CN109961410A - A kind of image pre-distortion method of optimization - Google Patents
A kind of image pre-distortion method of optimization Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
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Abstract
The invention discloses a kind of image pre-distortion method of optimization, the image pre-distortion method of the optimization includes: S1, and the non-linear relation of the original image of display and fault image is indicated using the polynomial transformation equation group between pixel coordinate；S2 is solved polynomial transformation equation group using least-squares algorithm and obtains transformation coefficient in the case that the change point number between original image and fault image is more than the number of unknown number in polynomial transformation equation group；S3 obtains fault image using Lanczos interpolation algorithm according to the transformation coefficient, to offset the fault image of display optical system.The problem of image pre-distortion method of the optimization overcomes the pattern distortion of display optical system in the prior art realizes the correction of fault image.
Description
Technical field
The present invention relates to image distortion corrections, and in particular, to a kind of image pre-distortion method of optimization.
Background technique
Image distortion correction is one of Recent study hot spot, is widely used in airphoto surveying, computer graphical
It learns, the research fields such as computer vision and the helmet are shown.Image distortion correction includes pattern distortion and image rectification, pattern distortion
Refer to the mapping from original image to fault image, image rectification refers to the mapping from fault image to original image.Image is abnormal
Becoming includes linear distortion and nonlinear distortion, the former includes perspective distortion etc., and the latter includes radial distortion and tangential distortion etc..
Important component of the optical system as Helmet Mounted Display, off-axis design is optical system major design mode,
And there are complicated aberration problems in off-axis optical system, not only include radial distortion and tangential distortion, further include arch distortion and
Trapezoidal distortion, but the design of Helmet Mounted Display must comprehensively consider with environmental factor, cannot sacrifice the operation of user in principle
Simplification and comfort exchange the improvement of individual indexs for.Method that there are two types of the bearing calibrations of the distortion as caused by optical system,
One is predistortion method, predistortion method is predistortion image needed for the normal original image of a width is transformed to optical system,
To offset pattern distortion caused by optical system, orthoscopic image is shown after projection；Another kind is posteriority correction method, is used
Polynomial curve is both horizontally and vertically removing the cable for being fitted each distortion, then acquires the correction function of anti-change, uses
This correction function, which carries out processing to fault image, can be obtained correcting distorted image.
Summary of the invention
The object of the present invention is to provide a kind of image pre-distortion method of optimization, the image pre-distortion method of the optimization overcomes
The problem of pattern distortion of display optical system in the prior art, realize the correction of fault image.
To achieve the goals above, the present invention provides a kind of image pre-distortion method of optimization, the image of the optimization is pre-
Distortion method includes:
The non-linear relation of the original image of display and fault image is utilized the polynomial transformation between pixel coordinate by S1
Equation group indicates；
S2, the change point number between original image and fault image is more than unknown number in polynomial transformation equation group
In the case where number, polynomial transformation equation group is solved using least-squares algorithm and obtains transformation coefficient；
S3 obtains fault image using Lanczos interpolation algorithm, to offset display light according to the transformation coefficient
The fault image of system.
Preferably, in S1, by the non-linear relation of the original image of display and fault image using between pixel coordinate
Polynomial transformation equation group include: come the method indicated
U', v' are the coordinate points of fault image, and x, y are the coordinate points of original image, and N is the number of specialized polynimial, aij
And bijFor the transformation coefficient of specialized polynimial.
Preferably, in S2, polynomial transformation equation group is solved using least-squares algorithm and obtains the side of transformation coefficient
Method includes:
The error sum of squares after fitting is made to reach minimum using following multinomials:
Wherein, εx、εyIt is error sum of squares, u', v' are the coordinate points of fault image, and x, y are the coordinate points of original image, N
For polynomial number, L is the number at control point, aijAnd bijFor the transformation coefficient of specialized polynimial.
Preferably, in S2, polynomial transformation equation group is solved using least-squares algorithm and obtains transformation coefficient, is passed through
Following formula makes maximum relative error value less than 0.5%:
Wherein, EmaxIt is maximum relative error value, rmodelIt is the coordinate data of fault image, rrealIt is the seat of original image
Mark data.
According to the above technical scheme, the present invention is based on the pre-distortion methods of least-squares algorithm and Lanczos interpolation algorithm
Distortion effect is generated to normal picture, then using obtained fault image as the input signal of Helmet Mounted Display, to offset head
Optical system produces in distortion brought by optical system in helmet display, the i.e. distortion of pre-distortion method generation and Helmet Mounted Display
Raw distortion is cancelled out each other, that is, being presented to observer is normal original image, which has universal adaptivity, only
The corresponding data relationship for wanting to obtain two spaces, can calculate corresponding transition matrix, can be to all input pictures
Distortion effect is generated, predistortion effect is reached.
Other features and advantages of the present invention will the following detailed description will be given in the detailed implementation section.
Detailed description of the invention
The drawings are intended to provide a further understanding of the invention, and constitutes part of specification, with following tool
Body embodiment is used to explain the present invention together, but is not construed as limiting the invention.In the accompanying drawings:
Fig. 1 a is the chessboard trrellis diagram for illustrating the original image of simulated experiment of the invention；
Fig. 1 b is the grid chart for illustrating the original image of simulated experiment of the invention；
Fig. 1 c is the U.S. army's standard resolution chart figure for illustrating the original image of simulated experiment of the invention；
Fig. 2 a is the chessboard trrellis diagram for illustrating the fault image of simulated experiment of the invention；
Fig. 2 b is the grid chart for illustrating the fault image of simulated experiment of the invention；
Fig. 2 c is the U.S. army's standard resolution chart figure for illustrating the fault image of simulated experiment of the invention.
Specific embodiment
Below in conjunction with attached drawing, detailed description of the preferred embodiments.It should be understood that this place is retouched
The specific embodiment stated is merely to illustrate and explain the present invention, and is not intended to restrict the invention.
The present invention provides a kind of image pre-distortion method of optimization, and the image pre-distortion method of the optimization includes:
The non-linear relation of the original image of display and fault image is utilized the polynomial transformation between pixel coordinate by S1
Equation group indicates；
S2, the change point number between original image and fault image is more than unknown number in polynomial transformation equation group
In the case where number, polynomial transformation equation group is solved using least-squares algorithm and obtains transformation coefficient；
S3 obtains fault image using Lanczos interpolation algorithm, to offset display light according to the transformation coefficient
The fault image of system.
According to the above technical scheme, the present invention is based on the pre-distortion methods of least-squares algorithm and Lanczos interpolation algorithm
Distortion effect is generated to normal picture, then using obtained fault image as the input signal of Helmet Mounted Display, to offset head
Optical system produces in distortion brought by optical system in helmet display, the i.e. distortion of pre-distortion method generation and Helmet Mounted Display
Raw distortion is cancelled out each other, that is, being presented to observer is normal original image, which has universal adaptivity, only
The corresponding data relationship for wanting to obtain two spaces, can calculate corresponding transition matrix, can be to all input pictures
Distortion effect is generated, predistortion effect is reached.
In a kind of specific embodiment of the invention, in S1, by the non-of the original image of display and fault image
Linear relationship includes: come the method indicated using the polynomial transformation equation group between pixel coordinate
U', v' are the coordinate points of fault image, and x, y are the coordinate points of original image, and N is the number of specialized polynimial, aij
And bijFor the transformation coefficient of specialized polynimial.
In a kind of specific embodiment of the invention, if corresponding points number between original image and fault image with
The number of unknown number is identical in equation group, then can be with direct solution equation group, but in order to obtain higher precision, original graph
Change point number between picture and fault image is always more than the number of unknown number in equation group, and the equation group obtained in this way is super
Determine equation group.It is assumed that solving over-determined systems using least-squares algorithm, i.e., after fitting of a polynomial for L control point
Error sum of squares reaches minimum.
In S2, the method that polynomial transformation equation group obtains transformation coefficient is solved using least-squares algorithm be can wrap
It includes:
The error sum of squares after fitting is made to reach minimum using following multinomials:
Wherein, εx、εyIt is error sum of squares, u', v' are the coordinate points of fault image, and x, y are the coordinate points of original image, N
For polynomial number, L is the number at control point, aijAnd bijFor the transformation coefficient of specialized polynimial.
In a kind of specific embodiment of the invention, in S2, polynomial transformation is solved using least-squares algorithm
Equation group obtains transformation coefficient, makes maximum relative error value less than 0.5% by following formula:
Wherein, EmaxIt is maximum relative error value, rmodelIt is the coordinate data of fault image, rrealIt is the seat of original image
Mark data.
Correcting Accuracy is related with degree of polynomial N, and degree of polynomial N and correction accuracy are proportional.Minimum two
Multiplication algorithm can provide an optimal approximate solution under the premise of polynomial fitting number is not very high, by the related money of investigation
Material and simulated experiment, this patent solve the transformation coefficient between original image and fault image using cubic polynomial, simultaneously
Calculate maximum relative error value.
This patent software platform uses Qt+OpenCV as experiment programming software, realize based on least-squares algorithm and
The pre-distortion method of Lanczos interpolation algorithm, hardware platform uses tetra- core of Intel Core i3-3240CPU@3.40GHz, interior
4G is saved as, operating system is 32-bit Windows 7.Using use chessboard trrellis diagram, grid chart U.S. army standard resolution chart figure as mould
Draft experiment figure, resolution ratio are all 1400*1050, such as Fig. 1 a, shown in Fig. 1 b and Fig. 1 c.
Predistortion software is inputted there are two part, first is that the mapping parameters of optical system, second is that simulated experiment figure, predistortion
Software calculates transition matrix according to the mapping parameters of optical system first, is then introduced into simulated experiment figure, is asked using transition matrix
Fault image is obtained, finally using obtained fault image as the input signal of Helmet Mounted Display, such as Fig. 2 a, Fig. 2 b and Fig. 2 c institute
Show.
It is described the prefered embodiments of the present invention in detail above in conjunction with attached drawing, still, the present invention is not limited to above-mentioned realities
The detail in mode is applied, within the scope of the technical concept of the present invention, a variety of letters can be carried out to technical solution of the present invention
Monotropic type, these simple variants all belong to the scope of protection of the present invention.
It is further to note that specific technical features described in the above specific embodiments, in not lance
In the case where shield, can be combined in any appropriate way, in order to avoid unnecessary repetition, the present invention to it is various can
No further explanation will be given for the combination of energy.
In addition, various embodiments of the present invention can be combined randomly, as long as it is without prejudice to originally
The thought of invention, it should also be regarded as the disclosure of the present invention.
Claims (4)
1. a kind of image pre-distortion method of optimization, which is characterized in that the image pre-distortion method of the optimization includes:
The non-linear relation of the original image of display and fault image is utilized the polynomial transformation equation between pixel coordinate by S1
Group indicates；
S2, the change point number between original image and fault image are more than the number of unknown number in polynomial transformation equation group
In the case where, polynomial transformation equation group is solved using least-squares algorithm obtains transformation coefficient；
S3 obtains fault image using Lanczos interpolation algorithm according to the transformation coefficient, to offset display optical system
The fault image of system.
2. the image pre-distortion method of optimization according to claim 1, which is characterized in that in S1, by the original of display
The non-linear relation of beginning image and fault image includes: come the method indicated using the polynomial transformation equation group between pixel coordinate
U', v' are the coordinate points of fault image, and x, y are the coordinate points of original image, and N is the number of specialized polynimial, aijAnd bij
For the transformation coefficient of specialized polynimial.
3. the image pre-distortion method of optimization according to claim 1, which is characterized in that in S2, use least square
Algorithm includes: to solve the method that polynomial transformation equation group obtains transformation coefficient
The error sum of squares after fitting is made to reach minimum using following multinomials:
Wherein, εx、εyIt is error sum of squares, u', v' are the coordinate points of fault image, and x, y are the coordinate points of original image, and N is more
The number of item formula, L are the number at control point, aijAnd bijFor the transformation coefficient of specialized polynimial.
4. the image pre-distortion method of optimization according to claim 1, which is characterized in that in S2, use least square
Algorithm obtains transformation coefficient to solve polynomial transformation equation group, by following formula maximum relative error value is less than
0.5%:
Wherein, EmaxIt is maximum relative error value, rmodelIt is the coordinate data of fault image, rrealIt is the number of coordinates of original image
According to.
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