CN117876720A - Method for evaluating PSF image similarity - Google Patents
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Abstract
The invention relates to the technical field of photoelectric imaging, in particular to a method for evaluating PSF image similarity. Comprising the following steps: s1: constructing an image difference comparison analysis model; s2: acquiring a first PSF image and a second PSF image, inputting the first PSF image and the second PSF image into an image difference contrast analysis model for numerical fitting, and correspondingly acquiring radial numerical curves and energy concentration numerical curves of the first PSF image and the second PSF image; s3: calculating the maximum difference parameter values of the radial logarithmic value curve and the energy concentration degree curve of the first PSF image and the second PSF image; s4: and outputting a similarity comparison result of the first PSF image and the second PSF image by combining the maximum difference parameter values of the radial logarithmic value curve and the energy concentration degree curve of the first PSF image and the second PSF image. The method and the device can effectively evaluate the similarity of the two PSF images.
Description
Technical Field
The invention relates to the technical field of photoelectric imaging, in particular to a method for evaluating PSF image similarity.
Background
The point spread function is an important parameter for evaluating the imaging performance of the optical system, and reflects the energy spread condition of the image point of the ideal object point after the ideal object point passes through the optical system. For high image quality required optical systems, the aberrations should be corrected to diffraction limited levels. The image quality of the optical system is generally evaluated by using a point spread function obtained based on a diffraction theory, the optical system (such as a space telescope) is influenced by multiple factors such as environmental change, attitude adjustment, mechanical vibration, device aging and the like, the optical system can change the point spread function, and the image quality degradation change degree of the optical system can be evaluated by comparing the deformation of the point spread function image at different moments, however, no related method for evaluating the image quality degradation change degree of the optical system exists at present.
Disclosure of Invention
The invention provides a method for evaluating PSF image similarity, which can compare two PSF images through an image difference comparison analysis model to effectively evaluate the similarity of the two PSF images, further provide reference data for on-orbit fault diagnosis of a space telescope and facilitate finding key error factors restricting imaging definition.
The method for evaluating PSF image similarity provided by the invention specifically comprises the following steps:
s1: constructing an image difference comparison analysis model, wherein the image difference comparison analysis model comprises a radial numerical function and an energy concentration function:
（1）；
（2）；
（3）；
wherein,m (i, j) is the pixel value of the PSF image to be input in the ith row and the jth column as a radial value function, +.>For centroid position coordinates of PSF image to be input, < ->N is the number of sampling points of the PSF image to be input, r is the radius of a circular ring taking the centroid of the PSF image to be input as the center, x is the sampling distance along the radial direction taking the centroid of the PSF image to be input as the starting point, x epsilon [0, n-p]，r∈[0,n-p]And x and r are integers;
s2: acquiring a first PSF image and a second PSF image, inputting the first PSF image and the second PSF image into an image difference contrast analysis model for numerical fitting, and correspondingly acquiring radial numerical curves and energy concentration numerical curves of the first PSF image and the second PSF image;
s3: converting radial numerical curves of the first PSF image and the second PSF image into radial logarithmic numerical curves, and calculating the maximum difference parameter values of the radial logarithmic numerical curves and the energy concentration numerical curves of the first PSF image and the second PSF image by the following steps:
（4）；
wherein,as a radial logarithmic function;
s4: and outputting a similarity comparison result of the first PSF image and the second PSF image by combining the maximum difference parameter values of the radial logarithmic value curve and the energy concentration degree curve of the first PSF image and the second PSF image.
Preferably, if the maximum difference parameter values of the radial logarithmic value curves of the first PSF image and the second PSF image are both smaller than the first target similarity value, and the maximum difference parameter values of the energy concentration value curves of the first PSF image and the second PSF image are both smaller than the second target similarity value, the similarities of the first PSF image and the second PSF image satisfy the target similarity.
Preferably, the first target similarity value and the second target similarity value are both designed according to target similarity.
Preferably, the first PSF image and the second PSF image are acquired at different times of the same optical system.
Compared with the prior art, the invention has the following beneficial effects:
the invention establishes the image difference contrast analysis model, compares the two PSF images through the image difference contrast analysis model, effectively evaluates the similarity of the two PSF images, further provides reference data for on-orbit fault diagnosis of the space telescope, is convenient for searching key error factors restricting imaging definition, and can provide judgment standards of calculation accuracy for the fields of calculation, restoration, simulation and the like of the point spread function.
Drawings
Fig. 1 is a flowchart of a method for evaluating PSF image similarity provided according to an embodiment of the present invention;
fig. 2 is a first PSF image provided according to an embodiment of the present invention;
fig. 3 is a second PSF image provided according to an embodiment of the present invention;
FIG. 4 is a radial logarithmic magnitude plot provided in accordance with an embodiment of the invention;
FIG. 5 is a graph of energy concentration values provided in accordance with an embodiment of the present invention;
FIG. 6 is a graph showing a comparison of radial logarithmic magnitude curves of a first PSF image and a second PSF image provided in accordance with an embodiment of the present invention;
fig. 7 is a schematic diagram showing comparison of energy concentration value curves of a first PSF image and a second PSF image according to an embodiment of the present invention.
Detailed Description
Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the following description, like modules are denoted by like reference numerals. In the case of the same reference numerals, their names and functions are also the same. Therefore, a detailed description thereof will not be repeated.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not to be construed as limiting the invention.
The invention firstly establishes an image difference contrast analysis model, compares the similarity of two PSF images through the image difference contrast analysis model, if the similarity of the two PSF images meets the target similarity, the imaging performance of the optical system is stable, otherwise, the optical system is required to be adjusted to ensure that the stability of the optical system meets the target requirement,
fig. 1 shows a flow of a method for evaluating PSF image similarity provided according to an embodiment of the present invention; fig. 2 shows a first PSF image provided according to an embodiment of the present invention; fig. 3 shows a second PSF image provided according to an embodiment of the present invention; FIG. 4 illustrates a radial logarithmic magnitude curve provided in accordance with an embodiment of the invention; FIG. 5 illustrates an energy concentration degree value curve provided in accordance with an embodiment of the present invention; FIG. 6 shows a comparison of radial logarithmic magnitude curves of a first PSF image and a second PSF image provided in accordance with an embodiment of the present invention; fig. 7 shows a comparison of energy concentration value curves for a first PSF image and a second PSF image provided in accordance with an embodiment of the present invention.
As shown in fig. 1 to 7, the method for evaluating the PSF image similarity provided by the invention specifically comprises the following steps:
s1: constructing an image difference comparison analysis model, wherein the image difference comparison analysis model comprises a radial numerical function and an energy concentration function:
（1）；
（2）；
（3）；
wherein,m (i, j) is the pixel value of the PSF image to be input in the ith row and the jth column as a radial value function, +.>For centroid position coordinates of PSF image to be input, < ->N is the number of sampling points of the PSF image to be input, r is the radius of a circular ring taking the centroid of the PSF image to be input as the center, x is the sampling distance along the radial direction taking the centroid of the PSF image to be input as the starting point, x epsilon [0, n-p]，r∈[0,n-p]And x and r are integers.
S2: and acquiring a first PSF image and a second PSF image, inputting the first PSF image and the second PSF image into an image difference contrast analysis model for numerical fitting, and correspondingly acquiring radial numerical curves and energy concentration numerical curves of the first PSF image and the second PSF image.
The first PSF image and the second PSF image are acquired at different times of the same optical system.
S3: converting radial numerical curves of the first PSF image and the second PSF image into radial logarithmic numerical curves, and calculating the maximum difference parameter values of the radial logarithmic numerical curves and the energy concentration numerical curves of the first PSF image and the second PSF image by the following steps:
（4）；
wherein,as a radial logarithmic function.
The method for obtaining the maximum difference parameter value comprises the following steps: taking radial logarithmic value curves or energy concentration value curves of the first PSF image and the second PSF image, making a difference between values at the same sampling point on the two curves, and finally taking the maximum difference value as a maximum difference parameter value.
S4: and outputting a similarity comparison result of the first PSF image and the second PSF image by combining the maximum difference parameter values of the radial logarithmic value curve and the energy concentration degree curve of the first PSF image and the second PSF image.
And if the maximum difference parameter values of the radial logarithmic value curves of the first PSF image and the second PSF image are smaller than the first target similarity value, and the maximum difference parameter values of the energy concentration value curves of the first PSF image and the second PSF image are smaller than the second target similarity value, the similarity of the first PSF image and the second PSF image meets the target similarity.
The first target similarity value and the second target similarity value are designed according to the target similarity.
Assume that the requirements of imaging quality of the optical system set forth by the user are: the optical system is ensured to have stable imaging performance in the five-year working period, and then the target similarity is set to 98 percent according to the requirement of a user, and correspondingly, the first target similarity value is 0.003 and the first target similarity value is 0.005.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the technical solutions of the present disclosure are achieved, and are not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (4)
1. A method for evaluating PSF image similarity, comprising the steps of:
s1: constructing an image difference comparison analysis model, wherein the image difference comparison analysis model comprises a radial numerical function and an energy concentration function:
（1）；
（2）；
（3）；
wherein,m (i, j) is the pixel point value of the PSF image to be input in the ith row and the jth column as a radial value function,for centroid position coordinates of PSF image to be input, < ->N is the number of sampling points of the PSF image to be input, r is the radius of a circular ring taking the centroid of the PSF image to be input as the center, x is the sampling distance along the radial direction taking the centroid of the PSF image to be input as the starting point, x epsilon [0, n-p]，r∈[0,n-p]And x and r are integers;
s2: acquiring a first PSF image and a second PSF image, inputting the first PSF image and the second PSF image into the image difference contrast analysis model for numerical fitting, and correspondingly acquiring radial numerical curves and energy concentration numerical curves of the first PSF image and the second PSF image;
s3: converting radial numerical curves of the first PSF image and the second PSF image into radial logarithmic numerical curves, and calculating maximum difference parameter values of the radial logarithmic numerical curves and the energy concentration numerical curves of the first PSF image and the second PSF image by:
（4）；
wherein,as a radial logarithmic function;
s4: and outputting a similarity comparison result of the first PSF image and the second PSF image by combining the maximum difference parameter values of the radial logarithmic value curve and the energy concentration degree value curve of the first PSF image and the second PSF image.
2. The method for evaluating PSF image similarity of claim 1, wherein the similarity of the first PSF image and the second PSF image satisfies a target similarity if the maximum difference parameter value of the radial logarithmic value curves of the first PSF image and the second PSF image are both less than a first target similarity value and the maximum difference parameter value of the energy concentration value curves of the first PSF image and the second PSF image are both less than a second target similarity value.
3. The method for evaluating PSF image similarity according to claim 2, wherein the first target similarity value and the second target similarity value are each designed based on the target similarity.
4. The method for evaluating PSF image similarity according to claim 1, wherein the first PSF image and the second PSF image are acquired at different times of the same optical system.
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