CN106558035B - Image processing method and system for exposure image - Google Patents
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Abstract
The present invention relates to the image processing methods and system for exposure image, and described method includes following steps: obtaining Initial R GB spatial image, the Initial R GB spatial image is respectively converted into XYZ space image and YCbCr space image；The second textural characteristics of luminance component in the first textural characteristics and YCbCr space image of luminance component in XYZ space image are extracted, and is superimposed and obtains the component that highlights；Transformation coefficient is obtained by the component that highlights, and is converted to obtain enhancing rgb space image according to transformation coefficient.Image processing method and system provided by the present invention for exposure image can be handled for the image of different depth of exposure, reduce computation complexity, be conducive to the detailed information of image after reservation exposure.
Description
Technical field
The present invention relates to technical field of image processing more particularly to a kind of image processing method for exposure image and it is
System.
Background technique
In image shoot process, since sunlight exposure intensity is excessive, occasion randomness is very big, is capturing some excellent winks
Between image when may because of do not have the sufficient time adjustment capture apparatus exposure, cause in shooting process, image mistake
The problems such as exposure or image exposure are insufficient, and then cause image information content low, and some important image informations are lost.It exposes at present
The processing method of light image is generally histogram transformation algorithm, i.e., by extracting the histogram of exposure image, carrying out histogram
The image after obtaining exposure-processed is exported after processing again.Though however, after exposure image is carried out histogram equalization by the above method
The image that gray level is abundant and dynamic range is big can be so obtained, but in histogram equalization process, this method is original in expansion
The visual effect for the image that can amplify the noise in original image while image gray levels, therefore obtain after handling is still inadequate
It is good；Algorithms different simultaneously is not also identical to the treatment effect of different degrees of exposure image, and therefore, it is necessary to for different degrees of
The exposure image picture processing finding suitable image processing algorithm to be exposed, cause to handle overlong time, algorithm is multiple
Miscellaneous degree is higher.
Summary of the invention
The embodiment of the present invention is designed to provide a kind of image processing method and system for exposure image, it is intended to solve
It certainly needs to be handled for different degrees of exposure image using different algorithms in the prior art, and causes to handle time mistake
Long, the higher problem of algorithm complexity.
The embodiment of the invention provides a kind of image processing methods for exposure image, and the method includes walking as follows
It is rapid:
Initial R GB spatial image is obtained, the Initial R GB spatial image is respectively converted into XYZ space image and YCbCr
Spatial image；
It extracts in the XYZ space image bright in the first textural characteristics of luminance component and the YCbCr space image
The second textural characteristics of component are spent, and is superimposed and obtains the component that highlights；
Transformation coefficient is obtained by the component that highlights, and converts to obtain treated rgb space image according to transformation coefficient.
The embodiment of the present invention provides a kind of image processing system for exposure image again, the system comprises:
The Initial R GB spatial image is respectively converted by image conversion unit for obtaining Initial R GB spatial image
XYZ space image and YCbCr space image；
Luminance component processing unit, for extract in the XYZ space image the first textural characteristics of luminance component and
Second textural characteristics of luminance component in the YCbCr space image, and be superimposed and obtain the component that highlights；
Image processing unit for obtaining transformation coefficient by the component that highlights, and converts everywhere according to transformation coefficient
Rgb space image after reason.
The embodiment of the present invention has the beneficial effect that: scheme provided in an embodiment of the present invention be for a width exposure image into
Row image procossing need to only obtain a width Initial R GB spatial image and be handled, be obtained without image detail information in order to obtain
It takes several exposure images to be handled, reduces the processing requirement to exposure image；In addition, this method is to different depth of exposure
The treatment effect of image be it is the same, Initial R GB spatial image only need to be converted into two kinds of color space images, i.e. XYZ space
Image and YCbCr space image, while two kinds of color space images are handled respectively, image detail information is just obtained, i.e.,
Highlight component, there is no need to find different processing methods for the images of different depth of exposure, reduce calculation amount and
Computation complexity, and be conducive to the detailed information of image after reservation exposure.
Detailed description of the invention
Fig. 1 is the flow chart of the image processing method provided in an embodiment of the present invention for exposure image；
Fig. 2 is Initial R GB spatial image provided in an embodiment of the present invention；
Fig. 3 is the XYZ space image after conversion provided in an embodiment of the present invention；
Fig. 4 is the YCbCr space image after conversion provided in an embodiment of the present invention；
Fig. 5 is the process of the first textural characteristics of luminance component in extraction XYZ space image provided in an embodiment of the present invention
Figure；
Fig. 6 is the image of the second luminance component provided in an embodiment of the present invention；
Fig. 7 is the 3-D image of the first textural characteristics provided in an embodiment of the present invention；
Fig. 8 is the stream of the second textural characteristics of luminance component in extraction YCbCr space image provided in an embodiment of the present invention
Cheng Tu；
Fig. 9 is the three-dimensional figure of the second textural characteristics of luminance component in YCbCr space image provided in an embodiment of the present invention
Picture；
Figure 10 is the image of the superimposed component that highlights provided in an embodiment of the present invention；
Figure 11 is the 3-D image of the superimposed component that highlights provided in an embodiment of the present invention；
Figure 12 obtains the flow chart of transformation coefficient by the component that highlights to be provided in an embodiment of the present invention；
Figure 13 is treated rgb space image provided in an embodiment of the present invention；
Figure 14 is the schematic diagram of the image processing system provided in an embodiment of the present invention for exposure image；
Figure 15 is that the luminance component in the image processing system provided in an embodiment of the present invention for exposure image handles list
The schematic diagram of member；
Figure 16 is the image processing unit in the image processing system provided in an embodiment of the present invention for exposure image
Schematic diagram.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
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.
Image processing method and system provided in an embodiment of the present invention for exposure image, by Initial R GB spatial image
It is converted into two different color space images, i.e. XYZ space image and YCbCr space image respectively, and to both colors
Spatial image carries out different processing, synthesizes the component that highlights, and finally distinguishes the three-component image in Initial R GB image
Brightness adjustment is carried out, enhanced rgb space image is finally exported.Image procossing provided in this embodiment for exposure image
Method and system can effectively extract the detailed information of image, and identical to the Processing Algorithm of different degrees of exposure image,
The processing time of algorithm is saved, computation complexity is greatly reduced.
Fig. 1 shows the flow chart of the image processing method provided in an embodiment of the present invention for exposure image, in order to just
In description, only parts related to embodiments of the present invention are shown, as shown in Figure 1, provided in an embodiment of the present invention for exposing
The image processing method of image includes the following steps:
Step S1, obtain Initial R GB spatial image, by Initial R GB spatial image be respectively converted into XYZ space image and
YCbCr space image.
In the present embodiment, the principle of computer color display display color is all to use as colour television set
The principle of red (R), green (G), blue (B) additive color mixture, colour television set is the electron beam by launching three kinds of varying strengths, is made
The red, green, blue phosphor material covered on the inside of screen shines and generates color, and the representation method of this color is known as RGB color
Space representation, it includes R, G, B be pixel three channel components.Read needed for handle initial pictures, acquisition it is initial
Image is rgb space image, this initial pictures is exposure image (such as image of overexposure or under-exposure).Fig. 2 is the present invention
The Initial R GB spatial image that embodiment provides, as shown in Fig. 2, the image is the image of overexposure, it can be seen from the figure that
Due to overexposure, many image detail informations of missing image.
Generally, the type of rgb space image can be uint8, uint16 or double class, due to exposure image
It can be related to the calculating of decimal point in treatment process, in order to facilitate the calculating of image data, preservation and reduce calculating error, sentence
The type of disconnected Initial R GB spatial image is converted into if Initial R GB spatial image is uint8 or uint16 types of image
Double type.
In the present embodiment, Fig. 3 is the XYZ space image after conversion provided in an embodiment of the present invention, as shown in figure 3, turning
Compared with the Initial R GB spatial image in Fig. 2, the overall gray value of XYZ space image becomes smaller XYZ space image after changing, and
Wherein contain more image detail informations.XYZ space image is to use three imaginary primary colors X, Y, Z instead to establish a color
Degree system.Initial R GB spatial image is converted into XYZ space image, specifically: Initial R GB spatial image removal gamma is calculated
Son is converted to XYZ space image.Specifically, if the rgb space image for being converted to double type is I, then gamma calculation is removed
The XYZ space image that son obtains is, wherein γ is gamma operator, and the value of gamma operator is according to many experiments
Data show that the value of γ is 2.2 in the present embodiment, and after removal gamma operator operation, the overall gray value of image becomes
It is small.
In the present embodiment, Fig. 4 is the YCbCr space image after conversion provided in an embodiment of the present invention, as shown in figure 4,
YCbCr space image is one kind of color space image, and Y refers to that luminance component, Cb refer to chroma blue point in YCbCr space image
Amount, Cr refer to red chrominance component.The algorithm that rgb space image is converted to YCbCr space image is as follows:
Y = 0.257*R+0.564*G+0.098*B+16；
Cb=-0.148*R-0.291*G+0.439*B+128；
Cr= 0.439*R-0.368*G-0.071*B+128。
Step S2 extracts the first textural characteristics of luminance component and the YCbCr space figure in the XYZ space image
The second textural characteristics of luminance component as in, and be superimposed and obtain the component that highlights.
In the present embodiment, Fig. 5 is the first line of luminance component in extraction XYZ space image provided in an embodiment of the present invention
The flow chart of feature is managed, as shown in figure 5, the step of extracting the first textural characteristics of luminance component in XYZ space image:
Step S211 extracts the first luminance component in XYZ space image.
Step S212 carries out bilateral filtering processing to the first luminance component, obtains the second brightness point in XYZ space image
Amount.
Step S213 determines brightness point in XYZ space image according to the ratio of the first luminance component and the second luminance component
First textural characteristics of amount.
Specifically, the first luminance component L_L in XYZ space image is extracted；And the first luminance component L_L is carried out bilateral
Filtering processing, obtains the second luminance component L_S_I in XYZ space image.Fig. 6 is the second brightness provided in an embodiment of the present invention
The image of component, as shown in fig. 6, carrying out the figure of the second luminance component obtained by bilateral filtering is handled to the first luminance component L_L
Picture has lacked more image detail informations compared with the Initial R GB spatial image in Fig. 2.
Further, according to the ratio of the first luminance component L_L and the second luminance component L_S_I in XYZ space image,
Determine the first textural characteristics H of luminance component in XYZ space image, the calculating formula of textural characteristics H is.Fig. 7 is this
The 3-D image for the first textural characteristics that inventive embodiments provide, as shown in fig. 7, can be seen that image from its 3-D image
Texture information.
In the present embodiment, Fig. 8 is second of luminance component in extraction YCbCr space image provided in an embodiment of the present invention
The flow chart of textural characteristics, as shown in figure 8, the step of extracting the second textural characteristics of luminance component in YCbCr space image has
Body are as follows:
Step S221 extracts the third luminance component in YCbCr space image；
Step S222 carries out logarithmic transformation to third luminance component, obtains second of luminance component in YCbCr space image
Textural characteristics.
Specifically, Fig. 9 is the second textural characteristics of luminance component in YCbCr space image provided in an embodiment of the present invention
3-D image carries out third luminance component L_Y as shown in figure 9, extracting the third luminance component L_Y in YCbCr space image
Logarithmic transformation obtains the second textural characteristics of luminance component in YCbCr space image, brightness point in YCbCr space image
The calculating formula of second textural characteristics L_X of amount are as follows:。
Specifically, superposition obtains the component that highlights, specifically: by the first texture of luminance component in XYZ space image
The second textural characteristics of feature H and luminance component in YCbCr space imageSummation process is carried out, obtains highlighting point
Amount.Figure 10 is the image of the superimposed component that highlights provided in an embodiment of the present invention, Figure 11
For the 3-D image of the superimposed component that highlights provided in an embodiment of the present invention, as shown in figs. 10-11, by by XYZ sky
Between in image the second textural characteristics of the first textural characteristics and luminance component in YCbCr space image of luminance component asked
After processing, the available more detailed image of textural characteristics, more such as the texture information in texture information ratio Fig. 7 in Figure 11
Add in detail.
Step S3 obtains transformation coefficient by the component that highlights, and according to transformation coefficient converts to obtain that treated that RGB is empty
Between image.
In the present embodiment, Figure 12 obtains the process of transformation coefficient by the component that highlights to be provided in an embodiment of the present invention
Figure, as shown in figure 12, the step of transformation coefficient is obtained by the component that highlights specifically:
Step S31 extracts the first luminance component in XYZ space image；
Step S32 obtains transformation coefficient according to the ratio of highlight component and first luminance component.
Specifically, the first luminance component in XYZ space image is extracted；According to the component that highlightsWith
One luminance componentRatio, obtaining transformation coefficient is。
In the present embodiment, convert to obtain treated rgb space image according to transformation coefficient, specifically: by Initial R GB
Three channel components of spatial image are respectively multiplied by transformation coefficient；It will synthesize multiplied by the three of transformation coefficient channel components to obtain
Treated rgb space image.Figure 13 is treated rgb space image provided in an embodiment of the present invention, as shown in figure 13, with
Initial R GB spatial image compares in Fig. 2, and the part exposed in Fig. 2 has been weakened, while the texture information of image is more clear
It is clear, clear.
Specifically, by tri- channel components of R, G, B of rgb space imageRespectively multiplied by the transformation coefficient of luminance component, i.e.,, whereinRespectively indicate R, G, B component；It is finally synthesizing to obtain
Treated rgb space image。
Further, if Initial R GB spatial image is uint8 or uint16 types of image, double class will be finally synthesizing
Treated that rgb space image is converted to uint8 or uint16 types of image for type.
Figure 14 is the schematic diagram of the image processing system provided in an embodiment of the present invention for exposure image, for the ease of retouching
It states, only parts related to embodiments of the present invention are shown, as shown in figure 14, provided in an embodiment of the present invention to be used for exposure image
Image processing system include: image conversion unit 51, luminance component processing unit 52 and image processing unit 53.
Specifically, image conversion unit 51 is for obtaining Initial R GB spatial image, by the Initial R GB spatial image point
XYZ space image and YCbCr space image are not converted to；Luminance component processing unit 52 is for extracting the XYZ space image
Second textural characteristics of luminance component in first textural characteristics of middle luminance component and the YCbCr space image, and be superimposed
Obtain the component that highlights；Image processing unit 53 is used to obtain transformation coefficient by the component that highlights, and according to transformation coefficient
Transformation obtains that treated rgb space image.
In the present embodiment, Figure 15 is bright in the image processing system provided in an embodiment of the present invention for exposure image
The schematic diagram of component processing unit is spent, as shown in figure 15, luminance component processing unit 52 includes the first extraction unit 521, second
Extraction unit 522 and superpositing unit 523.
Specifically, the first extraction unit 521 is used to extract the first luminance component in XYZ space image；By the first brightness
Component carries out bilateral filtering processing, obtains the second luminance component in XYZ space image；It is bright according to the first luminance component and second
The ratio for spending component, determines the first textural characteristics of the luminance component in XYZ space image.Second extraction unit 522 is for mentioning
Take the third luminance component in YCbCr space image；Third luminance component is subjected to logarithmic transformation, obtains YCbCr space image
Second textural characteristics of middle luminance component.Superpositing unit 523 is used for the first textural characteristics of luminance component in XYZ space image
Summation process is carried out with the second textural characteristics of luminance component in YCbCr space image, obtains the component that highlights.
In the present embodiment, Figure 16 is the figure in the image processing system provided in an embodiment of the present invention for exposure image
As the schematic diagram of processing unit, as shown in figure 16, image processing unit 53 includes: that transformation coefficient calculates unit 531 and synthesis
Unit 532.
Specifically, transformation coefficient calculates unit 531 and is used to extract the first luminance component in XYZ space image；According to increasing
The ratio of strong luminance component and first luminance component, obtains transformation coefficient.Synthesis unit 532 is used for the space Initial R GB
Three channel components of image are respectively multiplied by transformation coefficient；It will synthesize multiplied by the three of transformation coefficient channel components to be handled
Rgb space image afterwards.
The above content is a further detailed description of the present invention in conjunction with specific preferred embodiments, and it cannot be said that
Specific implementation of the invention is only limited to these instructions.For those of ordinary skill in the art to which the present invention belongs, exist
Several equivalent substitute or obvious modifications are made under the premise of not departing from present inventive concept, and performance or use is identical, all should
It is considered as belonging to present invention scope of patent protection determined by the appended claims.
Claims (7)
1. a kind of image processing method for exposure image, which is characterized in that described method includes following steps:
Initial R GB spatial image is obtained, the Initial R GB spatial image is respectively converted into XYZ space image and YCbCr space
Image；
Extract the first luminance component in XYZ space image；
First luminance component is subjected to bilateral filtering processing, obtains the second luminance component in XYZ space image；
According to the ratio of first luminance component and second luminance component, luminance component in XYZ space image is determined
First textural characteristics；
Extract the third luminance component in YCbCr space image；
The third luminance component is subjected to logarithmic transformation, obtains the second textural characteristics of luminance component in YCbCr space image；
First textural characteristics and second textural characteristics are superimposed to obtain the component that highlights；
Transformation coefficient is obtained by the component that highlights, and converts to obtain treated rgb space image according to transformation coefficient.
2. being used for the image processing method of exposure image as described in claim 1, which is characterized in that described by the space Initial R GB
Image is converted to XYZ space image specifically:
Initial R GB spatial image is removed into gamma operator, is converted to XYZ space image.
3. being used for the image processing method of exposure image as described in claim 1, which is characterized in that the superposition obtains enhancing bright
Spend component specifically:
By the second texture of luminance component in the first textural characteristics of luminance component in XYZ space image and YCbCr space image
Feature carries out summation process, obtains the component that highlights.
4. being used for the image processing method of exposure image as described in claim 1, which is characterized in that described by the component that highlights
Obtain transformation coefficient specifically:
Extract the first luminance component in XYZ space image；
According to the ratio of highlight component and first luminance component, transformation coefficient is obtained.
5. being used for the image processing method of exposure image as described in claim 1, which is characterized in that described to be become according to transformation coefficient
Getting treated in return, rgb space image specifically includes:
By three channel components of Initial R GB spatial image respectively multiplied by transformation coefficient；
By multiplied by three channel components synthesis after transformation coefficient with the rgb space image that obtains that treated.
6. a kind of image processing system for exposure image, which is characterized in that the system comprises:
The Initial R GB spatial image is respectively converted into XYZ sky for obtaining Initial R GB spatial image by image conversion unit
Between image and YCbCr space image；
Luminance component processing unit, for extracting in the XYZ space image the first textural characteristics of luminance component and described
Second textural characteristics of luminance component in YCbCr space image, and be superimposed and obtain the component that highlights；
Image processing unit for obtaining transformation coefficient by the component that highlights, and converts after obtaining processing according to transformation coefficient
Rgb space image；
The luminance component processing unit includes the first extraction unit, the second extraction unit and superpositing unit,
First extraction unit, for extract the first luminance component in XYZ space image, by first luminance component into
The processing of row bilateral filtering, obtains the second luminance component in XYZ space image, according to first luminance component and described second
The ratio of luminance component determines the first textural characteristics of luminance component in XYZ space image；
Second extraction unit, for extracting the third luminance component in YCbCr space image, by the third luminance component
Logarithmic transformation is carried out, the second textural characteristics of luminance component in YCbCr space image are obtained；
The superpositing unit, for by the first textural characteristics of luminance component in XYZ space image with it is bright in YCbCr space image
The second textural characteristics for spending component carry out summation process, obtain the component that highlights.
7. being used for the image processing system of exposure image as claimed in claim 6, which is characterized in that described image processing unit packet
Include: transformation coefficient calculates unit and synthesis unit,
The transformation coefficient calculates unit, for extracting the first luminance component in XYZ space image, according to the component that highlights
With the ratio of first luminance component, transformation coefficient is obtained；
The synthesis unit, for by three channel components of Initial R GB spatial image respectively multiplied by transformation coefficient, will be multiplied by change
Three channel components synthesis of coefficient is changed with the rgb space image that obtains that treated.
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| CN1578475A (en) * | 2003-07-18 | 2005-02-09 | 佳能株式会社 | Image processing method and apparatus for correcting image brightness distribution |
| CN1591172A (en) * | 2003-07-31 | 2005-03-09 | 佳能株式会社 | Image processing method and apparatus |
| CN1988629A (en) * | 2006-12-28 | 2007-06-27 | 上海广电（集团）有限公司中央研究院 | Method for improving image articulation |
| CN105243641A (en) * | 2015-08-18 | 2016-01-13 | 西安电子科技大学 | Low illumination image enhancement method based on dual-tree complex wavelet transform |
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| CN1578475A (en) * | 2003-07-18 | 2005-02-09 | 佳能株式会社 | Image processing method and apparatus for correcting image brightness distribution |
| CN1591172A (en) * | 2003-07-31 | 2005-03-09 | 佳能株式会社 | Image processing method and apparatus |
| CN1988629A (en) * | 2006-12-28 | 2007-06-27 | 上海广电（集团）有限公司中央研究院 | Method for improving image articulation |
| CN105243641A (en) * | 2015-08-18 | 2016-01-13 | 西安电子科技大学 | Low illumination image enhancement method based on dual-tree complex wavelet transform |
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