CN103886590A - Method for automatic focusing of push-scanning type remote sensing camera based on wavelet packet energy spectrum - Google Patents
Method for automatic focusing of push-scanning type remote sensing camera based on wavelet packet energy spectrum Download PDFInfo
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Abstract
The invention discloses a method for automatic focusing of a push-scanning type remote sensing camera based on a wavelet packet energy spectrum. The method comprises the following steps that firstly, gray level image conversion and brightness normalization preprocessing are conducted; secondly, four-layer wavelet packet decomposition is conducted on an image and wavelet coefficient matrixes, perpendicular to the motion direction of the camera, of frequency bands of a frequency domain are selected; thirdly, an energy spectrum exponential value and a definition evaluation function value of wavelet packets of the frequency bands are calculated; finally, automatic focusing and adjustment of the camera are achieved, the focusing position corresponding to the largest definition evaluation value is selected to serve as the final camera clear imaging position, and therefore automatic focusing is finished. According to calculation results of energy spectrums of the wavelet packets in the frequency bands of an out-of-focus remote sensing image in the perpendicular direction, weighing summation is conducted, focusing evaluation of the push-scanning type remote sensing camera is achieved, and the evaluation method is good in accuracy and monotony and unrelated to image content.
Description
Technical field
The invention belongs to remotely sensed image technical field, relate to a kind of push-broom type remote sensing camera Atomatic focusing method based on Wavelet Packet Energy Spectrum.
Background technology
Along with the development of Aid of Space Remote Sensing Technology, remote sensing images, in each side such as environmental monitoring, resource exploration, topographic mapping, military surveillances, play a part more and more important.Remote sensing camera is the key that digital remote sensing image is obtained, can blur-free imaging in complex environment in order to ensure space remote sensing camera, and space remote sensing camera need to be equipped with a set of focusing system, revises in time focusing position to ensure image quality.
Push-broom type remote sensing camera is the conventional space remote sensing camera of a class, this class camera be not a width expose, but continuous exposure, so this class camera does not need shutter, structure is relatively simple.Along with the fast development of electronic technology, the Atomatic focusing method based on image processing becomes the study hotspot of push-broom type remote sensing camera focusing technology, thereby instructs camera to carry out focusing work by the definition values that calculates image of focusing evaluation method.
Traditional focusing evaluation method all needs scenery to keep static, and space camera is kept in motion always, thereby cannot directly these focusing evaluation methods be applied in space camera; Meanwhile, push-broom type remote sensing camera at any time captured scenery is all different, does not have overlapping region between frame and frame.At present push-broom type remote sensing camera focusing evaluation method mainly contains: based on differential map as autocorrelative focusing evaluation method, focusing evaluation method based on line spread function and the focusing evaluation method based on power spectrum.Wherein the focusing evaluation method based on power spectrum is the Autofocus Technology that is best suited for push-broom type remote sensing camera, pass through wavelet transformation, ask for the wavelet coefficient under the different scale vertical with direction of motion, and these wavelet coefficients of the downward different scale of the party are weighted to summation, thereby as sharpness evaluation index, not only efficiently solve picture and move mismatch problems, and all have good performance at aspects such as robustness, correctness, accuracies.But in the time that the identical different scenes of fuzzy quantity are evaluated, its evaluation of estimate still cannot reach identical value, when the image that especially differs larger to scene structure is evaluated, even if they have identical fuzzy quantity, but that its evaluation result also differs is larger.How to realize the key that the fuzzy assessment method irrelevant with picture material is push-broom type remote sensing camera Atomatic focusing method.
Summary of the invention
The present invention proposes a kind of push-broom type remote sensing camera Atomatic focusing method based on Wavelet Packet Energy Spectrum, can be by the result of calculation of the each frequency range Wavelet Packet Energy Spectrum of remote sensing images motion vertical direction out of focus be weighted to summation, realize the focusing evaluation for push-broom type remote sensing camera, evaluation method has good accuracy and monotonicity, and accomplishes with picture material irrelevant.
The present invention is based on the decomposition of image wavelet bag and energy spectrum index and calculate, proposed a kind of automatic focusing evaluation method of push-broom type remote sensing camera, its main thought is:
1, remote sensing images are carried out to WAVELET PACKET DECOMPOSITION.
WAVELET PACKET DECOMPOSITION technology is on the basis of wavelet decomposition, the medium-high frequency section wavelet coefficient that stops in wavelet transformation decomposing is continued to decompose, have frequency resolution meticulous, effectively represent the advantage of local signal and good time-frequency characteristic, signal decomposition can be become to meticulousr frequency component, even if only there is small fuzzy quantity difference in image so, utilize WAVELET PACKET DECOMPOSITION also can carry out effective sharpness evaluation, thereby improve the assess performance of focusing evaluation method.Meanwhile, WAVELET PACKET DECOMPOSITION image frequency domain power spectrum has unchangeability, between different content, has almost consistent energy spectrum curve in Wavelet Packet Domain, can realize the focusing evaluation method irrelevant with picture material.
2, choose and sweep the vertical frequency domain frequency range of camera motion direction with pushing away, calculate the wavelet-packet energy spectrum index of each frequency range wavelet coefficient, weighted sum obtains final clear evaluation index.
Push-broom type remote sensing camera is due to its special imaging mode, and the image frequency domain component consistent with its direction of motion can be subject to certain impact due to camera motion, causes distortion to a certain degree.Choose the frequency domain frequency range vertical with camera motion direction, can get rid of the interference of camera motion, accurately reflect that the image power spectrum that out of focus factor causes changes.Meanwhile, consider that image defocus blur mainly causes the decay of image radio-frequency component, for high-frequency band set larger weighting coefficient and reduce the weight coefficient of low frequency frequency range can more effective response diagram as out of focus situation.
The present invention includes following steps:
(1) input remote sensing images F (x, y) are carried out to gray-scale map conversion, brightness normalized, obtains pretreatment image G (x, y).If the remote sensing images of input are coloured image, need to first be converted into gray scale territory, gray level image brightness is normalized to [0 1] interval.
(2) step (1) is processed to the image G (x, y) obtaining and carry out four layers of WAVELET PACKET DECOMPOSITION, obtain each frequency range wavelet coefficient matrix that every one deck decomposes.For the image that is of a size of M × N, utilize two-dimentional scaling function and 2-d wavelet function, image G (x, y) can be expressed as:
Wherein m, n represents the coordinate position of wavelet packet coefficient matrix,
two-dimentional scaling function, ψ
h(x, y), ψ
v(x, y), ψ
d(x, y) is respectively the 2-d wavelet function along horizontal edge direction H, vertical edge direction V and diagonal D variation.J
0to start arbitrarily yardstick,
coefficient Definition at yardstick j
0g (x, y) approximate;
coefficient is for j>=j
0add the details of level, vertical and focusing direction.
Wavelet decomposition all can obtain a low frequency frequency range and three high-frequency band each time, and WAVELET PACKET DECOMPOSITION is all decomposed again low frequency component and high fdrequency component in every one deck, thereby obtains how meticulous frequency range.
(3) for four layers that obtain in step (2) each frequency-domain small wave matrix of coefficients, in the 3rd layer, to choose and sweep 1 vertical lower frequency region frequency range of camera motion direction with pushing away, its wavelet coefficient defined matrix is C
1; 4 frequency domain frequency ranges, its wavelet coefficient defined matrix is C
i(i=2,3,4,5); In the 4th layer, choose all pushing away and sweep 64 vertical high-frequency domain frequency ranges of camera motion direction, its wavelet coefficient defined matrix is C
j(j=6,7...69).Choose altogether 69 frequency ranges and be used for calculating its wavelet-packet energy desired value.
(4) by the wavelet coefficient Matrix C of the each frequency range selecting in step (3)
k(k=1,2...69) processes, and calculates the wavelet-packet energy spectrum index Q of each frequency range in sign and camera motion vertical direction
k(k=1,2...69).According to singular value decomposition method, the wavelet coefficient Matrix C of a certain frequency range
ksvd can write and do:
Wherein C
kthe wavelet coefficient matrix on m × n rank, U
kthe unitary matrix of m × m, V
k' be V
kconjugate transpose, be the unitary matrix of n × n, U
k' U
k=I, V
k' V
k=I, Σ
kpositive semidefinite m × n rank diagonal matrix,
σ
kibe called matrix of coefficients C
ksingular value, according to descending sort be:
σ
k1≥σ
k2≥…≥σ
kr＞0
σ in theory
k1much larger than other singular value, available σ
k1representing matrix C
kmost energy.In order to eliminate the impact of sample randomness on energy, make with the different scene images under fuzzy energy under similar frequency bands to be similar to identical, can select σ
k1represent wavelet-packet energy, and remove the impact of other singular values on energy.Wavelet-packet energy spectrum index Q
kbe expressed as:
Q
k＝log
10(1+σ
k1) (4)
Wherein, σ
k1represent the wavelet packet coefficient Matrix C corresponding to a certain frequency range
kcarry out svd, obtain C
kcorresponding diagonal angle eigenvalue matrix, the maximum eigenwert of therefrom choosing.It is carried out to logarithm operation, obtain the Wavelet Packet Energy Spectrum exponential quantity Q of this frequency range
k.
(5) to each frequency range Wavelet Packet Energy Spectrum exponential quantity weighted sum of choosing in step (4), obtain final sharpness evaluation function:
Wherein N=69, represents selected frequency range number.K represents the order sequence number of selected frequency range, Q
krepresent the Wavelet Packet Energy Spectrum exponential quantity of certain frequency range, P
kfor corresponding weight coefficient, P
k=k/N, represents that frequency range order is higher, and its weight coefficient value is larger.Because out of focus mainly causes the high frequency attenuation of image, thereby strengthen the weight coefficient of high frequency and the weight coefficient that reduces low frequency can reflect the out of focus situation of image effectively.This evaluation index evaluation of estimate is less, shows that image is fuzzyyer.Carry out camera focusing according to image definition evaluation value.
(6) repeat (2)～(5), selecting the corresponding focusing position of sharpness evaluation of estimate maximum is final camera blur-free imaging position, finishes focusing automatically.
The present invention utilizes WAVELET PACKET DECOMPOSITION technology, the remote sensing images that push-broom type remote sensing camera is obtained carry out four layers of WAVELET PACKET DECOMPOSITION, choose the frequency domain frequency range with camera motion direction verticality, and calculate the Wavelet Packet Energy Spectrum exponential quantity of each frequency range, its weighted sum is obtained to final Image Definition, in order to instruct camera automatically to focus.The present invention can be applicable to push-broom type remote sensing camera Autofocus Technology field, can realize the focusing evaluation irrelevant with picture material.
Brief description of the drawings
Fig. 1 is the inventive method process flow diagram.
Fig. 2 is 2-d wavelet bag decomposing schematic representation, and decomposing the number of plies is 2 layers.
Fig. 3 is the schematic diagram of 69 the frequency domain frequency ranges vertical with camera motion direction chosen.
Fig. 4 (a) is 5 width wavelet-packet energy spectral curve test experiments remote sensing images.
Fig. 4 (b) is 5 width remote sensing figure wavelet-packet energy spectral curve results.
Fig. 5 is the clear remote sensing figure that 25 width contents are different.
Fig. 6 is the sharpness evaluation result of 25 width images under different defocusing amounts in Fig. 5, has reacted monotonicity and the consistance of focusing evaluation algorithms.
Embodiment
Below in conjunction with accompanying drawing, the invention will be further described.
As shown in Figure 1, concrete steps are process flow diagram of the present invention:
(1) input remote sensing images F is carried out to gray-scale map conversion, brightness normalized, obtains pretreatment image G.
(2) step (1) is processed to the image G obtaining and carry out four layers of WAVELET PACKET DECOMPOSITION, obtain each frequency range wavelet coefficient matrix that every one deck decomposes.
(3) for four layers that obtain in step (2) each frequency-domain small wave matrix of coefficients, in the 3rd layer, to choose and sweep 1 vertical lower frequency region frequency range of camera motion direction with pushing away, its wavelet coefficient defined matrix is C
1; 4 frequency domain frequency ranges, its wavelet coefficient defined matrix is C
i, i=2,3,4,5; In the 4th layer, choose and allly sweep 64 vertical high-frequency domain frequency ranges of camera motion direction with pushing away, its wavelet coefficient defined matrix is C
j, j=6,7...69.
(4) by the wavelet coefficient Matrix C of the each frequency range selecting in step (3)
kprocess, k=1,2...69, calculate characterize with camera motion vertical direction on the wavelet-packet energy spectrum index Q of each frequency range
k; Wavelet-packet energy spectrum index Q
kbe expressed as:
Q
k＝log
10(1+σ
k1)
Wherein, σ
k1represent the wavelet packet coefficient Matrix C corresponding to a certain frequency range
kcarry out svd, obtain C
kcorresponding diagonal angle eigenvalue matrix, the maximum eigenwert of therefrom choosing; It is carried out to logarithm operation, obtain the Wavelet Packet Energy Spectrum exponential quantity Q of this frequency range
k.
(5) each frequency range Wavelet Packet Energy Spectrum exponential quantity step (4) being calculated, is weighted summation, obtains sharpness evaluation function; This evaluation index evaluation of estimate is less, shows that image is fuzzyyer; Instruct the adjustment of automatically focusing of push-broom type remote sensing camera according to sharpness evaluation of estimate.
(6) repeat (2)～(5), selecting the corresponding focusing position of sharpness evaluation of estimate maximum is final camera blur-free imaging position, finishes focusing automatically.
Fig. 2 is the schematic diagram of a two-layer WAVELET PACKET DECOMPOSITION.Operated frequency range is divided into 4 frequency ranges by the decomposition meeting of every one deck: a low frequency frequency range, the high-frequency band of a horizontal direction, the high-frequency band of the high-frequency band of a vertical direction and a diagonal.WAVELET PACKET DECOMPOSITION is not only decomposed low frequency frequency range at every one deck, proceeds equally to decompose for high-frequency band, obtains successively the how meticulous frequency range under each frequency domain components.For certain one deck decomposes, from left to right raise successively according to frequency range shown in schematic diagram.
Algorithm carries out after four layers of WAVELET PACKET DECOMPOSITION image, need to choose the frequency domain frequency range vertical with camera motion direction and be used for calculating wavelet-packet energy spectrum index.Suppose that camera motion direction is image level direction, Fig. 3 is the schematic diagram (WAVELET PACKET DECOMPOSITION of some sublayers is not all listed) of selected 69 frequency domain frequency ranges, the square frame that wherein WWV represents in the 3rd layer is 1 low frequency frequency range choosing, WVW, WVH, the square frame that WVV and WVD represent is 4 intermediate-frequency bands choosing, and they are that the low frequency component in being decomposed by image ground floor further decomposes and obtains; Represented square frame from VWW to VDD in the 4th layer is 64 selected high-frequency band, and frequency range from left to right raises successively, and they are that the vertical direction details component in being decomposed by image ground floor further decomposes and obtains.
For the unchangeability feature of wavelet-packet energy power spectrum is described, 5 width test patterns in Fig. 4 (a), between them, there is neighborhood similarity, image scene is not quite identical, comprise different structure scene altimetric image content, Ye You city, existing ocean, is used for the imaging situation of Reality simulation push-broom type remote sensing camera.In Fig. 4 (b), solid line represents the wavelet-packet energy spectral curve of this 5 width test picture rich in detail, and synteny does not represent different content image, and the dotted line in Fig. 4 (b) represents the wavelet energy spectral curve of this 5 width picture rich in detail after a certain amount of identical defocus blur.As seen from the figure, different images has almost consistent wavelet-packet energy spectral curve under identical fog-level, and when fuzzy increase, high-frequency energy decay, curve declines.By the effectively focusing sharpness situation of response diagram picture of wavelet-packet energy spectrum index.
For monotonicity and the consistance of verification method, in Fig. 5, be 25 width test patterns, comprise different content scenes, difference is very large.To each picture rich in detail, from left to right, add successively from top to bottom even disk fuzzy in order to the emulation remote sensing camera out of focus situation different to different scenes.Blur radius is from 1 pixel to 25 pixel, and step-length is 1 pixel, obtains 25 width contents differences and the fuzzy image increasing successively.With proposed algorithm, 25 width out-of-focus images are processed, Fig. 6 is its sharpness evaluation of estimate, and horizontal ordinate is Gaussian Blur standard deviation, the sharpness evaluation index that ordinate is each image.As we know from the figure, for the image of different scenes, the focusing evaluation method based on Wavelet Packet Energy Spectrum has good monotonicity and consistance, can effectively instruct push-broom type remote sensing camera automatically to focus.
Claims (2)
1. the push-broom type remote sensing camera Atomatic focusing method based on Wavelet Packet Energy Spectrum, is characterized in that the method comprises the following steps:
(1) input remote sensing images F is carried out to gray-scale map conversion, brightness normalized, obtains pretreatment image G;
(2) step (1) is processed to the image G obtaining and carry out four layers of WAVELET PACKET DECOMPOSITION, obtain each frequency range wavelet coefficient matrix that every one deck decomposes;
(3) for four layers that obtain in step (2) each frequency-domain small wave matrix of coefficients, in the 3rd layer, to choose and sweep 1 vertical lower frequency region frequency range of camera motion direction with pushing away, its wavelet coefficient defined matrix is C
1; 4 frequency domain frequency ranges, its wavelet coefficient defined matrix is C
i, i=2,3,4,5; In the 4th layer, choose and allly sweep 64 vertical high-frequency domain frequency ranges of camera motion direction with pushing away, its wavelet coefficient defined matrix is C
j, j=6,7...69;
(4) by the wavelet coefficient Matrix C of the each frequency range selecting in step (3)
kprocess, k=1,2...69, calculate characterize with camera motion vertical direction on the wavelet-packet energy spectrum index Q of each frequency range
k; Wavelet-packet energy spectrum index Q
kbe expressed as:
Q
k＝log
10(1+σ
k1) (1)
Wherein, σ
k1represent the wavelet packet coefficient Matrix C corresponding to a certain frequency range
kcarry out svd, obtain C
kcorresponding diagonal angle eigenvalue matrix, the maximum eigenwert of therefrom choosing; It is carried out to logarithm operation, obtain the Wavelet Packet Energy Spectrum exponential quantity Q of this frequency range
k;
(5) each frequency range Wavelet Packet Energy Spectrum exponential quantity step (4) being calculated, is weighted summation, obtains sharpness evaluation function; This evaluation index evaluation of estimate is less, shows that image is fuzzyyer; Instruct the adjustment of automatically focusing of push-broom type remote sensing camera according to sharpness evaluation of estimate;
(6) repeat (2)～(5), selecting the corresponding focusing position of sharpness evaluation of estimate maximum is final camera blur-free imaging position, finishes focusing automatically.
2. Atomatic focusing method as claimed in claim 1, carries out remote sensing images after four layers of WAVELET PACKET DECOMPOSITION, to it is characterized in that:
When WAVELET PACKET DECOMPOSITION is decomposed low frequency component, can continue to decompose by centering high frequency wavelet coefficient, obtain more fine frequency components, even if there is small fuzzy quantity difference between image, the sharpness evaluation of also can effectively automatically focusing;
To each small echo frequency range of choosing, utilize the eigenvalue of maximum of wavelet coefficient matrix to characterize this frequency range wavelet-packet energy spectrum index, by the weighted sum of each frequency range Wavelet Packet Energy Spectrum exponential quantity, obtain final sharpness evaluation function:
Wherein N=69, represents selected frequency range number; K represents the order sequence number of selected frequency range, Q
krepresent the Wavelet Packet Energy Spectrum exponential quantity of certain frequency range, P
kfor corresponding weight coefficient, P
k=k/N, represents that frequency range order is higher, and its weight coefficient value is larger; Because out of focus mainly causes the high frequency attenuation of image, thereby strengthen the weight coefficient of high frequency and the weight coefficient that reduces low frequency can reflect the out of focus situation of image effectively; This evaluation index evaluation of estimate is less, shows that image is fuzzyyer.
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