Multi-view-field modulation transfer function measurement method and system based on feature recognition

Abstract

The invention belongs to the technical field of optical system detection, and provides a multi-view-field modulation transfer function measurement method and system based on feature recognition, and the method comprises the steps: collecting an image containing a feature target, determining an imaging position of the feature target on a detector through a feature recognition algorithm, and building a mapping relation between the imaging position and a view field of a to-be-detected optical system, determining a cutting area, transmitting image data into a modulation transfer function calculation algorithm for calculation, obtaining a modulation transfer function calculation result at a specific field of view based on a single static picture, and obtaining a plurality of calculation results of modulation transfer functions at different fields of view by continuously changing the relative position between the optical system and the to-be-measured target. And based on the modulation transfer function at the known field of view, utilizing an interpolation algorithm to obtain modulation transfer function data at other specific fields of view. According to the invention, the field-of-view position of the target to be analyzed in the measurement optical system can be accurately determined, the system structure is greatly simplified, and the construction cost of the test system is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of optical system detection, and in particular relates to a multi-field modulation transfer function measurement method and system based on feature recognition. Background Art

[0002] The modulation transfer function is an important evaluation indicator of the resolution capability of an optical system. Currently, commonly used modulation transfer function evaluation methods include the knife-edge method, the slit method, and the contrast method. The modulation transfer function evaluation methods mentioned here all refer to methods that image specific characteristic targets at a specific test field angle and apply corresponding analysis algorithms to ultimately calculate the modulation transfer function of the optical system. For example, the characteristic target of the knife-edge method is the yin and yang bevel (or knife edge), and the core of the analysis algorithm is the derivative and Fourier transform of the edge spread function; the characteristic target of the slit method is the slit, and the core of the analysis algorithm is the direct Fourier transform of the slit line spread function. Based on the above algorithms, if the modulation transfer function of the entire optical system is to be determined in each field of view, it is necessary to precisely control the relative position relationship between the target and the optical system to be tested through a mechanical device, and to photograph the target and calculate the modulation transfer function in the field of view to be tested.

[0003] During the above-mentioned measurement process, in order to accurately control the positional relationship between the optical system under test and the target, a precise electrically controlled rotary displacement platform is required, which greatly increases the construction cost of the test system. Based on this, the present invention provides a multi-field modulation transfer function measurement method and system based on feature recognition. Summary of the Invention

[0004] The purpose of the present invention is to overcome the existing defects and provide a multi-field modulation transfer function measurement method and system based on feature recognition, which can eliminate the electronically controlled rotation displacement platform in the system, greatly simplify the system structure, and reduce the construction cost of the test system.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A multi-field modulation transfer function measurement method based on feature recognition includes:

[0007] Collect images containing characteristic targets, determine the imaging position of the characteristic targets on the detector through feature recognition algorithms, and establish a mapping relationship between the imaging position and the field of view of the optical system to be measured;

[0008] The size of the identified feature target is calculated to determine the cropping area, and the data area in the image that only contains the input features of the matching algorithm is passed to the modulation transfer function calculation algorithm for calculation;

[0009] Obtain the modulation transfer function calculation results at a specific field of view based on a single static image;

[0010] By continuously changing the relative position between the optical system and the target to be measured, the calculation results of the modulation transfer function at multiple different fields of view are obtained;

[0011] Based on the modulation transfer function at a known field of view, an interpolation algorithm is used to obtain modulation transfer function data at other specific fields of view.

[0012] Furthermore, the feature recognition algorithm adopts the Shi-Tomasi corner detection algorithm, and the evaluation function is R=min(λ1, λ2), where λ1 and λ2 are the eigenvalues ​​of the differential matrix of the image pixel value.

[0013] Furthermore, the characteristic target adopts a half-moon target. When calculating the characteristic target size, the coordinates of the two end points of the half-moon target edge are recorded as (x1, y1) and (x2, y2), respectively. The length L of the half-moon target is approximately the difference between the vertical coordinates of the two points:

[0014] L≈|y2-y1|

[0015] The characteristic center C of the half-moon target is located between the two endpoints, that is,

[0016]

[0017] According to the characteristic length L, the width W and height H of the characteristic area are selected, and the size S of the characteristic area is taken as:

[0018] S=(W,H)=(0.66×L,0.66×L);

[0019] The coordinates of the upper left corner of the feature area are The coordinates of the lower right corner are

[0020] Furthermore, obtaining a modulation transfer function calculation result at a specific field of view based on a single static image includes:

[0021] The feature area is subjected to light and dark edge image rotation, line edge search, edge fitting, and projection in sequence to obtain the edge spread function, which is then derived to obtain the line spread function. Finally, the modulation transfer function of the field of view at the center of the feature area is calculated using Fourier transform.

[0022] Furthermore, the calculation results of the modulation transfer function at multiple different fields of view are obtained by continuously changing the relative position between the optical system and the target to be measured, including:

[0023] Within the field of view, the position of the characteristic target relative to the optical system to be measured is randomly changed to obtain multiple imaging pictures of the characteristic target at different positions of the detector, and the modulation transfer function of the optical system with different fields of view is obtained.

[0024] Furthermore, in the modulation transfer function data at other specific fields of view obtained by using an interpolation algorithm based on the modulation transfer function at the known field of view, if the known field of view covers the entire field of view of the optical system to be measured, the modulation transfer function at any unknown field of view can be obtained by interpolating the modulation transfer functions of nearby fields of view.

[0025] Another object of the present invention is to provide a multi-field modulation transfer function measurement system based on feature recognition, comprising:

[0026] An image acquisition module, used for acquiring images containing characteristic targets;

[0027] The target feature recognition module is used to determine the imaging position of the characteristic target on the detector through a feature recognition algorithm, and to establish a mapping relationship between the imaging position and the field of view of the optical system to be measured;

[0028] The cutting size determination module is used to calculate the size of the identified feature target and determine the cutting area;

[0029] The cropping region function calculation module is used to pass the data area in the image that only contains the input features of the matching algorithm into the modulation transfer function calculation algorithm for calculation, and obtain the modulation transfer function calculation result at a specific field of view based on a single static image;

[0030] The different field of view function calculation module is used to obtain the calculation results of the modulation transfer function at multiple different fields of view by continuously changing the relative position between the optical system and the target to be measured.

[0031] In combination with the above technical solutions, the present invention has the following beneficial effects compared with the prior art:

[0032] The present invention combines a feature recognition algorithm to accurately determine the field of view position of a target to be analyzed in a measuring optical system; through multi-frame acquisition, the modulation transfer function of the optical system is obtained based on the analysis of the target to be measured at different fields of view; and using an interpolation algorithm, the modulation transfer function data of other unknown fields of view are interpolated and calculated based on the analysis results of the modulation transfer function at the acquired field of view. The present invention greatly simplifies the high-precision control and positioning system in a conventional multi-field of view modulation transfer function measurement system, greatly simplifies the system structure, and reduces the construction cost of the test system.

[0033] The present invention is based on a feature recognition algorithm, can match and identify features of a test target, and calculate the modulation transfer function; based on the matched and identified features, calculate the field of view corresponding to the features on the detector target surface; based on the matched and identified features, automatically define the analysis range to be intercepted from the detector image; and can calculate the modulation transfer function using a standard modulation transfer function algorithm for the intercepted analysis range; the standard modulation transfer function algorithm includes but is not limited to a slit-based line spread function calculation method, a knife-edge-based edge spread function calculation method, etc.

[0034] Traditional methods require precise motion control to accurately adjust the position between the light source and the measurement system to obtain the modulation transfer function (MTF) at a specific field of view of an optical system. This method uses simple manual control to collect the MTFs at multiple different fields of view and interpolate them to calculate the MTF for the field of view being measured. This significantly reduces the precision required for relative motion control and instead utilizes high-precision target feature recognition combined with an interpolation algorithm to replace the high-precision motion control system in traditional systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0036] Figure 1 is a flow chart of a multi-field modulation transfer function measurement method based on feature recognition provided by an embodiment of the present invention;

[0037] Figure 2 1 is a schematic diagram of a multi-field modulation transfer function measurement method based on feature recognition provided by an embodiment of the present invention;

[0038] Figure 3 Schematic diagram of a characteristic half-moon target provided by an embodiment of the present invention;

[0039] Figure 4 Schematic diagram of edge fitting of a feature region provided by an embodiment of the present invention;

[0040] Figure 5 Schematic diagram of an Variable Spread Function (ESF) and a Line Spread Function (LSF) provided by an embodiment of the present invention;

[0041] Figure 6 is a schematic diagram of a modulation transfer function (Edge-based SFR) provided by an embodiment of the present invention;

[0042] Figure 7 Schematic diagram of imaging of a half-moon target at different fields of view on a detection target surface provided by an embodiment of the present invention;

[0043] Figure 83 is a schematic diagram comparing the modulation transfer function calculated using the interpolation method for a specified field of view provided by an embodiment of the present invention and the measurement result of a commercial device. DETAILED DESCRIPTION

[0044] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0045] Example 1:

[0046] like Figure 1 FIG. 1 is an embodiment of a multi-field modulation transfer function measurement method and system based on feature recognition provided by the present invention, comprising:

[0047] S1: Acquire an image containing a characteristic target, determine the imaging position of the characteristic target on the detector through a feature recognition algorithm, and establish a mapping relationship between the imaging position and the field of view of the optical system to be measured;

[0048] S2: Calculate the size of the identified feature target, determine the cropping area, and pass the data area in the image that only contains the input features of the matching algorithm into the modulation transfer function calculation algorithm for calculation;

[0049] S3: Obtain the modulation transfer function calculation results at a specific field of view based on a single static image;

[0050] S4: By continuously changing the relative position between the optical system and the target to be measured, the calculation results of the modulation transfer function at multiple different fields of view are obtained;

[0051] S5: Based on the modulation transfer function at the known field of view, an interpolation algorithm is used to obtain modulation transfer function data at other specific fields of view.

[0052] Specifically, in the embodiment of the present invention, the characteristic target is a half-moon target (such as Figure 3 As shown), and based on the knife-edge method, the modulation transfer function is calculated by calculating the image of the half-moon target by the optical system to be tested. The reason why the embodiment uses the knife-edge method to measure the modulation transfer function is that the implementation process of the knife-edge method is described in great detail in the standard ISO12233, and there is an open source code implementation officially released by its establishing organization, which is convenient for the effect verification and result comparison of the present invention. The reason why the bevel required by the knife-edge method is provided by the half-moon target is that the target pattern has only two corners, and the feature recognition efficiency based on corners is very high, so it is only necessary to determine the two corners to accurately match the features.

[0053] 1. Feature Recognition: First, identify the two corners of the half-moon target. While there are many corner detection algorithms, the classic Shi-Tomasi algorithm is used here: the evaluation function R = min(λ1, λ2), where λ1 and λ2 are the eigenvalues ​​of the differential matrix of the pixel values ​​of the image to be identified. Since the half-moon target has only two corners, the two pixels with the largest evaluation function R are selected, representing the two endpoints of the half-moon target edge. Their coordinates are recorded as (x1, y1) and (x2, y2), respectively.

[0054] 2. Considering that the half-moon target is set approximately vertically (the reason for its slight tilt is explained in ISO12233, mainly to partially offset the spatial sampling discontinuity caused by the detector pixel size), its length is approximately equal to the difference between the vertical coordinates of the two points: L ≈ |y2-y1|.

[0055] 3. The center of the half-moon target feature is located between the two endpoints, that is,

[0056] 4. Based on the characteristic length L, a specific characteristic area width W and height H can be selected, requiring that the characteristic area does not contain other features except the hypotenuse. Here, the size of the characteristic area can be taken as: S = (W, H) = (0.66×L, 0.66×L).

[0057] 5. Furthermore, it can be confirmed that the coordinates of the upper left corner of the feature area are CS / 2, and the coordinates of the lower right corner are C+S / 2.

[0058] 6. Based on the above calculations, the edge feature area with the center at C and size S is subjected to the following steps according to ISO12233: light and dark edge image rotation, line edge search, edge fitting, projection to obtain edge spread function, derivation to obtain line spread function, and finally Fourier transform to calculate the modulation transfer function at the field of view C. Figure 4 、 Figure 5 and Figure 6 shown.

[0059] 7. Randomly change the position of the characteristic target relative to the optical system to be measured within the field of view (usually only pay attention to the horizontal and vertical position changes) to obtain multiple photos of the target imaging at different positions of the detector. Repeat steps 1-6 respectively to obtain the modulation transfer function of the optical system at different fields of view C. For example, in this embodiment, the blade edge is set vertically, then the horizontally changing fields of view (x1, 0), (x2, 0), (x3, 0), ... correspond to the changes in the modulation function in the meridian direction at different fields of view, and the corresponding vertically changing fields of view (0, y1), (0, y2), (0, y3), ... correspond to the changes in the sub-arc sagittal modulation function at different fields of view, such as Figure 7 shown.

[0060] If the data collected in step 7 is sufficiently dense and covers the entire field of view of the optical system under test, the modulation transfer function at any unknown field of view can be interpolated from the modulation transfer functions of nearby fields of view. Applicable interpolation algorithms include, but are not limited to, Lagrange interpolation, piecewise linear interpolation, or spline interpolation.

[0061] It should be understood that, although the various steps in the flow charts of the various embodiments of the present invention are shown in sequence according to the instructions of the arrows, these steps are not necessarily performed in sequence according to the order indicated by the arrows. Unless otherwise specified in the present invention, the execution of these steps is not strictly limited in order, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the various embodiments may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0062] Those skilled in the art will appreciate that all or part of the processes in the above-described embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-described methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0063] In the description of the present invention, unless otherwise specified, "plurality" means two or more; terms such as "upper," "lower," "left," "right," "inner," "outer," "front end," "rear end," "head," and "tail" indicate positions or relationships based on those shown in the accompanying drawings. These terms are intended solely to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or components referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, terms such as "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0064] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A multi-field modulation transfer function measurement method based on feature recognition, characterized in that: The method comprises: Collect images containing characteristic targets, determine the imaging position of the characteristic targets on the detector through feature recognition algorithms, and establish a mapping relationship between the imaging position and the field of view of the optical system to be measured; The size of the identified feature target is calculated to determine the cropping area, and the data area in the image that only contains the input features of the matching algorithm is passed to the modulation transfer function calculation algorithm for calculation; Obtain the modulation transfer function calculation results at a specific field of view based on a single static image; By continuously changing the relative position between the optical system and the target to be measured, the calculation results of the modulation transfer function at multiple different fields of view are obtained; Based on the modulation transfer function at a known field of view, an interpolation algorithm is used to obtain modulation transfer function data at other specific fields of view.

2. The multi-field modulation transfer function measurement method based on feature recognition according to claim 1, characterized in that: The feature recognition algorithm adopts the Shi-Tomasi corner detection algorithm, and the evaluation function is R=min(λ1, λ2), where λ1 and λ2 are the eigenvalues ​​of the differential matrix of the image pixel value.

3. The multi-field modulation transfer function measurement method based on feature recognition according to claim 1, characterized in that: The characteristic target adopts a half-moon target. When calculating the characteristic target size, the coordinates of the two end points of the half-moon target edge are recorded as (x1, y1) and (x2, y2) respectively. The length L of the half-moon target is approximately the difference between the vertical coordinates of the two points: L≈|y2-y1| The characteristic center C of the half-moon target is located between the two endpoints, that is, According to the characteristic length L, the width W and height H of the characteristic area are selected, and the size S of the characteristic area is taken as: S=(W,H)=(0.66×L,0.66×L); The coordinates of the upper left corner of the feature area are The coordinates of the lower right corner are 4. The multi-field modulation transfer function measurement method based on feature recognition according to claim 3, characterized in that: The method of obtaining a modulation transfer function calculation result at a specific field of view based on a single static image includes: The feature area is subjected to light and dark edge image rotation, line edge search, edge fitting, and projection in sequence to obtain the edge spread function, which is then derived to obtain the line spread function. Finally, the modulation transfer function of the field of view at the center of the feature area is calculated using Fourier transform.

5. The multi-field modulation transfer function measurement method based on feature recognition according to claim 1, characterized in that: The method of obtaining calculation results of the modulation transfer function at multiple different fields of view by continuously changing the relative position between the optical system and the target to be measured includes: Within the field of view, the position of the characteristic target relative to the optical system to be measured is randomly changed to obtain multiple imaging pictures of the characteristic target at different positions of the detector, and the modulation transfer function of the optical system with different fields of view is obtained.

6. The multi-field modulation transfer function measurement method based on feature recognition according to claim 1, characterized in that: In the modulation transfer function data of other specific fields of view obtained by using an interpolation algorithm based on the modulation transfer function at the known field of view, if the known field of view covers the entire field of view of the optical system to be measured, the modulation transfer function at any unknown field of view can be obtained by interpolating the modulation transfer functions of nearby fields of view.

7. A multi-field modulation transfer function measurement system based on feature recognition, characterized in that: The system comprises: An image acquisition module, used for acquiring images containing characteristic targets; The target feature recognition module is used to determine the imaging position of the characteristic target on the detector through a feature recognition algorithm, and to establish a mapping relationship between the imaging position and the field of view of the optical system to be measured; The cutting size determination module is used to calculate the size of the identified feature target and determine the cutting area; The cropping region function calculation module is used to pass the data area in the image that only contains the input features of the matching algorithm into the modulation transfer function calculation algorithm for calculation, and obtain the modulation transfer function calculation result at a specific field of view based on a single static image; The different field of view function calculation module is used to obtain the calculation results of the modulation transfer function at multiple different fields of view by continuously changing the relative position between the optical system and the target to be measured.

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