CN105005976B - A kind of infrared image enhancing method based on fusion - Google Patents
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Abstract
The present invention provides a kind of infrared image enhancing method based on fusion, the infrared image P including S1, reception infrared detector output；S2, the infrared image P received is divided into low-light (level) component P1, medium luminance component P2 and high illumination component P3；S3, image enhancement processing is carried out to the low-light (level) component P1, the medium luminance component P2 and the high illumination component P3 respectively, it is corresponding to obtain low-light (level) enhancing component P1 ', middle equiluminous enhancing component P2 ' and high illumination enhancing component P3 '；S4, image co-registration processing is carried out to the enhancing of low-light (level) described in step S3 component P1 ', the middle equiluminous enhancing component P2 ' and high illumination enhancing component P3 '；S5, output result P4.The present invention compresses the dynamic range of image and improves the output result with wide dynamic range that contrast and clarity are finally taken into account image clear zone, dark space while retaining key detailed information.
Description
Technical field
The invention belongs to field of image processings, and in particular to a kind of infrared image enhancing method based on fusion.
Background technique
Nowadays, infrared thermal imaging technique is applied to public security, fire-fighting, military affairs, medicine, electric power, industry etc. more and more widely
Field.It is to be imaged using the electromagnetic wave heat radiation of specific wavelength, therefore infrared image can also be referred to as temperature pattern.So
And since infrared imaging system is frequently used for the very big scene of temperature span, such as: ground and sky, room temperature and flame etc..
And in this scene, the temperature difference between the target and background of user's real concern is smaller.Therefore in actual application
In, infrared imaging system not only space with higher and temperature resolving power are needed, but also there is biggish dynamic range of signals.
High-performance infrared imaging system generallys use the signal acquisition unit of 14bits or more seniority top digit to infrared acquisition
Device output signal is sampled and is quantified.In this way, in general stable scene, the gray scale of thermal image may concentrate on one compared with
In small quantizing range, but for some special Larger Dynamic scenes, the gray scale of thermal image may be distributed in larger quantization
In range.In order to guarantee that processing result image has suitable brightness and contrast, display equipment or subsequent is combined
The data volume quickly handled generally requires 14bits high accuracy data being compressed to 8bits data width.If compression is improper,
The image information for just having Larger Dynamic range cannot retain, it may be assumed that Larger Dynamic compression of images is likely to result in 8bits image difficult
To restore detailed information lost in original image out.
Currently, the point of penetration according to the enhancing processing of infrared image details in entire imaging process, it can be to infrared system
The 8bits gray level image of compression output carries out details enhancing processing；But data volume to be treated is smaller (8bits), processing speed
Spend relatively fast, but the details in image has often just been lost in compression process, it is difficult to be given again by subsequent enhancing processing
To restore.
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide one kind to take into account image clear zone, dark space, has wide dynamic
The infrared image enhancing method based on fusion of state range output result.
In order to achieve the above object, the present invention adopts the following technical scheme: a kind of infrared image enhancing method based on fusion,
This method comprises the following steps:
S1, the infrared image P for receiving infrared detector output；
S2, the infrared image P received is divided into low-light (level) component P1, medium luminance component P2 and high illumination point
Measure P3；
S3, figure is carried out to the low-light (level) component P1, the medium luminance component P2 and the high illumination component P3 respectively
Image intensifying processing, it is corresponding to obtain low-light (level) enhancing component P1 ', middle equiluminous enhancing component P2 ' and high illumination enhancing component
P3'；
S4, to the enhancing of low-light (level) described in step S3 component P1 ', middle equiluminous enhancing component P2 ' and described
High illumination enhances component P3 ' and carries out image co-registration processing；
S5, output result P4.
Further, the infrared image P of 14bits is received in the step S1.
Further, in the step S3, low-light (level) component P1, medium luminance component P2 and high illumination component P3 are distinguished
It carries out power transform progress image enhancement processing and obtains low-light (level) enhancing component P1 ', middle equiluminous enhances component P2 ', high illumination
Enhance component P3 ', specific formula is as follows:
C1, C2, C3 refer to the coefficient factor of power transform, b1, b2, and b3 refers to the offset of power transform, γ1, γ2,
γ3Refer to the power series of power transform.
C1, C2, C3, γ1, γ2, γ3It is positive number, wherein γ1< 1, γ2≈ 1, γ3> 1；
When=1, power transform is changed into linear transformation；
When < 0, transform function graph extends low gray level above direct ratio function at this time, compresses high grade grey level, makes figure
As brightening；
When > 0, transform function graph extends high grade grey level below direct ratio function at this time, compresses low gray level, makes figure
As dimmed.
Further, component P1 ', middle equiluminous enhancing point are enhanced to low-light (level) obtained in step S3 in the step S4
P2 ' is measured, high illumination enhances component P3 ' image and carries out fusion treatment, specifically comprises the following steps: S41, to P1 ', P2 ', P3 ' point
Not carry out small echo direct transform, specifically:
The first, uses continuous wavelet transform CWT, formula are as follows:
Wherein, a represents zoom factor, and τ represents time-shifting, and Ψ (t) is wavelet or morther wavelet,Indicate Ψ
(t) complex conjugate.
Second, use wavelet transform DWT, formula are as follows:
WhereinRemaining parameter is same as above.
S42, wavelet coefficient fusion, specific steps are as follows:
The first step, in coefficient image cΔIn (m, n) (Δ=A, B), calculating with (m, n) point is in center surrounding window region
Measurement as this detailed information intensity of energy or variance:
Wherein ω (u, v) is the template window centered on (0,0), and U and V are respectively template window line number and row number composition
Set；
Second step calculates cAAnd cBBetween local, normalized cross-correlation coefficient:
Third step takes different amalgamation modes: working as M according to cross-correlation coefficient sizeABWhen (m, n)≤α, wherein α=
0.85, i.e.,
Work as MABWhen (m, n)≤α, i.e.,
cF(m, n)=W (m, n) cA(m, n)+[I (m, n)-W (m, n)] cB(m, n)；
Wherein I (m, n)) be unit matrix, weight coefficient W (m, n)) determined by following formula:
S43, wavelet inverse transformation
If discrete wavelet sequence { ψj,k(t)}j,k∈ZA frame is constituted, Lower and upper bounds are respectively A and B, then work as A=B
When, being inversely transformed into for wavelet transform can be learnt by frame concept:
As A ≠ B, and A, B relatively when, approach, can use as single orderSo, small echo
The formula of inverse transformation is approximately:
Further, the image data that the enhanced image of step S4 is converted to 8bits is shown in the step S5
Show and handles, used linear gradation transformation for mula are as follows:
Wherein, the pixel value in f (x, y) representing input images at (x, y) coordinate；Indicate the minimum of input picture
Value；Indicate the maximum value of input picture；Indicate the minimum value of output image；Indicate the maximum value of output image；G (x, y) is indicated
Export value of the image at coordinate (x, y).
The present invention uses technical solution as above, is low-light (level) component, middle equiluminous point by the 14bits image segmentation of input
Then these three luminance components are carried out image enhancement processing respectively, finally give three enhancing results by amount and high illumination component
With fusion, the output result with wide dynamic range of image clear zone, dark space is finally taken into account.Existing image enchancing method
Big multipair image integrally carries out enhancing processing, be typically only capable to it is whole promote brightness of image or inhibit dark picture areas, can not two
Person takes into account.The present invention compresses the dynamic range of image and improves contrast and clear while retaining key detailed information
Degree.
Detailed description of the invention
Fig. 1 is the flow chart of the infrared image enhancing method the present invention is based on fusion；
Fig. 2 is the corresponding power letter of different power series of the power transform of the infrared image enhancing method the present invention is based on fusion
Number curve；
Fig. 3 is the image co-registration schematic diagram of the wavelet transformation of the infrared image enhancing method the present invention is based on fusion.
Specific embodiment
Various embodiments of the invention are further illustrated below in conjunction with attached drawing:
As shown in Figure 1, the present invention provides a kind of infrared image enhancing method based on fusion, this method includes following step
It is rapid:
S1, the infrared image P for receiving infrared detector output；
S2, the infrared image P received is divided into low-light (level) component P1, medium luminance component P2 and high illumination point
Measure P3；
S3, figure is carried out to the low-light (level) component P1, the medium luminance component P2 and the high illumination component P3 respectively
Image intensifying processing, it is corresponding to obtain low-light (level) enhancing component P1 ', middle equiluminous enhancing component P2 ' and high illumination enhancing component
P3'；
S4, to the enhancing of low-light (level) described in step S3 component P1 ', middle equiluminous enhancing component P2 ' and described
High illumination enhances component P3 ' and carries out image co-registration processing；
S5, output result P4.
In the present embodiment step S2, specially it is split using the basic, normal, high luminance component of image based on bit plane.
It is 2 for gray levelnImage, pixel value can be written as follow form:
an-12n-1+an-22n-2+...+a121+a020
Each pixel in image is extracted coefficient all in accordance with above formula, a width resolving power is the multivalue of n
Image has reformed into n width bianry image, wherein the i-th width image is made of i-th of binary digit of all pixels, each two
Value image is referred to as a bit plane.
The output of infrared detector is usually 14bits in the present embodiment, can set what the 0---5 binary digit was constituted
Image as low-light (level) component, image that the 4--9 binary digit is constituted as medium luminance component, 8---13 two into
The image that position processed is constituted is as bright field image.That is:
It should be noted that user can determine bit plane model belonging to basic, normal, high illumination according to the needs of practical application
It encloses.For example, user in practical process, can set the image of 0-2 binary systems composition in input 14bits as low photograph
Bit-plane image is spent, the image that 11-13 binary system is constituted is high illumination bit-plane image, remaining is medium illumination image.
As shown in Fig. 2, in the step S3, to low-light (level) component P1, medium luminance component P2 and high illumination component P3
Power transform progress image enhancement processing is carried out respectively and obtains low-light (level) enhancing component P1 ', and middle equiluminous enhances component P2 ', high
Illumination enhances component P3 ', specific formula is as follows:
Here C1, C2, C3 refer to the coefficient factor of power transform, b1, b2, and b3 refers to the offset of power transform,
γ1, γ2, γ3Refer to the power series of power transform.
C1, C2, C3, γ1, γ2, γ3It is positive number, wherein γ1< 1, γ2≈ 1, γ3> 1.
When=1, power transform is changed into linear transformation；
When < 0, transform function graph extends low gray level above direct ratio function at this time, compresses high grade grey level, makes figure
As brightening；
When > 0, transform function graph extends high grade grey level below direct ratio function at this time, compresses low gray level, makes figure
As dimmed.
As shown in figure 3, the clear zone enhancing image and dark space figure that are obtained using wavelet transformation to back in the present embodiment
As being merged.This method carries out wavelet transformation to source images first, then using fusion rule appropriate to different decomposition
Wavelet coefficient on layer is merged, and new wavelet pyramid structure is formed, and is finally carried out inverse wavelet transform again and is acquired fusion figure
Picture.Specifically comprise the following steps:
S41, small echo direct transform, specifically:
The first, by any L2(R) the function x (t) in space is unfolded below wavelet basis, and title is this to expand into x
(t) continuous wavelet transform (ContinoueWaveletTransform, CWT):
Wherein, a represents zoom factor, and τ represents time-shifting.
Second, in Digital Image Processing, usually used is wavelet transform, in any L2(R) x in space
(t) wavelet transform (DiscreteWaveletTransform, DWT) are as follows:
Wherein
It should be noted that discretization here is both for continuous scale parameter and continuous translation parameter, without
It is for time variable t.
S42, wavelet coefficient merge, and wavelet coefficient fusion method is using the weighted average fusion based on window in the present embodiment
Rule.That is: coefficient image is filtered using the window of fixed size, filtered pixel value is strong as the detailed information
The measurement of degree.Specific steps are as follows:
The first step, in coefficient image cΔIn (m, n) (Δ=A, B), calculating with (m, n) point is in center surrounding window region
Measurement as this detailed information intensity of energy or variance:
Wherein ω (u, v) is the template window centered on (0,0), and U and V are respectively template window line number and row number composition
Set；
Second step calculates cAAnd cBBetween local, normalized cross-correlation coefficient:
Third step takes different amalgamation modes: working as M according to cross-correlation coefficient sizeABWhen (m, n)≤α, wherein α is general
0.85 is taken, correlation is relatively low between illustrating source images coefficient, and choosing the big coefficient of local variance is that coefficients comparison is reasonable after merging,
I.e.
Work as MABWhen (m, n) > α, correlation is bigger between illustrating coefficient, more reasonable using average weighted method, i.e.,
cF(m, n)=W (m, n) cA(m, n)+[I (m, n)-W (m, n)] cB(m, n)；
Wherein I (m, n)) be unit matrix, weight coefficient W (m, n)) determined by following formula:
S43, wavelet inverse transformation
Arbitrary function f (t) ∈ L2(R) wavelet inverse transformation are as follows:
For digital picture, using discrete wavelet inverse transform.If discrete wavelet sequence { ψj,k(t)}j,k∈Z
A frame is constituted, Lower and upper bounds are respectively that A and B then when a=b can learn wavelet transform by frame concept
It is inversely transformed into:
As A ≠ B, and A, B relatively when, approach, can use as single orderSo, small echo
The formula of inverse transformation is approximately:
It is analyzed and processed in above-mentioned steps S4 for 14bits image data, and the display equipment of mainstream generallys use
The image data of 8bits is shown and is handled, therefore, it is necessary to which the enhanced result of infrared detector is converted to 8bits
Form facilitate subsequent display and preservation.Used linear gradation transformation for mula are as follows:
Wherein, the pixel value in f (x, y) representing input images at (x, y) coordinate；Indicate the minimum of input picture
Value；Indicate the maximum value of input picture；Indicate the minimum value of output image；Indicate the maximum value of output image；G (x, y) is indicated
Export value of the image at coordinate (x, y).
The present invention is not limited to above-mentioned preferred forms, anyone can show that other are various under the inspiration of the present invention
The product of form, however, make any variation in its shape or structure, it is all that there is skill identical or similar to the present application
Art scheme, is within the scope of the present invention.
Claims (2)
1. a kind of infrared image enhancing method based on fusion, it is characterised in that: this method comprises the following steps:
S1, the infrared image P for receiving infrared detector output；
S2, the infrared image P received is divided into low-light (level) component P1, medium luminance component P2 and high illumination component
P3；
S3, image increasing is carried out to the low-light (level) component P1, the medium luminance component P2 and the high illumination component P3 respectively
Strength reason, it is corresponding to obtain low-light (level) enhancing component P1 ', middle equiluminous enhancing component P2 ' and high illumination enhancing component P3 '；
S4, component P2 ' and the Gao Zhao is enhanced to the enhancing of low-light (level) described in step S3 component P1 ', the middle equiluminous
Degree enhancing component P3 ' carries out image co-registration processing；
S5, output result P4；
In the step S3, power change is carried out respectively to low-light (level) component P1, medium luminance component P2 and high illumination component P3
Swap-in row image enhancement processing obtains low-light (level) enhancing component P1 ', and middle equiluminous enhances component P2 ', and high illumination enhances component
P3 ', specific formula is as follows:
C1, C2, C3 refer to the coefficient factor of power transform, b1, b2, and b3 refers to the offset γ of power transform1, γ2, γ3It refers to
The power series of power transform；
C1, C2, C3, γ1, γ2, γ3It is positive number, wherein γ1< 1, γ2≈ 1, γ3> 1；
When=1, power transform is changed into linear transformation；
When < 0, transform function graph extends low gray level above direct ratio function at this time, compresses high grade grey level, becomes image
It is bright；
When > 0, transform function graph extends high grade grey level below direct ratio function at this time, compresses low gray level, becomes image
Secretly；
Component P1 ' is enhanced to low-light (level) obtained in step S3 in the step S4, middle equiluminous enhances component P2 ', Gao Zhao
Degree enhancing component P3 ' image carries out fusion treatment, specifically comprises the following steps:
S41, to P1 ', P2 ', P3 ' respectively carry out small echo direct transform, specifically:
For continuous signal, usually using continuous wavelet transform CWT, formula are as follows:
Wherein, a represents zoom factor, and τ represents time-shifting, and Ψ (t) is wavelet or morther wavelet,It indicates Ψ (t)
Complex conjugate；
For image, due to belonging to discrete signal, usually using wavelet transform DWT, formula are as follows:Wherein
S42, wavelet coefficient fusion, specific steps are as follows:
The first step, in coefficient image cΔIn (m, n) (Δ=A, B), calculate with (m, n) point as the energy in center surrounding window region
The measurement of amount or variance as this detailed information intensity:
Wherein ω (u, v) is the template window centered on (0,0), and U and V are respectively the collection of template window line number and row number composition
It closes；
Second step calculates two coefficient image cAAnd cBBetween local, normalized cross-correlation coefficient:
Third step takes different amalgamation modes according to cross-correlation coefficient size: when
MABWhen (m, n)≤α, wherein α=0.85, i.e.,
Work as MABWhen (m, n) > α, i.e.,
cF(m, n)=W (m, n) cA(m, n)+[I (m, n)-W (m, n)] cB(m, n)；
Wherein I (m, n) is unit matrix, and weight coefficient W (m, n) is determined by following formula:
S43, wavelet inverse transformation
If discrete wavelet sequence { ψJ, k(t)}J, k ∈ ZConstituting a frame, Lower and upper bounds are respectively A and B, then when a=b, by
Frame concept can learn being inversely transformed into for wavelet transform:
As A ≠ B, and A, B relatively when, approach, can use as single orderSo, wavelet inverse transformation
Formula be approximately:
The image data that the enhanced image of step S4 is converted to 8bits is shown and handled in the step S5, institute
Using linear gradation transformation for mula are as follows:
Wherein, the pixel value in f (x, y) representing input images at (x, y) coordinate；fminIndicate the minimum value of input picture；
fmaxIndicate the maximum value of input picture；gminIndicate the minimum value of output image；gmaxIndicate the maximum value of output image；g(x,
Y) value of the output image at coordinate (x, y) is indicated.
2. a kind of infrared image enhancing method based on fusion according to claim 1, it is characterised in that: the step S1
The middle infrared image P for receiving 14bits.
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