CN115272496A - Method for realizing color enhanced imaging based on spectral migration - Google Patents

Method for realizing color enhanced imaging based on spectral migration Download PDF

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CN115272496A
CN115272496A CN202210581142.6A CN202210581142A CN115272496A CN 115272496 A CN115272496 A CN 115272496A CN 202210581142 A CN202210581142 A CN 202210581142A CN 115272496 A CN115272496 A CN 115272496A
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light
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金虹辛
贾飞
贾伟
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Xiaoyuan Perception Beijing Technology Co ltd
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    • G06T7/90—Determination of colour characteristics
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    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • 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 provides a method for realizing color enhanced imaging based on spectrum migration, which comprises the steps of collecting imaging information including ultraviolet and/or near infrared and visible light intensity through a visible light imaging lens including ultraviolet and/or near infrared spectrum; calculating the imaging intensity In of the ultraviolet and/or near-infrared color channel of each pixel pointUVAnd/or InNIRCalculating the hue H of HSaIn color space of each pixel point of visible lightVLSaturation SaVLAnd intensity value InVL(ii) a Passing InIN＝InVL+InUV+InNIR，InN＝InOUT＝LUT(InIN)，SaIN＝SaVL，SaN＝SaOUT＝LUT(SaIN)，HN＝HVICalculating output color data HN、SaN、InN(ii) a X reconverting to a new XYZ color spaceN，YN，ZNThe value is obtained. According to the invention, by a brand new technical theory and by means of the imaging spectrum energy of the near infrared band and/or the ultraviolet band, the imaging spectrum energy is transferred according to the method of the invention, the signal-to-noise ratio of night imaging is improved, the full-color imaging effect is greatly improved, and the effect that the imaging is clearer and more visible is realized.

Description

Method for realizing color enhanced imaging based on spectrum migration
Technical Field
The invention relates to the technical field of imaging, in particular to a method for realizing color enhanced imaging based on spectral migration.
Background
With the development of society, the demand of video camera apparatuses for color imaging in an extremely dark environment is increasing, and the demand field is becoming wider. The color imaging device can play an important role in a very dark environment from mobile phone shooting, intelligent automobile shooting, field shooting, safety monitoring and various large-scale engineering projects.
The conventional monitoring equipment can hardly realize effective monitoring under the low-illumination environmental condition at night, and some scenes can not or are not suitable for erecting a light source in a large area, so that the common camera does not work under the low-illumination environment.
Although the infrared camera can shoot at night, certain defects still exist. The infrared camera cannot well reflect the ambient environment conditions; meanwhile, the image has a single color, usually black and white or red and blue, and cannot reflect the color of the scene. Due to the imaging principle and the manufacturing process of the infrared camera, the definition of the infrared camera is not high, and the requirement of high-definition watching cannot be met.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides a method for realizing color enhanced imaging based on spectrum migration, provides a new solution for the problems existing in video monitoring under the condition of low illumination at night at present, can effectively improve the color shooting effect of a camera under various low illumination environments, and realizes full-color imaging under ultra-low illumination. By a brand new technical theory and by means of imaging spectrum energy of near infrared bands and/or ultraviolet bands, the imaging spectrum energy is transferred according to the method, the signal-to-noise ratio of night imaging is improved, the full-color imaging effect is greatly improved, and the effect that imaging is clearer and more visible is achieved.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for realizing color enhanced imaging based on spectral shift comprises the following steps:
step 1: collecting imaging information including ultraviolet and/or near-infrared and visible light intensity through a visible light imaging lens including ultraviolet and/or near-infrared spectrum;
and 2, step: acquiring multispectral image information R, G and B through a CMOS image sensor capable of receiving imaging intensity information comprising ultraviolet and/or near infrared and visible light, wherein the R, G and B are original RGB image information, and the R, G and B of the RGB image information are approximate to X, Y and Z in XYZ color space in engineering;
and step 3: calculating the ultraviolet and/or near-infrared color channel imaging intensity: intensity of ultraviolet light InUVAnd/or intensity of near infrared light InNIR；
Extracting visible light information X from XYZ color spaceVL，YVL，ZVL；ZVLI.e. original XYZ color space information XO， YO，ZO；
And 4, step 4: h of each pixel point of visible light is calculated through an HSaIn color space and a (X, Y, Z) interconversion modelVL、SaVL、InVL；HVL、SaVL、InVLHue, saturation and intensity values of the HSaIn color space, respectively;
and 5: passing InN＝InOUT＝LUT(InIN)＝LUT(InVL+InUV+InNIR) Or InN＝InOUT＝LUT(InIN)＝LUT(InVL+InUV) Or InN＝InOUT＝LUT(InIN)＝LUT(InVL+InNIR)，
SaN＝SaOUT＝LUT(SaIN)＝LUT(SaVL)，HN＝HVLCalculating output color data HN、SaN、InN；
Wherein: inNAs light intensity value of the new HSaIn color space, saNAs a saturation value of the new HSaIn color space, HNA hue value for the new hsalin color space;
the LUT is an operation function in the field of color calculation, and means that each color information can obtain a new color information after being repositioned by the LUT;
InOUTis the intensity output; sa (Sa)OUTIs the saturation output;
InINis an intensity input; sa (Sa)INIs the saturation input;
InVLis the intensity of visible light;
HVLis a color adjustment value of visible light;
SaVLis a visible light saturation value;
step 6: converting the new color data H of HSaIn color space into (X, Y, Z) color data HN、SaN、InNX converted into a new XYZ color spaceN，YN，ZNThe value is obtained.
Further, the ultraviolet and/or near-infrared color channel imaging intensity InUVAnd/or InNIRThe following:
ultraviolet light and near infrared light do not have color tone and color quantity, and the color tone value H and the color quantity Cl value are both 0, namely: h =0, cl =0, and using the light intensity In = Gl + Cl, it is found that the light intensity of the ultraviolet light and the near-infrared light is equal to the gray level Gl thereof, that is:
InUV＝GlUV，InNIR＝GlNIR
GlUVis the ash value of the ultraviolet light;
GlNIRis the gray scale value of the near infrared light.
Further, the saturation input value SaINAnd light intensity input value InINIs calculated as follows:
SaIN＝SaVL＝ClVL/InVL；
InIN＝InVL+InUV+InNIR；
ClVLis the color value of visible light.
Further, in step 5, the operation of the LUT is:
determining an intensity mapping relation and a saturation mapping relation under a constant hue plane according to color gamuts of input equipment and output equipment, a color distribution range of an image and a color rendering intention;
input device side color data In of image according to intensity mapping relationship and saturation mapping relationshipIN、SaINTo output device side color data InOUT、SaOUTObtaining color data Sa in HSaIn format on the output device side by mappingN、InN。
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a method for realizing color enhanced imaging based on spectrum migration, provides a new solution for the problems of video monitoring under the condition of low illumination at night at the present stage, can effectively improve the color shooting effect of a camera under various low illumination environments, and realizes full-color imaging under ultra-low illumination. By a brand new technical theory and by means of imaging spectrum energy of near infrared bands and/or ultraviolet bands, the imaging spectrum energy is transferred according to the method, the signal-to-noise ratio of night imaging is improved, the full-color imaging effect is greatly improved, and the effect that imaging is clearer and more visible is achieved.
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FIG. 1 is a flow chart of a method for realizing color enhanced imaging based on spectral shift according to the present invention;
FIG. 2 is a graph of the intensity mapping of the present invention;
FIG. 3 is a saturation map of the present invention;
FIG. 4 is a diagram of a common shooting effect in a low-light environment at night;
FIG. 5 is a diagram of the effect of the present invention in low light environment at night.
Detailed Description
The following detailed description of the present invention will be made with reference to the accompanying drawings.
As shown in fig. 1, a method for implementing color enhanced imaging based on spectral shift according to the present invention includes the following steps:
step 1: collecting imaging information including ultraviolet and/or near infrared and visible light intensity through a visible light imaging lens including ultraviolet and/or near infrared spectrum;
step 2: acquiring multispectral image information R, G and B through a CMOS image sensor capable of receiving imaging intensity information including ultraviolet and/or near infrared and visible light, wherein R, G and B are original RGB image information, and R, G and B of the RGB image information are similar to X, Y and Z in XYZ color space in engineering;
and step 3: calculating the ultraviolet and/or near-infrared color channel imaging intensity: intensity of ultraviolet light InUVAnd/or intensity In of near infrared lightNIR；
Extracting visible light information X from XYZ color spaceVL，YVL，ZVL；XVL、YVL、ZVLI.e. original XYZ color space information XO，YO，ZO；
And 4, step 4: h of each pixel point of visible light is calculated through an HSaIn color space and a (X, Y, Z) interconversion modelVL、SaVL、InVL；HVL、SaVL、InVLHue, saturation and intensity values of the HSaIn color space, respectively;
and 5: by InN＝InOUT＝LUT(InIN)＝LUT(InVL+InUV+InNIR) Or InN＝InOUT＝LUT(InIN)＝LUT(InVL+InUV) Or InN＝InOUT＝LUT(InIN)＝LUT(InVL+InNIR)，
SaN＝SaOUT＝LUT(SaIN)＝LUT(SaVL)，HN＝HVLCalculating output color data HN、SaN、InN；
Wherein: inNAs light intensity value of new HSaIn color space, saNIs a new saturation value of HSaIn color space, HNHue value for the new hsalin color space;
the LUT is an operation function in the field of color calculation, and means that each color information can obtain a new color information after being repositioned by the LUT;
InOUTis the intensity output; sa (Sa)OUTIs the saturation output;
InINis the intensity input; sa (Sa)INIs the saturation input;
InVLthe intensity of visible light;
HVLis a color adjustment value of visible light;
SaVLis a visible light saturation value;
and 6: color data H of the new HSaIn color space is converted into color data H through the interconversion model of the HSaIn color space and (X, Y, Z)N、SaN、InNX converted into a new XYZ color spaceN，YN，ZNThe value is obtained.
Further, the ultraviolet and/or near-infrared color channel imaging intensity InUVAnd/or InNIRThe following:
the ultraviolet light and the near infrared light do not have color tone and color quantity, and the color tone value H and the color quantity Cl value are both 0, namely: h =0, cl =0, and using the light intensity In = Gl + Cl, it is found that the light intensity of the ultraviolet light and the near-infrared light is equal to the gray level Gl thereof, that is:
InUV＝GlUV，InNIR＝GlNIR
GlUVis the gray scale value of the ultraviolet light;
GlNIRis the gray scale value of near infrared light.
Light intensity In of ultraviolet lightUVI.e. ash value GlUVAnd light intensity In of near infrared lightNIRI.e. ash value GlNIRAcquired by one or several joint image sensors of the prior art or deduced by algorithms of the prior art.
Further, the saturation input value SaINAnd light intensity input value InINIs calculated as follows:
SaIN＝SaVL＝ClVL/InVL；
InIN＝InVL+InUV+InNIR；
ClVLis the value of the color of visible light.
Further, in step 5, the operation of the LUT is:
determining an intensity mapping relation and a saturation mapping relation under a tone surface according to color gamut of input equipment and output equipment, color distribution range of an image and a color rendering intention;
input device side color data In of image according to intensity mapping relation and saturation mapping relationIN、SaINTo output device side color data InOUT、SaOUTObtaining color data Sa in HSaIn format on the output device side by mappingN、InN。
The mapping is shown in the maps of fig. 2-3.
In the above description, the variables and subscripts are explained as follows:
UV: ultraviolet light;
NIR: near infrared light;
VL: visible light;
n: a new function generated after system operation;
o: a system inputs an old function before operation;
IN: a function input in a system operation;
OUT: a function of the output of the system operation.
And as shown in fig. 4-5, the image is enhanced according to the calculated new image color data, so that the video image acquisition under the low-illumination environment at night is realized.
Specific example 1: imaging lens and CMOS image sensor
Visible light, light waves that are perceivable by the human eye, has a wavelength of about 780nm to about 400 nm. Light waves above and below this interval are not perceptible to the human eye. Light waves having a wavelength higher than 780nm and lower than microwaves are infrared light, and infrared light is classified into near infrared rays, middle infrared rays and far infrared rays. Light waves with a wavelength below 400nm and above the X-ray are ultraviolet light.
In the step 1, the imaging lens adopts a camera lens subjected to film coating treatment to realize near infrared band and/or ultraviolet band imaging energy acquisition; realizing the confocal of ultraviolet, near infrared and visible light.
In the step 2, the invention adopts a CMOS image sensor which can receive ultraviolet, near infrared and visible light wave bands and realize multispectral image data acquisition.
The ultraviolet light, the near infrared light and the visible light all have linear superposition of imaging light intensity. The camera collects light signals (including ultraviolet light, near infrared light and visible light) in a low-illumination environment, and the strength of the monochromatic light signals of the camera is about 11.5 times that of the monochromatic light signals in the visible light (the strength of the ultraviolet light is 1.5 times, the strength of the near infrared light is 9 times, and the strength of the monochromatic light is 1 time).
The camera adopted by the invention only collects ultraviolet light, visible light and near infrared light for the following reasons:
1) The intensity of the reflected light of the object to ultraviolet light, visible light and near-infrared light is proportional to the intensity of the irradiated light, i.e. at a certain absorption rate, the higher the intensity of the irradiated light, the higher the intensity of the reflected light, and vice versa.
2) The lens glass has high compatibility to ultraviolet light, visible light and near infrared rays. Lens glass which can simultaneously transmit ultraviolet light, visible light and near infrared light is easy to obtain.
3) The imaging information including ultraviolet light, visible light and near infrared light spectrum can be obtained by selecting proper optical glass with wide-spectrum transmittance and changing the film coating spectrum of the lens.
4) It is necessary to acquire ultraviolet and near infrared imaging signals and visible light spectrum CMOS imaging signals for color enhancement algorithms.
Specific example 2: HSaIn color space model
A color space is a mathematical expression that describes the law of perception of color by the human eye.
1. HSaIn color space, its relationship with XYZ color space
1) HSaIn color space
Hsalin color space, comprising hue H, saturation Sa, intensity In.
2) Relationship between HSaIn color space and XYZ color space
Engineering approximation (R, G, B) = (X, Y, Z)
3) Definition of HSaIn color space related parameters
The shade of a solid color is called gray and is described by the amount of gray defined below, the shade is called color and the color is described by the amount of color defined below.
Ash Level Gray Level (Gl): the color light intensity stimulus value is defined as the gray color light. The effective range of gray levels is 0-white saturation.
Chrominance Level of color vector
Figure BDA0003663779260000061
The stimulus value, defined as the brightness of a pure colored shade at a single hue, is a vector. Vector of color quantities
Figure BDA0003663779260000062
Contains dual orthogonal information of the chroma stimulus value (modulo Cl of the chroma vector, chroma for short) and the chroma hue (direction, hue for short). The effective range of the color stimulus value is 0-color light saturation value.
Hue H (Hue): stimulus value of the human eye to the visual perception of the color attributes of the colored light. Is a component of a vector of color quantities, and the hue is described by the polar angle of the vector, or the hue angle, which ranges from 0,360 deg..
Stimulus value of color light Intensity In (Intensity): sum of gray amount stimulus value and color amount stimulus value of the colored light. In = Gl + Cl.
Saturation Sa (Saturation): the color quantity stimulation value of the colored light accounts for the proportion of the color light intensity stimulation value. Sa = Cl/In.
2. The XYZ color space (X, Y, Z) values are converted to HSaLn color space values.
Hue H in hsalin format color data obtained according to the following formula.
Figure BDA0003663779260000071
Wherein, X, Y, Z are color data in XYZ format, that is, tristimulus values of the color data in the XYZ color space, and respectively represent numerical values on X, Y, Z coordinate axes of the XYZ color space.
The saturation Sa and the intensity In the hsaain format color data are obtained according to the following formula and based on the XYZ format color data, i.e., the Sa and In values are obtained by the X, Y, Z values.
Gl＝Km[Min(X,Y,Z)]p+A,In＝KM[Max(X,Y,Z)]q+B,Cl＝In-Gl,
Figure BDA0003663779260000072
Km,KMThe real number is positive, in is more than or equal to Gl is more than or equal to 0, A is more than or equal to 0, B is more than or equal to 0, p and q are non-zero real numbers.
Or
Gl＝Km[Min(X,Y,Z)]p+A,
Figure BDA0003663779260000073
Cl＝In-Gl,
Figure BDA0003663779260000074
Km, KM is positive real number, KM is more than Km, in is more than or equal to Gl and more than or equal to 0, A is more than or equal to 0, B is more than or equal to 0, p and q are non-zero real numbers.
Or
Gl＝KmMin(X,Y,Z)p+A,
Figure BDA0003663779260000075
Cl＝In-Gl,
Figure BDA0003663779260000076
Km and KM are positive real numbers, KM is more than Km, in is more than or equal to Gl and more than or equal to 0, A is more than or equal to 0, B is more than or equal to 0, p, q is a non-zero real number.
Or
Gl＝KmMin(X,Y,Z)p+A,
Figure BDA0003663779260000077
In＝Gl+Cl,
Figure BDA0003663779260000078
Km and KM are positive real numbers, in is more than or equal to Gl and more than or equal to 0, A is more than or equal to 0, B is more than or equal to 0, p and m is a non-zero real number.
Or
Gl＝KmMin(X,Y,Z)r+A,
Figure BDA0003663779260000079
Cl＝In-Gl,
Figure BDA00036637792600000710
Km and KM are positive real numbers, KM is more than Km and more than 0, in is more than or equal to Gl and more than or equal to 0, A is more than or equal to 0, B is more than or equal to 0, p, q and r are nonzero real numbers.
Or alternatively
Gl＝KmMin(X,Y,Z)r+A,
Figure BDA0003663779260000081
In＝Gl+Cl,
Figure BDA0003663779260000082
Km and KM are positive real numbers, in is more than or equal to Gl and more than or equal to 0, A is more than or equal to 0, B is more than or equal to 0, p, q and r are nonzero real numbers.
3. Conversion of HSaLn color space values to XYZ color space (X, Y, Z) values
The saturation Sa and the intensity In the hsalin format color data as the input device side are obtained according to the following formulas:
Gl＝Km[Min(X,Y,Z)]p+A,In＝KM[Max(X,Y,Z)]q+B,Cl＝In-Gl,
Figure BDA0003663779260000083
Km，KMthe real number is positive, in is more than or equal to Gl is more than or equal to 0, A is more than or equal to 0, B is more than or equal to 0, p and q are non-zero real numbers.
The XYZ-format color data on the output device side is acquired according to the following formula:
Figure BDA0003663779260000084
alternatively, the saturation Sa and the intensity In the hsajn format color data as the input device side are obtained according to the following formulas:
Gl＝Km[Min(X,Y,Z)]p+A,
Figure BDA0003663779260000085
Cl＝In-Gl,
Figure BDA0003663779260000086
km and KM are positive real numbers, KM is more than Km, in is more than or equal to Gl and more than or equal to 0, A is more than or equal to 0, B is more than or equal to 0, p, q is a non-zero real number.
XYZ-format color data on the output device side is acquired according to the following formula:
h is more than or equal to 0 degree and less than 120 degrees
Figure BDA0003663779260000087
H is more than or equal to 120 degrees and less than 240 degrees
Figure RE-GDA0003849220310000092
Figure BDA0003663779260000092
Figure BDA0003663779260000093
H is more than or equal to 240 degrees and less than 360 degrees
Figure BDA0003663779260000094
Figure BDA0003663779260000095
Figure BDA0003663779260000096
Alternatively, the saturation Sa and the intensity In the hsalin format color data as the input device side are obtained according to the following formulas:
Gl＝KmMin(X,Y,Z)p+A,
Figure BDA0003663779260000097
Cl＝In-Gl,
Figure BDA0003663779260000098
km and KM are positive real numbers, KM is more than Km, in is more than or equal to Gl and more than or equal to 0, A is more than or equal to 0, B is more than or equal to 0, p, q is a non-zero real number.
The XYZ-format color data on the output device side is acquired according to the following formula:
Figure BDA0003663779260000101
alternatively, the saturation Sa and the intensity In the hsajn format color data as the input device side are obtained according to the following formulas:
Gl＝KmMin(X,Y,Z)p+A,
Figure BDA0003663779260000102
In＝Gl+Cl,
Figure BDA0003663779260000103
km and KM are positive real numbers, in is more than or equal to Gl and more than or equal to 0, A is more than or equal to 0, B is more than or equal to 0, p and m is a non-zero real number.
The XYZ-format color data on the output device side is acquired according to the following formula:
Figure BDA0003663779260000104
[·]is the operator of pair, H ∈ [0 °,360 °), H =0,1,2
If h =0
Figure BDA0003663779260000105
If h =1
Figure BDA0003663779260000106
If h =2
Figure BDA0003663779260000107
Alternatively, the saturation Sa and the intensity In as In the hsalin format color data on the input device side are obtained according to the following formulas,
Gl＝KmMin(X,Y,Z)r+A,
Figure BDA0003663779260000111
Cl＝In-Gl,
Figure BDA0003663779260000112
km and KM are positive real numbers, KM is more than Km and more than 0, in is more than or equal to Gl and more than or equal to 0, A is more than or equal to 0, B is more than or equal to 0, p, q, r are nonzero real numbers.
XYZ-format color data on the output device side is acquired according to the following formula:
Figure BDA0003663779260000113
[·]is an integer of a, H ∈ [0 °,360 °), H =0,1,2
If h =0
Figure BDA0003663779260000114
Figure BDA0003663779260000115
Figure BDA0003663779260000116
And obtaining the X and Y values expressed by In, sa, H, p, q and r according to the specific values of p, q and r, wherein X > Z is more than or equal to 0, Y > Z is more than or equal to 0, and Z is a value which accords with the physical practical situation.
If h =1
Figure BDA0003663779260000117
Figure BDA0003663779260000118
And obtaining the X and Y values expressed by In, sa, H, p, q and r according to the specific values of p, q and r, wherein X > Z is more than or equal to 0, Y > Z is more than or equal to 0, and Z is a value which accords with the physical practical situation.
If h =2
Figure BDA0003663779260000119
Figure BDA0003663779260000121
Figure BDA0003663779260000122
And obtaining the X and Y values expressed by In, sa, H, p, q and r according to the specific values of p, q and r, wherein X > Z is more than or equal to 0, Y > Z is more than or equal to 0, and Z is a value which accords with the physical practical situation.
Alternatively, the saturation Sa and the intensity In the hsalin format color data as the input device side are obtained according to the following formulas:
Gl＝KmMin(X,Y,Z)r+A,
Figure BDA0003663779260000123
In＝Gl+Cl,
Figure BDA0003663779260000124
km and KM are positive real numbers, in is more than or equal to Gl and more than or equal to 0, A is more than or equal to 0, B is more than or equal to 0, p, q and r are nonzero real numbers.
The XYZ-format color data on the output device side is acquired according to the following formula:
Figure BDA0003663779260000125
[·]is an integer of a, H ∈ [0 °,360 °), H =0,1,2
If h =0
Figure BDA0003663779260000126
If h =1
Figure BDA0003663779260000127
If h =2
Figure BDA0003663779260000131
The variables in the above formula that are not paraphrased are common knowledge variables.
The above embodiments are implemented on the premise of the technical solution of the present invention, and detailed embodiments and specific operation procedures are given, but the scope of the present invention is not limited to the above embodiments. The methods used in the above examples are conventional methods unless otherwise specified.

Claims (4)

1. A method for realizing color enhanced imaging based on spectral shift is characterized by comprising the following steps:
step 1: collecting imaging information including ultraviolet and/or near infrared and visible light intensity through a visible light imaging lens including ultraviolet and/or near infrared spectrum;
and 2, step: acquiring multispectral image information R, G and B through a CMOS image sensor capable of receiving imaging intensity information including ultraviolet and/or near infrared and visible light, wherein R, G and B are original RGB image information, and R, G and B of the RGB image information are similar to X, Y and Z in XYZ color space in engineering;
and 3, step 3: calculating the imaging intensity of the ultraviolet and/or near-infrared color channel: intensity of ultraviolet light InUVAnd/or intensity In of near infrared lightNIR；
Extracting visible light information X from XYZ color spaceVL，YVL，ZVL；XVL、YVL、ZVLI.e. original XYZ color space information XO，YO，ZO；
And 4, step 4: calculating H of each pixel point of visible light through a mutual conversion model of HSaIn color space and XYZ color spaceVL、SaVL、InVL；HVL、SaVL、InVLThe hue, saturation and intensity value of visible light in the HSaIn color space are respectively;
and 5: passing InN＝InOUT＝LUT(InIN)＝LUT(InVL+InUV+InNIR) Or InN＝InOUT＝LUT(InIN)＝LUT(InVL+InUV) Or InN＝InOUT＝LUT(InIN)＝LUT(InVL+InNIR)，
SaN＝SaOUT＝LUT(SaIN)＝LUT(SaVL)，HN＝HVLCalculating output color data HN、SaN、InN；
Wherein: inNAs light intensity value of the new HSaIn color space, saNSaturation for new HSaIn color spaceValue of HNHue value for the new hsalin color space;
the LUT is an operation function in the field of color calculation, and means that each color information can obtain a new color information after being repositioned by the LUT;
InOUTis the intensity output; sa (Sa)OUTIs the saturation output;
InINis the intensity input; sa (Sa)INIs the saturation input;
InVLthe intensity of visible light;
HVLthe color adjustment value of the visible light is obtained;
SaVLis a visible light saturation value;
and 6: converting the new color data H of HSaIn color space into (X, Y, Z) color data HN、SaN、InNX converted into a new XYZ color spaceN，YN，ZNThe value is obtained.
2. The method of claim 1, wherein the UV and/or NIR color channel imaging intensity In is selected from the group consisting of In, inUVAnd/or InNIRThe following were used:
ultraviolet light and near infrared light do not have color tone and color quantity, and the color tone value H and the color quantity Cl value are both 0, namely: h =0, cl =0, using light intensity In = Gl + Cl, it is found that the light intensity of the ultraviolet light and the near-infrared light is equal to the gray level Gl thereof, i.e.:
InUV＝GlUV，InNIR＝GlNIR
GlUVis the ash value of the ultraviolet light;
GlNIRis the gray scale value of near infrared light.
3. The method for realizing color enhanced imaging based on spectral shift according to claim 1, wherein the saturation input value SaINAnd light intensity input value InINIs calculated as follows:
SaIN＝SaVL＝ClVL/InVL；
InIN＝InVL+InUV+InNIR；
ClVLis the value of the color of visible light.
4. The method for realizing color enhanced imaging based on spectrum migration according to claim 1, wherein in the step 5, the operation of the LUT is as follows:
determining an intensity mapping relation and a saturation mapping relation under a constant hue plane according to color gamuts of input equipment and output equipment, a color distribution range of an image and a color rendering intention;
input device side color data In of image according to intensity mapping relationship and saturation mapping relationshipIN、SaINTo output device side color data InOUT、SaOUTObtaining the HSaIn format color data Sa of the output device side by mappingN、InN。
CN202210581142.6A 2022-05-26 2022-05-26 Method for realizing color enhanced imaging based on spectral migration Pending CN115272496A (en)

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