CN105118027B - A kind of defogging method of image - Google Patents
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Abstract
The invention discloses a kind of defogging method of image, applied to the image comprising fog, methods described includes：The dark of described image is obtained by the Color Channel of described image；The transmissivity of air light intensity and described image is obtained by the dark；The Color Channel is modified according to the transmissivity and obtains correcting Color Channel；Amendment air light intensity is obtained by the amendment Color Channel and transmissivity is corrected；Mist elimination image is obtained according to the amendment Color Channel, amendment air light intensity and amendment transmissivity.The present invention is modified to the Color Channel of image, air light intensity and transmissivity, can eliminate the fog of image, the problems such as eliminating blocky effect to greatest extent according to the characteristics of image itself.
Description
Technical Field
The invention belongs to the technical field of image processing, and particularly relates to a defogging method for an image.
Background
As an important means of safety protection, video monitoring plays an extremely important role. However, the video surveillance system is greatly affected by environmental factors when acquiring images. For example, under the haze condition, the quality of an image captured by the optical sensor is seriously reduced, the image contrast is low, the detail loss is serious, and great difficulty is brought to subsequent image processing and analysis work, so that the research on the efficient and feasible defogging algorithm has very important theoretical and research values.
The researches of domestic and foreign scholars on the defogging method mainly include two types: defogging algorithm based on atmospheric light scattering model and defogging algorithm based on image enhancement technology. The defogging algorithm based on the atmospheric light scattering model mainly comprises the following steps: a defogging algorithm, a fuzzy defogging algorithm and the like based on dark channel prior; the defogging algorithm based on the image enhancement technology comprises the following steps: defogging algorithm based on Retinex image enhancement technology, defogging algorithm based on pixel color diversity and the like. Among these algorithms in existence, the defogging algorithm based on dark channel prior is recognized as the most effective and most common one. The algorithm is used for constructing a defogging model based on dark channel prior information, wherein the prior considers that the pixel value of at least one color channel in three color channels in a local area of an image is lower or close to zero, and the color channel is defined as a dark channel. By defining the dark channel, the fog component in the foggy image can be estimated, thereby achieving the purpose of recovering the original image from the foggy image, and the flow chart of the method is shown in fig. 1. The defogged image obtained by the existing method has a large-area image with a light color or white area, and the value of a dark channel is usually higher, so that the image to be processed does not completely meet the prior theory of the dark channel, and the obtained defogged image has the problems of blocky effect and the like.
Disclosure of Invention
In view of the above, it is desirable to provide a method for defogging an image, which can at least solve the technical problems of the prior defogging method, such as the blockiness.
The technical scheme of the embodiment of the invention is realized as follows:
the embodiment of the invention provides an image defogging method, which is applied to an image containing fog, and comprises the following steps:
obtaining a dark channel of the image through a color channel of the image;
obtaining atmospheric light intensity and transmittance of the image through the dark channel;
correcting the color channel according to the transmissivity to obtain a corrected color channel;
obtaining corrected atmospheric light intensity and corrected transmittance through the corrected color channel;
and obtaining a defogged image according to the corrected color channel, the corrected atmospheric light intensity and the corrected transmissivity.
In the foregoing solution, obtaining the dark channel of the image through the color channel of the image includes:
carrying out channel decomposition on the image to obtain each color channel of the image;
dividing the image into set image blocks, and setting the color channel with the minimum gray value corresponding to the image blocks as the dark channel of the image blocks.
In the above scheme, the process of obtaining the atmospheric light intensity is as follows:
acquiring a pixel point set with highest brightness in the dark channel;
selecting pixel points with set proportion from the pixel point set as reference pixel points;
calculating the gray value of the pixel point corresponding to the reference pixel point in the image;
the median of the grey values was set as the atmospheric light intensity.
In the foregoing solution, the correcting the color channel according to the transmittance to obtain a corrected color channel includes:
normalizing the transmittance on the dark channel of the image block to obtain a normalized transmittance;
calculating the weight of the color channel on the dark channel of the image block in the color channel corresponding to the image;
and calculating a corrected color channel through the normalized transmissivity and the weight.
In the above scheme, the obtaining a defogged image according to the corrected color channel, the corrected atmospheric light intensity, and the corrected transmittance includes:
obtaining a defogging color channel of the image through the correction color channel, the correction atmospheric light intensity and the correction transmissivity;
and weighting the defogging color channels to obtain a defogged image corresponding to the image.
In the above scheme, the calculation process of the dark channel of the image block is as follows:
wherein, Jdark(y) is the dark channel of the image block and is expressed by a matrix, r, g and b respectively represent red, green and blue, c is one of the three colors of r, g and b, y is a set formed by local small areas taking the space coordinate x of the image as the center, omega is a set symbol and is expressed as y ∈ omega (x), JcAnd (y) is any one of the local area color channels of the image block.
In the above scheme, the calculation process of the transmittance is as follows:
wherein t (y) is the transmittance; i isc(y) is a color channel corresponding to color c; a. thecIs a color channel Ic(y) corresponding atmospheric light intensity.
In the above scheme, the calculation process of correcting the color channel is as follows:
wherein, Ic' (y) is a modified color channel, represented by a matrix; t isck(y) is the normalized transmission; gck(y) is a weight; i isck(y) color channel I of the foggy image in image block kcThe value on (y).
In the above scheme, the calculation process of the defogging color channel is as follows:
wherein,the color channels of the defogged image are represented by a matrix; i isc' (y) is the corrected color channel;to correct the atmospheric light intensity;to correct the transmittance.
In the above scheme, the calculation process of the defogged image is as follows:
wherein J (y) is a defogged image and is represented by a matrix; n is a weight value, and the value of n is the same as the number of color channels.
The image defogging method provided by the embodiment of the invention corrects the color channel, the atmospheric light intensity and the transmissivity of the image, can remove the fog of the image to the maximum extent according to the characteristics of the image, and solves the problems of block effect and the like.
Drawings
FIG. 1 is a flow chart of a prior art defogging method;
FIG. 2 is a flowchart of a defogging method for an image according to embodiment 1;
FIG. 3 is a graph comparing the defogging effects of the images of example 2.
To clearly illustrate the structure of embodiments of the present invention, certain dimensions, structures and devices are shown in the drawings, which are for illustrative purposes only and are not intended to limit the invention to the particular dimensions, structures, devices and environments, which may be adjusted or modified by one of ordinary skill in the art according to particular needs and are still included in the scope of the appended claims.
Detailed Description
In the following description, various aspects of the invention will be described, however, it will be apparent to those skilled in the art that the invention may be practiced with only some or all of the structures or processes of the present invention. Specific numbers, configurations and sequences are set forth in order to provide clarity of explanation, but it will be apparent that the invention may be practiced without these specific details. In other instances, well-known features have not been set forth in detail in order not to obscure the invention.
Example 1
In order to solve the technical problems of the block effect and the like of the existing defogging method, an embodiment of the invention provides a defogging method for an image, which is applied to the image containing fog, and as shown in fig. 2, the method comprises the following steps:
step S101: obtaining a dark channel of the image through a color channel of the image;
the image described in this embodiment refers to an image containing fog obtained by a digital imaging device (such as a mobile phone, a video camera, a digital camera, etc.), and the image is also referred to as a color cast image. The color cast image has low contrast and serious detail loss, and simultaneously generates fogging condition, thereby bringing great difficulty to subsequent image processing and analysis work.
In the embodiment, the image is subjected to a channel decomposition method to obtain the pixel value of each pixel point of the image on an RGB (Red-Red, Green-Green, Blue-Blue) channel, and the pixel value is expressed in a matrix form, namely a color channel; and obtaining a dark channel according to the color channel.
Step S102: obtaining atmospheric light intensity and transmittance of the image through the dark channel;
and obtaining the atmospheric light intensity of the image and the transmissivity of the image based on the dark channel, so that the atmospheric light intensity and the transmissivity are more consistent with the current image.
Step S103: correcting the color channel according to the transmissivity to obtain a corrected color channel;
generally, images have different depths of field, and the transmittance of images is different according to different depths of field; therefore, the fog can be removed with respect to the depth of field characteristic of the current image itself by correcting the color channel according to the transmittance.
Step S104: obtaining corrected atmospheric light intensity and corrected transmittance through the corrected color channel;
and after the corrected color channel is obtained, correcting the atmospheric light intensity and the transmittance again to further meet the defogging requirement of the current image.
Step S105: and obtaining a defogged image according to the corrected color channel, the corrected atmospheric light intensity and the corrected transmissivity.
The corrected color channel, the corrected atmospheric light intensity and the corrected transmittance are applied to the image at the beginning of the implementation, and then the corresponding defogged image is obtained.
The method corrects the color channel, the atmospheric light intensity and the transmissivity of the image, can remove the fog of the image to the maximum extent according to the characteristics of the image, and solves the problems of block effect and the like.
Specifically, step S101 includes:
step S1011: carrying out channel decomposition on the image to obtain a color channel;
and carrying out channel decomposition on the image through three RGB channels to respectively obtain a red channel, a green channel and a blue channel.
Step S1012: dividing the image into set image blocks, and setting the color channel with the minimum gray value corresponding to the image blocks as a dark channel of the image blocks.
The depth of field is different for different images. Dividing the image into set image blocks according to the characteristics of the image; and then, independently solving a dark channel block for each image block, and combining the dark channels of all the image blocks into a dark channel image corresponding to the image.
The calculation process of the dark channel of the image block is as follows:
wherein, Jdark(y) is the dark channel of the image block and is expressed by a matrix, r, g and b respectively represent red, green and blue, c is one of the three colors of r, g and b, y is a set formed by local small areas taking the space coordinate x of the image as the center, omega is a set symbol and is expressed as y ∈ omega (x), JcAnd (y) is any one of the local area color channels of the image block.
The process of obtaining the atmospheric light intensity in step S102 is as follows:
step S1021: acquiring a pixel point set with highest brightness in the dark channel;
step S1022: selecting pixel points with set proportion from the pixel point set as reference pixel points;
step S1023: calculating the gray value of the pixel point corresponding to the reference pixel point in the image;
step S1024: the median of the grey values was set as the atmospheric light intensity.
Further, the calculation process of the transmittance in step S102 is:
wherein t (y) is the transmittance; i isc(y) is a color channel corresponding to color c; a. thecIs a color channel Ic(y) corresponding atmospheric light intensity.
The step S103 specifically includes:
step S1031: normalizing the transmittance on the dark channel of the image block to obtain a normalized transmittance;
step S1032: calculating the weight of the color channel on the dark channel of the image block on the image;
step S1033: and calculating a corrected color channel through the normalized transmissivity and the weight. The calculation process of the corrected color channel is as follows:
wherein, Ic' (y) is a corrected color channel, represented by a matrix; t isck(y) is the normalized transmission; gck(y) is a weight; i isck(y) color channel I of the foggy image in image block kcA value on (y);
the step S105 specifically includes:
step S1051: obtaining a defogging color channel of the image through the correction color channel, the correction atmospheric light intensity and the correction transmissivity; the calculation process of the defogging color channel is as follows:
wherein,the color channels of the defogged image are represented by a matrix; i isc' (y) is the corrected color channel;to correct the atmospheric light intensity;to correct the transmittance.
Step S1052: and weighting the defogging color channels to obtain a defogged image corresponding to the image. The calculation process of the defogged image is as follows:
wherein J (y) is a defogged image and is represented by a matrix; n is a weight value, and the value of n is the same as the number of color channels.
The method of the embodiment expresses the color channels of the image blocks of the image by using the weight, simultaneously endows the color channels of different image blocks with different weight values, combines the transmittance optimization cost function in the original dark channel-based preoperative algorithm, is suitable for the image with large-area light color or white area, and can remarkably improve the problems of 'halo' and block effect of the processed image.
Example 2
The present embodiment describes the present invention in detail according to an actual scenario.
The method of the embodiment comprises the following steps:
(1) obtaining color channels of an image
Inputting the foggy image acquired by digital imaging equipment such as a digital camera, a mobile phone camera and the like into a computer, and expressing the image in an RGB color space;
the color cast image is obtained by a digital imaging device (such as a digital camera, a mobile phone camera, etc.). Under the haze condition, the quality of an image captured by an optical sensor of the digital imaging equipment is seriously reduced, the contrast of the image is low, the loss of details is serious, and a fogging image is generated, so that great difficulty is brought to subsequent image processing and analysis work. Reading the atomized image into a computer, and obtaining the pixel values of each pixel point of the image in R, G, B three channels through channel decomposition, thereby obtaining the data information of the image, wherein the data information is the basis for defogging and the formula is as follows:
wherein, I (x) is an image to be defogged and is expressed by a matrix; i isr(x) Is the red color channel of the image; i isg(x) Is the green color channel of the image; i isb(x) Is the blue color channel of the image. For convenience of presentation, use Ic(x) Is represented byr(x)、Ig(x) And Ib(x) Any one color channel of.
(2) Computing dark channels of an image
The method comprises the following steps:
a, dividing an image into image blocks, wherein the number of the specific image blocks is set according to an actual image;
b, calculating a dark channel of each image block, wherein a dark channel solving formula is as follows:
wherein, Jc(y) is the color channel of the fog-free image, where the formula is used to solve the dark channel of the fog-free image, and the formula is transformed into:
wherein, Idark(y) a dark channel where fog suddenly attacks; i isc(y) is a foggy image.
(3) Estimating atmospheric light intensity
In general, the atmospheric light intensity selects the pixel with the highest fog concentration and the highest brightness in the image. And selecting the point with the highest pixel in the dark channel, and then averaging the pixels of the points in the foggy image to obtain the atmospheric light intensity. In this embodiment, first, 0.1% of the pixels of the brightest pixels are selected from the dark channels, and then the maximum gray value among the gray values of these pixels in the original input image is selected as the atmospheric light intensity value (on this basis).
(4) Calculating the transmittance
Assuming that the total atmospheric light intensity of each image block in the foggy image is the same and known, assuming that the transmittance is constant in each image block, and the transmittance is calculated by rough estimation, the foggy atmosphere illumination model is as follows:
I(x)＝J(x)t(x)+A(1-t(x))
wherein, I (x) is a foggy image and is represented by a matrix; j (x) is I (x) the image after defogging, and is expressed by a matrix; t (x) is the transmittance; a is the atmospheric light intensity; x is the spatial coordinate of the image.
Since the defogging process is performed in each of the regions R, G, B, the local regions of the three color channels are respectively, the above formula can be expressed as:
Ic(y)＝Jc(y)t(y)+Ac(1-t(y))
since y is a set of local small regions centered on the spatial coordinate x of the image, and correspondingly, t (y) is a projection rate representing the local region, it is similarly generalized to Jc(y) and Ic(y)。
Using minimal filtering on the above equation, one can obtain:
the above formula is divided by AcComprises the following steps:
the minimum is taken over the three color channels:
as can be seen from the above, the present invention,and the atmospheric light intensity AcThe actual value of (a) is very large, then:
further, the transmittance was obtained:
(5) correcting color channels
a, calculating the normalized transmittance of the image block:
wherein, Tck(y) color channel I for image block kc(y) normalized transmittance; t is tck(y) color channel I for image block kc(y) transmittance; u (y) is the color channel I of image block kc(y) the average value of the transmittance of (y),s (y) is the color channel I of image block kc(y) the standard deviation of the transmittance,ωkis the total number of image blocks k; and omega is the omega-th image block.
b, calculating the weight of the color channel of the image block in the corresponding color channel of the image:
wherein, ω iscAs a colour channel I of the imagec(y) the number of pixels; i isck(y) is the color channel I of the image in image block kcA value on (y); gck(y) is the image in image block IcWeight on (y).
c, correcting color channels:
wherein, Ick(y) is the color channel I of the image in image block kcValue on (y)
(6) Correcting atmospheric light intensity and transmissivity
The corrected color channel obtained in the step (5) is substituted into the steps (2) to (4), and the atmospheric light intensity and the transmissivity are corrected to obtain the corrected atmospheric light intensityAnd correcting the transmittance(when the difference of the transmittance values after two adjacent times of optimization is less than 0.15, the optimization process is stopped, and when the difference of the transmittance strength values after two adjacent times of optimization is less than 0.15, the optimization process is stopped).
(7) Outputting a defogged image
a, calculating defogging color channels
According to Ic(y)＝Jc(y)t(y)+Ac(1-t (y)) can be obtainedThen the corresponding defogging color channelComprises the following steps:
wherein,is the color channel of the defogged image.
b, calculating a defogged image
The effect diagram of processing an image by the existing method and the method of the present embodiment is shown in fig. 3. Wherein, FIG. 3a is an original image; FIG. 3b is a defogged image processed by a conventional method; fig. 3c is the defogged image processed by the method of the embodiment. As is apparent from fig. 3, the image after defogging by the method of the present embodiment has higher definition than that of the prior art.
The method adopts a color channel weighting method to carry out defogging treatment on the atomized image, fully utilizes data information contained in the image on the basis of dark channel prior, deeply discovers the correlation among pixel values of each color channel of the image and considers the influence of a local area color channel weight value on a defogging result. The image subjected to defogging by the method is more in line with the visual perception of human eyes and has a better defogging effect; the correction weight is constructed by calculating the transmissivity of the area (image block) and the weight values of the color channels in different areas, so that the correction of the dark channel value is realized, the application range of the algorithm is improved, and the algorithm still has higher accuracy even if light color or white areas exist in the image; by adopting a color channel weighted output mode, the blocky effect and the halo phenomenon in the processed image are obviously improved, and the depth information of different scenes can be embodied; the method has the advantages of relatively simple calculation formula and algorithm flow, small time complexity, high execution speed and high efficiency, and can meet the real-time requirement. The method can be used for accurately and efficiently defogging images shot by digital imaging equipment such as a digital camera, a mobile phone camera and the like, and has wide application value and market prospect.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may be separately used as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media capable of storing program codes, such as a removable Memory device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, and an optical disk.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (9)
1. A method for defogging an image, the method being applied to an image containing fog, the method comprising:
obtaining a dark channel of the image through a color channel of the image;
obtaining atmospheric light intensity and transmittance of the image through the dark channel;
correcting the color channel according to the transmissivity to obtain a corrected color channel; the method specifically comprises the following steps: normalizing the transmittance on the dark channel of the image block to obtain a normalized transmittance; calculating the weight of the color channel on the dark channel of the image block in the color channel corresponding to the image; calculating a corrected color channel through the normalized transmittance and the weight;
obtaining corrected atmospheric light intensity and corrected transmittance through the corrected color channel;
and obtaining a defogged image according to the corrected color channel, the corrected atmospheric light intensity and the corrected transmissivity.
2. The method of claim 1, wherein obtaining the dark channel of the image through the color channel of the image comprises:
carrying out channel decomposition on the image to obtain each color channel of the image;
dividing the image into set image blocks, and setting the color channel with the minimum gray value corresponding to the image blocks as the dark channel of the image blocks.
3. The method of claim 1, wherein the atmospheric light intensity is obtained by:
acquiring a pixel point set with highest brightness in the dark channel;
selecting pixel points with set proportion from the pixel point set as reference pixel points;
calculating the gray value of the pixel point corresponding to the reference pixel point in the image;
the median of the grey values was set as the atmospheric light intensity.
4. The method of claim 2, wherein obtaining the defogged image according to the corrected color channel, the corrected atmospheric light intensity and the corrected transmittance comprises:
obtaining a defogging color channel of the image through the correction color channel, the correction atmospheric light intensity and the correction transmissivity;
and weighting the defogging color channels to obtain a defogged image corresponding to the image.
5. The method according to claim 2, wherein the dark channel of the image block is calculated by:
<mrow> <msup> <mi>J</mi> <mrow> <mi>d</mi> <mi>a</mi> <mi>r</mi> <mi>k</mi> </mrow> </msup> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>=</mo> <munder> <mi>min</mi> <mrow> <mi>c</mi> <mo>&Element;</mo> <mo>{</mo> <mi>r</mi> <mo>,</mo> <mi>g</mi> <mo>,</mo> <mi>b</mi> <mo>}</mo> </mrow> </munder> <mrow> <mo>(</mo> <munder> <mi>min</mi> <mrow> <mi>y</mi> <mo>&Element;</mo> <mi>&Omega;</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> </mrow> </munder> <msup> <mi>J</mi> <mi>c</mi> </msup> <mo>(</mo> <mi>y</mi> <mo>)</mo> <mo>)</mo> </mrow> <mo>=</mo> <mn>0</mn> </mrow>
wherein, Jdark(y) is the dark channel of the image block and is expressed by a matrix, r, g and b respectively represent red, green and blue, c is one of the three colors of r, g and b, y is a set formed by local small areas taking the space coordinate x of the image as the center, omega is a set symbol and is expressed as y ∈ omega (x), JcAnd (y) is any one of the local area color channels of the image block.
6. The method according to claim 1, wherein the transmittance is calculated by:
<mrow> <mi>t</mi> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>=</mo> <mn>1</mn> <mo>-</mo> <munder> <mi>min</mi> <mi>c</mi> </munder> <mrow> <mo>(</mo> <munder> <mi>min</mi> <mrow> <mi>y</mi> <mo>&Element;</mo> <mi>&Omega;</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> </mrow> </munder> <mo>(</mo> <mfrac> <mrow> <msup> <mi>I</mi> <mi>c</mi> </msup> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> <msup> <mi>A</mi> <mi>c</mi> </msup> </mfrac> <mo>)</mo> <mo>)</mo> </mrow> </mrow>
wherein t (y) is the transmittance; i isc(y) is a color channel corresponding to color c; a. thecIs a color channel Ic(y) corresponding atmospheric light intensity.
7. The image defogging method according to claim 2, wherein the calculation process of the correction color channel is:
<mrow> <msubsup> <mi>I</mi> <mi>c</mi> <mo>&prime;</mo> </msubsup> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>=</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <msub> <mi>T</mi> <mrow> <mi>c</mi> <mi>k</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> <msub> <mi>G</mi> <mrow> <mi>c</mi> <mi>k</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> <msub> <mi>I</mi> <mrow> <mi>c</mi> <mi>k</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow>
wherein, I'c(y) for the corrected color channel, expressed in a matrix; t isck(y) is the normalized transmission; gck(y) is a weight; i isck(y) color channel I of the foggy image in image block kcThe value on (y).
8. The image defogging method according to claim 7, wherein the computation process of the defogging color channels is as follows:
<mrow> <msup> <mover> <mi>J</mi> <mo>~</mo> </mover> <mi>c</mi> </msup> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <msubsup> <mi>I</mi> <mi>c</mi> <mo>&prime;</mo> </msubsup> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>-</mo> <msup> <mover> <mi>A</mi> <mo>~</mo> </mover> <mi>c</mi> </msup> </mrow> <mrow> <mover> <mi>t</mi> <mo>~</mo> </mover> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>+</mo> <msup> <mover> <mi>A</mi> <mo>~</mo> </mover> <mi>c</mi> </msup> </mrow>
wherein,to removeColor channels of the fog image, represented by a matrix; i'c(y) is the corrected color channel;to correct the atmospheric light intensity;to correct the transmittance.
9. The image defogging method according to claim 4, wherein the defogged image is calculated by:
<mrow> <mi>J</mi> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <munder> <mo>&Sigma;</mo> <mrow> <mi>c</mi> <mo>&Element;</mo> <mo>{</mo> <mi>r</mi> <mo>,</mo> <mi>g</mi> <mo>,</mo> <mi>b</mi> <mo>}</mo> </mrow> </munder> <msup> <mover> <mi>J</mi> <mo>~</mo> </mover> <mi>c</mi> </msup> <mrow> <mo>(</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> <mi>n</mi> </mfrac> </mrow>
wherein J (y) is a defogged image and is represented by a matrix; n is a weight value, and the value of n is the same as the number of color channels.
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