CN106952245A - A kind of processing method and system for visible images of taking photo by plane - Google Patents
A kind of processing method and system for visible images of taking photo by plane Download PDFInfo
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Abstract
The invention discloses a kind of processing method for visible images of taking photo by plane, including：Visible images and infrared image are obtained respectively using visible light sensor and infrared sensor simultaneously, YUV color gamut conversions are carried out to visible images, to generate YUV color space images, the YUV color space images are decomposed into brightness domain Y component map picture, color gamut U component images, and color gamut V component image, Gassian low-pass filter denoising is carried out to the brightness domain Y component map picture that decomposition is obtained, to obtain brightness area image, processing is sharpened to infrared image, to obtain final sharpening image, brightness area image and final sharpening image are merged, to generate final brightness domain Y component map picture, tone saturation degree adjustment is carried out to color gamut U component images and color gamut V component image, to obtain final color domain U images and final color domain V image.The present invention can be solved in existing method using soft edge, the technical problem that details is deteriorated caused by visible images denoising, enhancing.
Description
Technical field
The invention belongs to digital image processing techniques and the crossing domain of Space Science and Technology, taken photo by plane more particularly, to one kind
The processing method and system of visible images.
Background technology
Realize that remote sensing and navigation have become a weight of Aero-Space career development using aircraft such as unmanned plane, satellites
Technical field is wanted, and all with very important application value in economic development, daily life.However, due on aircraft
The performance constraints of imaging sensor, and become increasingly complex and changeable (such as low photograph environment, foggy weather etc.) along with scene of taking photo by plane,
So that the Aerial Images noise that aircraft is got is very big, and details is fuzzy, it is impossible to meet the demand of remote sensing and navigation field,
Therefore, it is highly desirable to handle aircraft Aerial Images.
Processing to aircraft Aerial Images at present, is broadly divided into the denoising enhancing processing to visible images, and right
The enhancing processing of infrared image.Wherein, it is seen that the denoising of light is broadly divided into spatial domain denoising and time domain denoising, and spatial domain denoising can
To be carried out on a two field picture, time domain denoising then needs to carry out denoising to continuous multiple frames image reference, at the enhancing of visible ray
Reason, which then includes saturation degree and contrast, to be strengthened.
However, for the existing denoising method to visible images, can all cause soft edge, definition becomes
Difference, denoising is stronger, then loss of detail is more, so as to influence final image enhancement effects.Therefore, some scholars propose profit
With infrared image visible images are carried out with the enhancing of contrast and acutance, so that the object in picture is more obvious；However,
During the enhancing of infrared image, because infrared image only has gamma characteristic, lack the features such as texture, color, it can only enhanced scene
The edge of middle object, enhancing effect is not obvious, has little significance.In view of this, also scholar utilizes infrared image and visible ray
The mode that image is merged strengthens visible images, i.e. the directly fusion of progress two images, or only with reference to
Fusion in infrared brightness, but this mode does not have the characteristic for utilizing both images well, has only used infrared image
Light characteristic, and the color characteristic of visible ray is not considered, so this enhanced effect is also bad.
The content of the invention
For the disadvantages described above or Improvement requirement of prior art, the invention provides a kind of processing for visible images of taking photo by plane
Method and system, it is intended that solving to cause image using visible images denoising in existing Visual image processing method
Edge blurry, details are deteriorated, and lack texture color feature, and commonly red using image is caused after infrared image enhancing method
Outer image and visible light image fusion method enhancing effect is not good, technical problem to color characteristic enhancing effect difference.
To achieve the above object, according to one aspect of the present invention, there is provided a kind of processing side for visible images of taking photo by plane
Method, comprises the following steps：
(1) while obtaining visible images and infrared image G respectively using visible light sensor and infrared sensor；
(2) YUV color gamut conversions are carried out to the visible images that step (1) is obtained, to generate YUV color space images,
The YUV color space images are decomposed into brightness domain Y component map picture, color gamut U component images and color gamut V component image；
(3) Gassian low-pass filter denoising is carried out to the brightness domain Y component map picture that decomposition is obtained, to obtain brightness area image
Y’；
(4) processing is sharpened to the infrared image G that step (1) is obtained, to obtain final sharpening image G '；
(5) the final sharpening image G ' that the brightness area image Y ' and step (4) obtained step (3) is obtained is merged,
To generate new visible images Ynew；
(6) tone saturation degree tune is carried out to the color gamut U component images and color gamut V component image that are obtained in step (2)
It is whole, to obtain final color domain U images UnewWith final color domain V image Vnew；
(7) the new visible images Y for obtaining step (5)new, and the final color domain U images that step (6) is obtained
UnewWith final color domain V image VnewMerged, to obtain new YUV color space images YUVnew, and to the YUV colors
Spatial image YUVnewYUV is carried out to the conversion of RGB color, to generate final visible images.
Preferably, between the standard deviation α of the Gaussian filter function used in step (3) is 0.25 to 0.75.
Preferably, step (4) includes following sub-step：
(4-1) is filtered processing using high-pass filter to infrared image G, to generate the image G after processinghpf；
(4-2) obtains infrared image G mean μ and standard deviation sigma：
Wherein w represents infrared image G width, and h represents infrared image G height, and G (i, j) represents picture on infrared image G
The coordinate of vegetarian refreshments；
(4-3) obtains pixel G (i, j) correspondences on image G according to the mean μ and standard deviation sigma obtained in step (4-2)
High fdrequency component enhancing factor beta (i, j)：
The high fdrequency component enhancing coefficient that (4-4) is obtained according to step (4-3) and the image G that step (4-1) is obtainedhpfTo red
Outer image G carries out back add operation, to obtain initial sharpening image G "：
G " (x, y)=G (x, y)+β Ghpf(x,y)
(4-5) judge step (4-4) obtain initial sharpening image G " value be less than 0, or more than or equal to 0 and less than etc.
In 255,255 are also greater than, if less than 0, then final sharpening image G ' value 0 is set to, if greater than equal to 0 and being less than
Equal to 255, then final sharpening image G ' value is set to G " (x, y), if greater than 255, then by final sharpening image G's '
Value is set to 255.
Preferably, step (5) is specifically to use below equation：
Ynew(i, j)=γ (i, j) Y ' (i, j)+(1- γ (i, j)) G ' (i, j)
The middle operator γ of wherein above formula can be tried to achieve by following formula
γ (i, j)=0.7* α+0.3* β (i, j).
Preferably, step (6) specifically includes following sub-step：
(6-1) obtains average tone coefficient Coef according to color gamut U component images and color gamut V component image：
The tone that (6-2) obtains color gamut U component images and color gamut V component image respectively according to average tone coefficient is adjusted
Integral coefficient δuAnd δv：
Wherein τuEmpirical coefficient, τ are adjusted for the colourity of color gamut U componentsvFor the colourity adjustment experience system of color gamut V component
Number, τuAnd τvTake between 0.75~1.5.
(6-3) obtains priming color domain U images U ' according to the hue adjustment coefficient obtained in step (6-2)newWith initial face
Colour gamut V image V 'new：
U′new(i, j)=(U(i,j)-128)*δu+128
V′new(i, j)=(V(i,j)-128)*δv+128
(6-4) judges obtained priming color domain U images U ' respectivelynewWith priming color domain V image V 'newValue be difference
Less than 0, or more than or equal to 0 and less than or equal to 255,255 are also greater than, if less than 0, then by final color domain U images
UnewWith final color domain V image VnewValue be set to 0, if more than or equal to 0 and less than or equal to 255, then by final color
Domain U images UnewWith final color domain V image VnewValue be respectively set to be equal to U 'newWith V 'new, if more than 255, then will
Final color domain U images UnewWith final color domain V image VnewValue be respectively set to 255.
It is another aspect of this invention to provide that there is provided a kind of processing system for visible images of taking photo by plane, including：
First module, for obtaining visible images respectively and infrared using visible light sensor and infrared sensor simultaneously
Image G；
Second module, the visible images for being obtained to the first module carry out YUV color gamut conversions, to generate YUV face
Colour space image, brightness domain Y component map picture, color gamut U component images and color are decomposed into by the YUV color space images
Domain V component image；
3rd module, the brightness domain Y component map picture for being obtained to decomposition carries out Gassian low-pass filter denoising, bright to obtain
Spend area image Y '；
4th module, for being sharpened processing to the infrared image G that the first module is obtained, to obtain final sharpening image
G’；
5th module, the final sharpening image obtained for the brightness area image Y ' for obtaining the 3rd module and the 4th module
G ' is merged, to generate new visible images Ynew；
6th module, color is carried out for the color gamut U component images to being obtained in the second module and color gamut V component image
Saturation degree adjustment is adjusted, to obtain final color domain U images UnewWith final color domain V image Vnew；
7th module, for the new visible images Y for obtaining the 5th modulenew, and the 6th module obtain it is final
Color gamut U images UnewWith final color domain V image VnewMerged, to obtain new YUV color space images YUVnew, and
To YUV color space images YUVnewYUV is carried out to the conversion of RGB color, to generate final visible images.
In general, by the contemplated above technical scheme of the present invention compared with prior art, it can obtain down and show
Beneficial effect：
1st, the present invention can solve the problem that denoising present in existing Visual image processing method can make visible images edge
The technical problem that fuzzy, details is deteriorated：As a result of following step (4) and step (5), it is sharpened to infrared image,
Strengthen edge and details, then merged with the Y-component in artwork YUV, therefore, it is possible to which solve can be by light image denoising back
Edge is obscured, the technical problem that details is deteriorated；
2nd, the present invention can solve the problem that in existing Visual image processing method using cause after infrared image enhancement image lack
The technical problem of weary texture color feature：As a result of following step (2) and step (5), (6), it will be seen that light is in yuv space
It is interior to be decomposed, adjustment enhancing operation has been carried out to color component U, V, the ash after the Y-component and edge sharpening that texture is more is allowed
Degree image is merged, and texture and color characteristic all very abundant results has been ultimately generated, therefore, it is possible to solve only to infrared figure
Lack the technical problem of texture color feature after image intensifying；
3rd, the present invention can solve the problem that in existing Visual image processing method causes enhancing effect not using common fusion
Good technical problem, as a result of step (3), (4), (6) so that fusion is no longer that two images are directly merged, and
Merging comprising the Y-component after denoising and the infrared image after sharpening, in addition color component U, V carry out color gamut enhancing operation,
It is not exposed to the brightness influence merged with infrared image, it is ensured that not only color characteristic is added the visible images after fusion
By force, and brightness and edge can strengthen, therefore, it is possible to solving to merge the not good technical problem of enhancing effect；
4th, the operation that the present invention is decomposed to visible images, merged, remerged, can enter to each component in parallel
Row processing, so as to ensure that the quickly and efficiently rate of processing procedure；
5th, the present invention employs most basic coefficient fusion method, fusion effect for visible ray Y-component and infrared fusion
It is really good, and ensure that real-time.
Brief description of the drawings
Fig. 1 is the flow chart of the processing method of visible images of the invention of taking photo by plane.
Fig. 2 shows the primary visible light image obtained in step of the present invention (1).
Fig. 3 shows the original infrared image obtained in step of the present invention (1).
Fig. 4 shows the YUV color space images obtained in step of the present invention (2).
Fig. 5 shows the brightness domain Y component map picture obtained in step of the present invention (2).
Fig. 6 shows the color gamut U component images obtained in step of the present invention (2).
Fig. 7 shows the color gamut V component image obtained in step of the present invention (2).
Fig. 8 shows the brightness area image obtained after the Gassian low-pass filter denoising of step of the present invention (3).
Fig. 9 shows the final sharpening image obtained in step of the present invention (4)；
Figure 10 shows the new visible images obtained in step of the present invention (5).
Figure 11 shows the final color domain U images that step of the present invention (6) is obtained.
Figure 12 shows the final color domain V image that step of the present invention (6) is obtained.
Figure 13 shows step of the present invention (7) by merging obtained new YUV color space images.
Figure 14 shows the final visible ray figure being converted to by YUV to RGB color in step of the present invention (7)
Picture.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.As long as in addition, technical characteristic involved in each embodiment of invention described below
Not constituting conflict each other can just be mutually combined.
As shown in figure 1, the present invention takes photo by plane, the processing method of visible images comprises the following steps：
(1) while obtaining visible images (as shown in Figure 2) respectively and red using visible light sensor and infrared sensor
Outer image G (as shown in Figure 3)；Specifically, it is seen that optical sensor and infrared sensor may be disposed at aircraft (such as nobody
Machine, satellite etc.) on；
(2) YUV color gamut conversions are carried out to the visible images that step (1) is obtained, to generate YUV color space images
(as shown in Figure 4), brightness domain Y component map picture (as shown in Figure 5), color gamut U component maps are decomposed into by the YUV color space images
As (as shown in Figure 6) and color gamut V component image (as shown in Figure 7)；
(3) Gassian low-pass filter denoising is carried out to the brightness domain Y component map picture that decomposition is obtained, to obtain brightness area image Y '
(as shown in Figure 8), wherein the standard deviation of the Gaussian function used is α, in the present invention, α is between 0.25 to 0.75, preferably to take
0.5；
(4) processing is sharpened to the infrared image G that step (1) is obtained, to obtain final sharpening image G ' (such as Fig. 9 institutes
Show)；This step includes following sub-step：
(4-1) is filtered processing using high-pass filter to infrared image G, to generate the image G after processinghpf；Specifically
For, the high-pass filter in the present invention can be single order or bivalent high-pass filter；
(4-2) obtains infrared image G mean μ and standard deviation sigma, and formula is as follows：
Wherein w represents infrared image G width, and h represents infrared image G height, and G (i, j) represents picture on infrared image G
The coordinate of vegetarian refreshments；
(4-3) obtains pixel G (i, j) correspondences on image G according to the mean μ and standard deviation sigma obtained in step (4-2)
High fdrequency component enhancing factor beta (i, j)：
The high fdrequency component enhancing coefficient that (4-4) is obtained according to step (4-3) and the image G that step (4-1) is obtainedhpfTo red
Outer image G carries out back add operation, to obtain initial sharpening image G "：
G " (x, y)=G (x, y)+β Ghpf(x,y)
(4-5) judge step (4-4) obtain initial sharpening image G " value be less than 0, or more than or equal to 0 and less than etc.
In 255,255 are also greater than, if less than 0, then final sharpening image G ' value 0 is set to, if greater than equal to 0 and being less than
Equal to 255, then final sharpening image G ' value is set to G " (x, y), if greater than 255, then by final sharpening image G's '
Value is set to 255.
(5) the final sharpening image G ' that the brightness area image Y ' and step (4) obtained step (3) is obtained is merged,
To generate new visible images Ynew(as shown in Figure 10), specifically using below equation：
Ynew(i, j)=γ (i, j) Y ' (i, j)+(1- γ (i, j)) G ' (i, j)
The middle operator γ of above formula can be tried to achieve by following formula
γ (i, j)=0.7* α+0.3* β (i, j)
(6) tone saturation degree tune is carried out to the color gamut U component images and color gamut V component image that are obtained in step (2)
It is whole, to obtain final color domain U images Unew(as shown in figure 11) and final color domain V image Vnew(as shown in figure 12)；This step
Suddenly following sub-step is specifically included：
(6-1) obtains average tone coefficient Coef according to color gamut U component images and color gamut V component image：
The tone that (6-2) obtains color gamut U component images and color gamut V component image respectively according to average tone coefficient is adjusted
Integral coefficient δuAnd δv：
Wherein τuEmpirical coefficient, τ are adjusted for the colourity of color gamut U componentsvFor the colourity adjustment experience system of color gamut V component
Number, in order that final tone will not adjust excessively violent, it is however generally that, τuAnd τvTake between 0.75~1.5, preferred value takes
1.25。
(6-3) obtains priming color domain U images U ' according to the hue adjustment coefficient obtained in step (6-2)newWith initial face
Colour gamut V image V 'new：
U′new(i, j)=(U(i,j)-128)*δu+128
V′new(i, j)=(V(i,j)-128)*δv+128
(6-4) judges obtained priming color domain U images U ' respectivelynewWith priming color domain V image V 'newValue be difference
Less than 0, or more than or equal to 0 and less than or equal to 255,255 are also greater than, if less than 0, then by final color domain U images
UnewWith final color domain V image VnewValue be set to 0, if more than or equal to 0 and less than or equal to 255, then by final color
Domain U images UnewWith final color domain V image VnewValue be respectively set to be equal to U 'newWith V 'new, if more than 255, then will
Final color domain U images UnewWith final color domain V image VnewValue be respectively set to 255.
(7) the new visible images Y for obtaining step (5)new, and the final color domain U images that step (6) is obtained
UnewWith final color domain V image VnewMerged, to obtain new YUV color space images YUVnew(as shown in figure 13), and
To YUV color space images YUVnewYUV is carried out to the conversion of RGB color, to generate final visible images (such as
Shown in Figure 14).
By the processing method of the present invention, and the final visible ray that will be obtained in Fig. 1 primary visible light image and Figure 14
Image is contrasted, it can clearly be seen that Figure 14 noise has obvious improvement, and color, details can be effectively retained, and
And the contour of object in picture is more apparent than Fig. 1 visible, embody it is of the invention effective make use of infrared image gamma characteristic and
The characteristics of back edge is clear is sharpened, original visible images can be kept by visible images are divided into each color component handling respectively
Color characteristics, after brightness domain component noise reduction with merging after IR Image Sharpening and can ensure that while denoising edge and
Details, has been finally reached good enhancing effect.
As it will be easily appreciated by one skilled in the art that the foregoing is only presently preferred embodiments of the present invention, it is not used to
The limitation present invention, any modification, equivalent and the improvement made within the spirit and principles of the invention etc., it all should include
Within protection scope of the present invention.
Claims (6)
1. a kind of processing method for visible images of taking photo by plane, it is characterised in that comprise the following steps：
(1) while obtaining visible images and infrared image G respectively using visible light sensor and infrared sensor；
(2) YUV color gamut conversions are carried out to the visible images that step (1) is obtained, to generate YUV color space images, by this
YUV color space images are decomposed into brightness domain Y component map picture, color gamut U component images and color gamut V component image；
(3) Gassian low-pass filter denoising is carried out to the brightness domain Y component map picture that decomposition is obtained, to obtain brightness area image Y '；
(4) processing is sharpened to the infrared image G that step (1) is obtained, to obtain final sharpening image G '；
(5) the final sharpening image G ' that the brightness area image Y ' and step (4) obtained step (3) is obtained is merged, with life
Cheng Xin visible images Ynew；
(6) tone saturation degree adjustment is carried out to the color gamut U component images and color gamut V component image that are obtained in step (2), with
Obtain final color domain U images UnewWith final color domain V image Vnew；
(7) the new visible images Y for obtaining step (5)new, and the final color domain U images U that step (6) is obtainednewWith
Final color domain V image VnewMerged, to obtain new YUV color space images YUVnew, and to the YUV color space figures
As YUVnewYUV is carried out to the conversion of RGB color, to generate final visible images.
2. processing method according to claim 1, it is characterised in that the mark of the Gaussian filter function used in step (3)
Accurate difference α is between 0.25 to 0.75.
3. processing method according to claim 1 or 2, it is characterised in that step (4) includes following sub-step：
(4-1) is filtered processing using high-pass filter to infrared image G, to generate the image G after processinghpf；
(4-2) obtains infrared image G mean μ and standard deviation sigma：
Wherein w represents infrared image G width, and h represents infrared image G height, and G (i, j) represents pixel on infrared image G
Coordinate；
(4-3) obtains the corresponding height of pixel G (i, j) on image G according to the mean μ and standard deviation sigma obtained in step (4-2)
Frequency component enhancing factor beta (i, j)：
The high fdrequency component enhancing coefficient that (4-4) is obtained according to step (4-3) and the image G that step (4-1) is obtainedhpfTo infrared figure
As G carries out back add operation, to obtain initial sharpening image G "：
G " (x, y)=G (x, y)+β Ghpf(x,y)
(4-5) judges that the value for the initial sharpening image G " that step (4-4) is obtained is less than 0, or more than or equal to 0 and is less than or equal to
255, be also greater than 255, if less than 0, then final sharpening image G ' value be set to 0, if greater than equal to 0 and less than etc.
In 255, then final sharpening image G ' value is set to G " (x, y), if greater than 255, then by final sharpening image G ' value
It is set to 255.
4. processing method as claimed in any of claims 1 to 3, it is characterised in that step (5) be specifically use with
Lower formula：
Ynew(i, j)=γ (i, j) Y ' (i, j)+(1- γ (i, j)) G ' (i, j)
The middle operator γ of wherein above formula can be tried to achieve by following formula
γ (i, j)=0.7* α+0.3* β (i, j).
5. processing method according to claim 4, it is characterised in that step (6) specifically includes following sub-step：
(6-1) obtains average tone coefficient Coef according to color gamut U component images and color gamut V component image：
(6-2) obtains the hue adjustment system of color gamut U component images and color gamut V component image according to average tone coefficient respectively
Number δuAnd δv：
Wherein τuEmpirical coefficient, τ are adjusted for the colourity of color gamut U componentsvEmpirical coefficient, τ are adjusted for the colourity of color gamut V componentu
And τvTake between 0.75~1.5.
(6-3) obtains priming color domain U images U ' according to the hue adjustment coefficient obtained in step (6-2)newWith priming color domain
V image V 'new：
U′new(i, j)=(U(i,j)-128)*δu+128
V′new(i, j)=(V(i,j)-128)*δv+128
(6-4) judges obtained priming color domain U images U ' respectivelynewWith priming color domain V image V 'newValue be to be respectively smaller than
0, or more than or equal to 0 and less than or equal to 255,255 are also greater than, if less than 0, then by final color domain U images UnewWith
Final color domain V image VnewValue be set to 0, if more than or equal to 0 and less than or equal to 255, then final color domain U is schemed
As UnewWith final color domain V image VnewValue be respectively set to be equal to U 'newWith V 'new, if more than 255, then will be final
Color gamut U images UnewWith final color domain V image VnewValue be respectively set to 255.
6. a kind of processing system for visible images of taking photo by plane, it is characterised in that including：
First module, for obtaining visible images and infrared image respectively using visible light sensor and infrared sensor simultaneously
G；
Second module, the visible images for being obtained to the first module carry out YUV color gamut conversions, empty to generate YUV colors
Between image, the YUV color space images are decomposed into brightness domain Y component map picture, color gamut U component images and color gamut V point
Spirogram picture；
3rd module, the brightness domain Y component map picture for being obtained to decomposition carries out Gassian low-pass filter denoising, to obtain brightness domain
Image Y '；
4th module, for being sharpened processing to the infrared image G that the first module is obtained, to obtain final sharpening image G '；
5th module, the final sharpening image G ' obtained for the brightness area image Y ' for obtaining the 3rd module and the 4th module enters
Row fusion, to generate new visible images Ynew；
6th module, carries out tone for the color gamut U component images to being obtained in the second module and color gamut V component image and satisfies
Adjusted with degree, to obtain final color domain U images UnewWith final color domain V image Vnew；
7th module, for the new visible images Y for obtaining the 5th modulenew, and the final color that the 6th module is obtained
Domain U images UnewWith final color domain V image VnewMerged, to obtain new YUV color space images YUVnew, and to this
YUV color space images YUVnewYUV is carried out to the conversion of RGB color, to generate final visible images.
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| CN113724164B (en) * | 2021-08-31 | 2024-05-14 | 南京邮电大学 | Visible light image noise removing method based on fusion reconstruction guidance filtering |
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