformed into hsv color spatial manipulation;(5), to the V component in step (4), i.e. luminance component carries out histogram equalization operation;(6), multi-Scale Retinex Algorithm processing is carried out to step (5) treated V component, i.e. three single scale Retinex are calculated Method weighted sum obtains W (x, y):In formula:(x, y) be V component pixel position, i be single scale sequence number, ωiFor the weighting coefficient of i-th of scale, ω is taken1 =ω2=ω3=1/3;Ri(x, y) calculation formula is:In formula:V component values of the I (x, y) for (x, y) position, σiFor the Gauss scale parameter of i-th of scale, i=1,2,3;Take σ1 =90, σ2=160, σ3=10;(7), to step (6), treated, and image converts back RGB color;(8), to step (7), treated that tri- channels of image R, G, B carry out respectively that identical gamma curve corrects, and formula is:Wherein, I2i(u, v) represents i-th of channel gray value in the pixel exported at image (u, v), I1i(u, v) represents input figure As the gray value of i-th of channel in pixel at (u, v).
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