CN102867320B - Method for constructing integral discrete degraded image in uniform motion on basis of superposition of sub-images - Google Patents
Method for constructing integral discrete degraded image in uniform motion on basis of superposition of sub-images Download PDFInfo
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Abstract
The invention discloses a method for constructing an integral discrete degraded image in uniform motion on the basis of superposition of sub-images, belongs to a section using more than one image in the field of general image data processing or generation, and particularly relates to a method for constructing a blurred image in discrete motion. The method includes constructing n sub-images fig i (i=1, 2, ..., n) according to n-pixel motion distances of an original image with the resolution of M*N along a row or column direction of the original image; and then carrying out equally-weighted linear superposition for the obtained n sub-images according to a formula shown in the description. The n is smaller than the N if the original image moves along the row direction, and the n is smaller than the M if the original image moves along the column direction. In the formula, the fig is the constructed discrete degraded image. The method for constructing the discrete degraded image has the advantages that operation time is short, a degradation process is visible and is easy to understand, and the image does not need to be readjusted.
Description
Technical field
View picture uniform motion discrete degraded image building method based on subimage superposition to belong in general image real time transfer or generation field by using more than the part of piece image, particularly relates to a kind of discrete motion blurred picture building method.
Background technology
If there is relative motion between imageing sensor and target in imaging process, gained image will produce motion blur phenomenon.At daily life, commercial production, aerospace field, this phenomenon is very general.Although motion blur image can present the aesthetic feeling of art in some special dimension, but in most field such as communications and transportation, commercial production, motion blur image but can only make troubles to the identification of target in image and to the acquisition of target detail information to us.As the electronic eyes in traffic and transport field, if the fog-level photographing image brings difficulty to the identification of license plate number, be so just difficult to press chapter punishment to vehicles peccancy, be unfavorable for the conventional maintenance of traffic order, cause potential safety hazard to the life of people.
Avoid the generation of motion blur phenomenon in image, generally adopt stabilization technology, stabilization technology comprises optical anti-vibration and electronic flutter-proof, optical anti-vibration is divided into again camera lens stabilization and imaging stabilization, camera lens stabilization refers to and arrange special stabilization compensating glass group in camera lens, according to jitter direction and the degree of camera, and the corresponding adjustment position of compensating glass group and angle, light path is made to keep stable, as Canon EF IS series camera lens, Nikon VR series camera lens, suitable horse OS series camera lens; Imaging stabilization refers to image device after perception camera shake, and the position or the angle that change image device are held in the stable of picture, and this technology was widely used in the digital camera epoch.Electronic flutter-proof refers to by analyzing become image, then utilizes the stabilization technology that algorithm compensates image, and this technology carrys out compensate for jitter indeed through reduction image quality, attempts between image quality and float, obtain an equilibrium point.Electronic flutter-proof, compared with optical anti-vibration, has cost low, the feature of weak effect, and therefore electronic flutter-proof is only used in low side camera.But the algorithm about electronic flutter-proof is but more subject to the concern of academia than optical anti-vibration technology.
For the algorithm of electronic flutter-proof, it is exactly the restoration algorithm of corresponding academia motion blur image, present stage, restoration algorithm was very many, there are traditional liftering algorithm, Wiener filtering algorithm, also has numerous blind restoration algorithm such as Kalman filtering algorithm and projections onto convex sets, up to now, the new algorithm of improvement is still had to continue to bring out out.In order to verify the adaptability of these new restoration algorithms, needing to restore the different degraded image of only degradation parameter, and comparing with original image.When each collection image, although we artificially can set the degradation parameter of image as required, but the impact of random noise cannot be avoided, the image sequence that actual acquisition is arrived is except degradation parameter difference, the impact of random noise will inevitably be subject to, therefore cannot actual acquisition to the different degraded image of only degradation parameter.
The way overcoming this problem is very simple, manually degenerates exactly by the mode of software simulation to the different degenrate function of original non degenerate imagery exploitation.By people's works such as Gonzalez, the people such as Ruan Qiuqi translation, and " Digital Image Processing " of being published by China Machine Press summarizes the method for two kinds of artificial degraded images that prior art adopts in book:
The first is spatial domain convolution degeneration method, if original image is f (x, y), degenrate function is h (x, y), then degraded image g (x, y) is expressed as:
g(x,y)＝f(x,y)*h(x,y)
In formula, " * " represents convolution algorithm; For the discrete picture of M × N, the process that the first spatial domain convolution way of degeneration obtains degraded image can be write as further:
In formula, x=1,2 ..., M; Y=1,2 ..., N.Can know according to formula above, calculate discrete degraded image g (x, y), need x, y, m, n completes quadruple loop computation and could realize, quadruple loop computation makes the computation process of discrete degraded image g (x, y) very consuming time, and this is the shortcoming of spatial domain convolution way of degeneration.
The second is that frequency domain Fourier degenerates method, if the frequency spectrum of original image f (x, y) is F (u, v), the frequency spectrum of degenrate function h (x, y) is H (u, v), then the frequency spectrum designation of degraded image g (x, y) is:
G(u,v)＝F(u,v)H(u,v)
In formula, u=1,2 ..., M; V=1,2 ..., N.Due to the existence of Fast Fourier Transform (FFT) method, frequency domain Fourier method of degenerating is made to compare spatial domain convolution degeneration method and have on operation time and significantly promote, but, this method also has himself shortcoming: first, whole degenerative process completes in a frequency domain, degenerative process is neither directly perceived, not easily understands again; Secondly, by the frequency spectrum G (u of degraded image g (x, y), v) carry out inverse Fourier transform and obtain degraded image g (x, y) in process, also need image border to move to center, otherwise correspondingly with real image not go up.
Summary of the invention
The present invention is exactly the shortcoming for spatial domain convolution degeneration method length operation time, and frequency domain Fourier transform degeneration method intuitively, is not easily understood, and after inverse Fourier transform, also need shortcoming image being moved to operation, propose a kind of discrete degraded image building method of view picture uniform motion based on subimage superposition; The method not only operation time short, and degenerative process is directly perceived, is convenient to understand, and without the need to adjusting image again.
The object of the present invention is achieved like this:
The discrete degraded image building method of view picture uniform motion based on subimage superposition comprises the following steps:
A. be that the original image of M × N moves along its row or column direction the distance of n pixel according to resolution, construct n subimage fig
i(i=1,2 ..., n), wherein:
If original image moves in the row direction, then n≤N;
If original image moves along column direction, then n≤M;
B. n the subimage obtained by step a carries out equal weight linear superposition according to following formula:
In formula, fig is the discrete degraded image constructed.
The above-mentioned discrete degraded image building method of view picture uniform motion based on subimage superposition, in described step a, the 1st subimage fig
1be expressed as:
The above-mentioned discrete degraded image building method of view picture uniform motion based on subimage superposition, in described step a, original image is uniform motion upwards, i-th subimage fig
i(2≤i≤n) is expressed as:
The above-mentioned discrete degraded image building method of view picture uniform motion based on subimage superposition, in described step a, the downward uniform motion of original image, i-th subimage fig
i(2≤i≤n) is expressed as:
The above-mentioned discrete degraded image building method of view picture uniform motion based on subimage superposition, in described step a, original image is uniform motion left, i-th subimage fig
i(2≤i≤n) is expressed as:
The above-mentioned discrete degraded image building method of view picture uniform motion based on subimage superposition, in described step a, original image is uniform motion to the right, i-th subimage fig
i(2≤i≤n) is expressed as:
The above-mentioned discrete degraded image building method of view picture uniform motion based on subimage superposition, the discrete degraded image fig obtained by step b carries out gray-scale value adjustment according to following formula:
fig_improve＝k·fig
In formula, k is regulation coefficient, and fig_improve is the discrete degraded image after adjustment.
The above-mentioned discrete degraded image building method of view picture uniform motion based on subimage superposition, described regulation coefficient k is after the described discrete degraded image fig mean value divided by all grey scale pixel values of this image, then is multiplied by the 1st subimage fig
1the mean value of all grey scale pixel values.
The invention has the beneficial effects as follows:
1) due to discrete degraded image building method of the present invention be according to original image motion n pixel distance, construct n subimage, and simple linear sum operation is carried out to these subimages, therefore be only n the matrix representing n subimage the operation time of the method and be added the time used, avoid spatial domain convolution degeneration method four recirculate, and therefore the method has short beneficial effect operation time;
2) due to n locus in n of the present invention subimage respectively corresponding imaging process residing for target, carry out the expression of simple linear sum operation to this n subimage the subimage of this n locus is recorded, whole degenerative process completes in spatial domain, the direct corresponding imaging process of calculating process, therefore to have degenerative process directly perceived for the method, be convenient to understand, and the beneficial effect without the need to adjusting again image.
Accompanying drawing explanation
Fig. 1 is original image.
Fig. 2 is the degraded image based on subimage stacking method.
Fig. 3 is the degraded image based on convolution method.
Fig. 4 is the degraded image based on Fourier transformation method.
Embodiment
Below in conjunction with accompanying drawing, the specific embodiment of the invention is described in further detail.
Fig. 1 does not have the resolution of degenerating to be the original image of 256 × 256, and in the present embodiment, original image is from its initial position along the distance of column direction upwards uniform motion 6 pixels.
The discrete degraded image building method of view picture uniform motion based on subimage superposition comprises the following steps:
A. according to resolution be 256 × 256 original image to move upward along its column direction the distance of 6 pixels, construct 6 subimage fig
1~ fig
6, and meet 6<256;
Wherein, fig
1there is the function distribution that same original image is identical:
Element value in matrix represents the gray-scale value of this image correspondence position pixel.
The above-mentioned discrete degraded image building method of view picture uniform motion based on subimage superposition, in described step a, original image is uniform motion upwards, i-th subimage fig
i(2≤i≤6) are expressed as:
B. 6 subimages obtained by step a carry out equal weight linear superposition according to following formula:
In formula, fig is the discrete degraded image constructed.
The above-mentioned discrete degraded image building method of view picture uniform motion based on subimage superposition, the discrete degraded image fig obtained by step b carries out gray-scale value adjustment according to following formula:
fig_improve＝k·fig
In formula, k is regulation coefficient, and fig_improve is the discrete degraded image after adjustment.Described regulation coefficient k is after the described discrete degraded image fig mean value divided by all grey scale pixel values of this image, then is multiplied by the 1st subimage fig
1the mean value of all grey scale pixel values, the degraded image obtained after adjustment as shown in Figure 2.
Short in order to verify that the view picture uniform motion discrete degraded image building method that the present invention is based on subimage superposition has not only operation time further, and degenerative process is directly perceived, be convenient to understand, and the beneficial effect without the need to adjusting again image, method of spatial domain convolution degeneration method and frequency domain Fourier in method therefor of the present invention and prior art being degenerated contrasts.
No matter spatial domain convolution degeneration method or frequency domain Fourier degenerate method, and its spatial domain degenrate function h is the matrix of 256 × 256, and 123rd ~ 128 row in this matrix, 6 elements of the 128th row are 1, and rest of pixels is 0.According to spatial domain convolution degeneration method, utilize degraded image g (x, y) that g (x, y)=f (x, y) * h (x, y) obtains as shown in Figure 3; To degenerate method according to frequency domain Fourier, utilize G (u, v)=F (u, v) H (u, v) first obtains the frequency spectrum of degraded image g (x, y), again through inverse Fourier transform, and image border is moved to center, the degraded image g (x, y) obtained is as shown in Figure 4.
Fig. 2, Fig. 3, Fig. 4 are contrasted, the maximum difference of Fig. 2 and Fig. 3 respective pixel gray-scale value is only 8.5265 × 10
-14, the maximum difference of Fig. 2 and Fig. 4 respective pixel gray-scale value is only 2.2737 × 10
-13, the small difference between each method rounds off due to computer-internal mathematical operation and causes, completely negligible.This conclusion illustrates that the view picture uniform motion discrete degraded image building method that the present invention is based on subimage superposition has same prior art spatial domain convolution degeneration method and frequency domain Fourier and to degenerate the identical deteriorating effect of method.
In addition, on operation time, the present invention is based on the view picture uniform motion discrete degraded image building method used time 0.2030s of subimage superposition, spatial domain convolution degeneration method used time 281.3590s, frequency domain Fourier degenerates method used time 0.2500s, can find out, the present invention compares with spatial domain convolution degeneration method, has short beneficial effect operation time, compare with frequency domain Fourier method of degenerating, there is degenerative process directly perceived, be convenient to understand, and the beneficial effect without the need to adjusting again image.
Claims (1)
1., based on the discrete degraded image building method of view picture uniform motion of subimage superposition, it is characterized in that said method comprising the steps of:
A. be that the original image of M × N moves along its row or column direction the distance of n pixel according to resolution, construct n subimage fig
i(i=1,2 ..., n), wherein:
If original image moves in the row direction, then n≤N;
If original image moves along column direction, then n≤M;
B. n the subimage obtained by step a carries out equal weight linear superposition according to following formula:
In formula, fig is the discrete degraded image constructed;
C. the discrete degraded image fig obtained by step b carries out gray-scale value adjustment according to following formula:
fig_improve＝k·fig
In formula, k is regulation coefficient, and fig_improve is the discrete degraded image after adjustment, and described regulation coefficient k is after the described discrete degraded image fig mean value divided by all grey scale pixel values of this image, then is multiplied by the 1st subimage fig
1the mean value of all grey scale pixel values;
In described step a, at the 1st subimage fig
1be expressed as:
When:
Original image is uniform motion upwards, i-th subimage fig
i(2≤i≤n) is expressed as:
The downward uniform motion of original image, i-th subimage fig
i(2≤i≤n) is expressed as:
Original image is uniform motion left, i-th subimage fig
i(2≤i≤n) is expressed as:
Original image is uniform motion to the right, i-th subimage fig
i(2≤i≤n) is expressed as:
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Citations (1)
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| CN102082914A (en) * | 2009-11-30 | 2011-06-01 | 佳能株式会社 | Image processing apparatus and image processing method |
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| CN102082914A (en) * | 2009-11-30 | 2011-06-01 | 佳能株式会社 | Image processing apparatus and image processing method |
Non-Patent Citations (3)
| Title |
|---|
| 刘立欣等.《高速运动模糊图像的恢复》.《仪器仪表学报》.2011,第32卷(第6期),第251-254页. * |
| 曾志高等.《匀速直线运动模糊图像的恢复技术研究》.《陕西理工学院学报》.2006,第22卷(第2期),第36-38页. * |
| 黄学雨等.《匀速直线运动模糊图像的退化模型研究》.《科技广场》.2005,(第10期),第51-53页. * |
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