TWI411815B - A design method and system for computational optical imaging - Google Patents

Abstract

The invention discloses a digital optical imaging system, comprising at least an optical module and an image recovery module, and the design method comprises a step of setting re-set target, a design step of optical module, and a design step of image recovery module, wherein optimized criterion is carried out by using the similarity and fuzzy minimum value of point spread function produced by the optical module and the similarity and fuzzy minimum value of point spread function outputted by the image recovery module, and the design step of optical module and the design step of image recovery module are carried out individually or sequentially, and simultaneously the design of the optical imaging system is carried out by means of a computer software product.

Description

Digital optical imaging design method and system

The present invention relates to a digital optical imaging design method and system, and more particularly to a system and method for individually designing and modularizing an optical module and an image processing module.

Although it is similar to traditional industries in the optical industry, it has a high gross profit margin; in addition, the optical industry must rely heavily on the experience of technicians in the manufacturing process and parameter control to make the optical products perfect. Therefore, optical products usually have a longer development period than information products.

At present, a hybrid digital optical imaging system 1 using an integrated optical module and an image restoration module, as shown in FIG. 1, is a flow chart showing the design of a conventional hybrid digital optical imaging system. The design method uses a pre-stage optical mode. The group 1A and the post-image restoration module 1B must be designed in sequence, that is, the post-image restoration module 1B must generate a point spread function (PSF) P after the pre-stage optical module 1A. Then, according to the point spread function PSF generated by the front and the optical module, the output image matrix IB is designed. If it is not optimized by the designer standard, then it is returned to the front optical module 1A to repeat the above. The steps are designed.

The post-image restoration module (such as the reduction filter) must be designed according to the results of the pre-stage optical module (such as the lens architecture), that is, to design the post-image restoration module, the pre-stage optical module must be completed. Design Count, otherwise the post-image restoration module has no basis and no comparison.

For such a structure, reference is made to U.S. Patent No. US20050197809, which discloses a system and method for optimizing optical and digital image design, which is used to determine the rules of the digital optical imaging system. Estimated by value. In general, this final value is the mean square error (MSE) of the reference image and the restored image.

In addition, in US Patent No. US20070239417, a method for designing a camera includes a plurality of objective lens assemblies for forming a blurred image on an electronic image sensor, and for reconstructing the blurred image ( De-blurred image) of a virtual lens. The function of the virtual lens is the same as that of the digital filter (ie, the aforementioned reduction filter). This method includes defining the design of the objective lens assembly and determining the coefficients of the digital filter. An input image is sequentially processed through the design of the objective lens assembly and the determination of the digital filter coefficients to generate an output image of the camera simulation operation. The display of this output image is estimated by the camera designer. The design constraints of the real objective lens assembly are relaxed by the use of virtual lenses, as if the optical design system had an additional optical component incorporated into the design for the purpose of aberration correction.

The above-mentioned techniques may cause the following problems or difficulties: 1. The optical module and the image processing module of the imaging can only be integrated and designed; 2. There is no particularly effective and rapid design for the pre-stage optical module. Method; 3. Image calculation is time consuming, and the speed of optimization is extremely slow; 4. It is difficult to achieve objective image evaluation; 5. The scores of the pre-stage optical module and the post-stage image restoration module are unknown.

Therefore, how to design the optical module and the image processing module separately to reduce the time of image calculation and improve the speed of optimization is an urgent task in designing an image processing system.

In view of the above, the present invention provides a method and system for designing digital optical imaging by separately modularizing optical modules and digital image modules and optimizing them to restore optimal digital images.

An object of the present invention is to provide a digital optical imaging design method comprising: a desired target setting step; an optical module design step; and a digital image restoration module design step; wherein the optical module design step and The digital image restoration module design steps are performed synchronously or sequentially.

In addition, another object of the present invention is to provide a digital optical imaging system comprising: an optical module having an optical threshold and an optical point spread function, and an image restoration module having an image reduction threshold and An image restoration point spread function; wherein the optical module is optimized by comparing the similarity of the optical point spread function with the optical threshold value, and the image restoration module is used to restore the image point The similarity of the diffusion function is compared to the image reduction threshold for optimization.

Preferably, the optical module can be optimized by comparing the fuzzy minimum value of the optical point spread function with the optical threshold value; and the image restoration module can further restore the point spread function by using the image. Fuzzy minimum The image restores a comparison of threshold values for optimization.

Therefore, according to the above structure and method, the optical module and the digital image module can be separately and individually designed, and then matched with each other to achieve individual optimization and modularized individual matching, thereby saving cost.

The detailed features and advantages of the present invention are described in detail in the embodiments of the present invention, which are to be understood by those of ordinary skill in the art. The objects and advantages associated with the present invention can be readily understood by those skilled in the art.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The preferred embodiments of the present invention will be described in detail below with reference to the drawings.

Please refer to FIG. 2, which is a block diagram showing the digital optical imaging of the present invention. The digital optical imaging system 2 of the present embodiment includes an optical module 2A (for example, a lens group structure) and an image restoration module 2B (for example, The reduction filter); the optical module 2A and the image restoration module 2B can operate individually or simultaneously.

The optical module 2A can generate an optical point spread function (PSF) PO, and the image restoration module can output an image reductible point spread function PI; and by comparing the similarity of the point spread function, or optical The optical module 2A and the digital image module 2B can be individually designed by the similarity of the optical transfer function (OTF). From a mathematical point of view, the optical transfer function is a Fourier transform of the point spread function. Therefore, the optical transfer function is equivalent to a point spread function. The comparison method of the similarity of the point spread function by the analyzer An includes Fidelity, Correlation and Hilbert Space Projected Angle. The equations are as follows: degree:

Correlation:

Hibbert space projection angle:

Wherein, the PSF1 optical module 2A or the image restoration module 2B previously generates or outputs a point spread function, and the PSF2 optical module 2A or the image restoration module 2B generates or outputs a point spread function next time; Detailed design steps will be detailed later.

Referring to Figure 3, there is shown a block diagram of a first embodiment of the present invention. The system 3 of the present embodiment includes an optical module 3A and an image restoration module 3B, and the embodiment is an optical module 3A with an image restoration module. 3B is designed at the same time, and the design steps include: step SA2: designing an optical module 3A; and step SA3: designing a digital image module 3B.

Before designing the optical module and designing the digital image module, the designer can first set a desired target (step SA1), which includes a predetermined point spread function PD and a threshold value T for which image optimization is desired.

In step SA2, the method further includes: step SB1: generating an optical point spread function PO from the optical module 3A; step SB2: comparing the similarity between the optical point spread function PO and the predetermined point spread function PD; step SB3: when the optical point spread function When the similarity between PO and the predetermined point spread function PD is equal to or greater than the critical value T, the parameters of the optical module are output; and step SB4: when the similarity between the optical point spread function PO and the predetermined point spread function PD is less than the critical value T, The optical module is optimized and step SB1 is repeated.

Step SA3 further includes: step SC1: generating an image restoration point spread function PI from the image restoration module 3B; step SC2: comparing the similarity between the image restoration point spread function PI and the predetermined point spread function PD; step SC3: when the image When the similarity between the reduction point spread function PI and the predetermined point spread function PD is equal to or greater than the threshold value T, the parameters of the digital image restoration module are output; And step SC4: when the similarity between the image restoration point spread function PI and the predetermined point spread function PD is less than the threshold value T, the digital image restoration module is optimized and the step SC1 is repeated.

In step SB2, the manner of comparing similarities includes the aforementioned fidelity, correlation, and Hibbert space projection angle; and in addition to comparing similarities, it also includes blur minimization of comparing optical point spread functions (blur minimization) MIO; and in step SC2, further includes comparing the fuzzy minimum MID of the image restoration point spread function.

Furthermore, the parameter outputted in step SB3 includes a refractive index, a curvature, a thickness value, and an aspherical coefficient, or a combination thereof; and the parameter outputted in step SC3 includes a control parameter and a regularization parameter. (regularization parameter) and signal to noise ratio parameter.

After the steps SA2 and SA3 are individually completed, a step SA4 is further included, that is, an optical image and a digital restored image are output.

Referring to Figure 4, there is shown a block diagram of a second embodiment of the present invention. This embodiment illustrates that the optical module 3A is individually and individually optimized; the steps include: step SF1: generating at least two optical point spread functions PO1, PO2 from the optical module 3A; and step SF2: by analyzing At least two optical point spread functions PO1, PO2 generated by the optical module 3A are used to optimize the optical module 3A.

In step SF1, different object distances or different positions may be utilized to generate different optical point spread functions.

Step SF2 uses whether the similarity of the comparative optical point spread function is greater than or equal to the critical value T (step SF3). If it is greater than or equal to a critical value T, the optical result is output, such as an optical parameter (step SF4), if it is less than the critical value. For the value T, step SF1 is repeated (step SF5).

Also in step SF2, the method of analysis includes comparing the fuzzy minimum of the optical point spread function.

Referring to Figure 5, there is shown a block diagram of a third embodiment of the present invention. In this embodiment, the image restoration module 3B is separately and individually optimized; the steps include: step SG1: generating at least two image restoration point spread functions PI1, PI2 from the image restoration module 3B; and step SG2: The image restoration module 3B is optimized by analyzing at least two image restoration point spread functions PI1, PI2 generated by the image restoration module 3B.

In step SG1, different noises can be utilized to generate different image reduction point spread functions.

Step SG2 is to use the comparison image to restore whether the similarity of the point spread function is greater than or equal to the threshold value T (step SG3). If it is greater than or equal to a threshold value T, the image restoration result is output, for example, the control parameter value (step SG4), if If it is smaller than the critical value T, the step SG1 is repeated (step SG5).

Moreover, in step SG2, the fuzzy minimum value of the image reduction point spread function is further included.

Referring to Figure 6, there is shown a block diagram of a fourth embodiment of the present invention. In this embodiment, the optical module 3A is matched with the image restoration module 3B after being individually and individually optimized. The steps include: Step SD1: providing a fixed image by the digital image restoration module 3B. Image restoration point spread function PIF; step SD2: generating an optical point spread function PO by the optical module 3A; step SD3: comparing the similarity between the optical point spread function PO and the fixed image reduction point spread function PIF; step SD4: when optical The parameter of the output optical module 3A when the similarity between the point spread function PO and the fixed image reduction point spread function PIF is equal to or greater than a critical value T; and step SD5: when the optical point spread function PO and the fixed image restore point spread When the similarity of the function PIF is less than the critical value T, the optical module 3A is optimized and the step SD2 is repeated.

In step SD3, in addition to comparing the similarity between the optical point spread function and the fixed image reduction point spread function, the fuzzy minimum value of the comparison optical point spread function and the fixed image reduction point spread function is further included.

The parameters output in step SD4 include a refractive index, a curvature, a thickness value, and an aspheric coefficient, or a combination thereof.

Referring to Fig. 7, there is shown a block diagram of a fifth embodiment of the present invention. In this embodiment, the image restoration module 3B is matched with the optical module 3A after being individually and individually optimized. The steps include: Step SE1: providing a fixed optical point by the optical module 3A. Diffusion function POF; Step SE2: an image restoration point spread function PI is generated by the digital image restoration module 3B; step SE3: comparing the similarity between the fixed optical point spread function POF and the image reduction point spread function PI; step SE4: when the fixed optical point spreads When the similarity between the function POF and the image restoration point spread function PI is equal to or greater than a critical value T, the parameters of the digital image restoration module 3B are output; and step SE5: when the fixed optical point spread function POF and the image reduction point spread function PI When the similarity is less than the critical value, the digital image restoration module 3B is optimized and the step SE2 is repeated.

In step SE3, in addition to comparing the similarity between the image reduction point spread function and the fixed optical point spread function, the fuzzy minimum value of the comparison image reduction point spread function and the fixed optical point spread function is further included.

The parameters output in step SE4 include a control parameter, a regularization parameter, and a signal noise ratio parameter, or a combination thereof.

Referring to Figure 8, there is shown a block diagram of a sixth embodiment of the present invention. In the present embodiment, since the optical module and the digital image module are modularized, the modules can be interchanged. The embodiment includes a first optical module MO1 and a first image restoration module MI1, and a second optical module MO2 and a second image restoration module MI2. The steps of this embodiment include: Step SK1: Select one of the optical modules MO1 or MO2 and obtain at least one optical of the selected optical module MO1 or MO2 a point spread function PO; step SK2: selecting one of the image restoration modules MI1 or MI2, and obtaining at least one image restoration point spread function PI of the selected image restoration module MI1 or MI2; and step SK3: separately or according to Sequentially analyzing the similarity of the optical point spread function PO of the selected optical module MO1 or MO2 and the image restoration point spread function PI of the selected image restoration module MI1 or MI2, and according to a predetermined threshold T, The optical module MO1 or MO1 and the image restoration module MI1 or MI2 form a digital optical imaging system IS.

In detail, a first optical point spread function is generated from the first optical module, a second optical point spread function is generated from the second optical module, and a first image restore point diffusion is output from the first image restoration module. a function, outputting a second image restore point spread function from the second image restoration module; comparing the first optical point spread function with the first image restore point spread function, and comparing the second optical point spread function with the second The similarity of the image reduction point spread function.

Therefore, when the similarity between the two reaches a predetermined threshold, it means that the optical properties of the first optical module and the second optical module are very close, that is, the first optical module and the second optical module are Can be replaced with each other, so that the purpose of modularized individual matching can be achieved. Furthermore, the present invention can be replaced by an optical module of the same specification alone, without replacing the entire system, in order to save costs.

Please refer to FIG. 9, which is a block diagram showing the application of the present invention to a software product. The software product 4 presented by the present invention includes: Step SH1: modularizing a digital imaging system comprising a plurality of optical variable definitions; step SH2: optimizing optical performance of the digital optical system by similarity of a point spread function; and step SH3: optimizing and repeating steps SH1 to correct optical variables.

In step SH1, the digital imaging system is modularized into an optical module and an image restoration module; wherein the optical variable includes an optical module variable and an image restoration module variable, and the optical module variable includes The refractive index of an optical component, the size of an optical component, the thickness, wavelength, and Abbe number of an optical component; and the image reduction variables include filter parameters, regularization parameters, and signal noise ratio parameters. Wait.

Please refer to FIG. 10 and FIG. 11 simultaneously, which are graphs showing the results of the Doublet software simulation before and after the optimization of the present invention. And Fig. 12 is a list showing a list of simulation variables of the present invention. Taking Doublet's imaging system as an example, the design goal is that the degree of similarity of the point spread function in the focal depth of 0.2 mm before and after the focal plane is expected to be greater than 0.8 with respect to the conventional optical system.

Therefore, with the above structure and method, a modular digital imaging system can be realized, that is, divided into an optical module and an image restoration module, and the similarity of the point spread function and the fuzzy minimum value are obtained to obtain objectivity. The optical module and/or the image restoration module can be optimized individually and individually, and then matched to each other to reduce the time of image calculation; and the optical modules that achieve the same performance can be replaced with each other. There is no need to replace the entire system to save costs.

In summary, the present invention is only described as a preferred embodiment or embodiment of the technical means for solving the problem, and is not intended to limit the scope of the invention. That is, the equivalent changes and modifications made in accordance with the scope of the patent application of the present invention or the scope of the invention are covered by the scope of the invention.

1‧‧‧Hybrid digital optical imaging system

1A‧‧‧Pre-stage optical module

1B‧‧‧After image restoration module

2‧‧‧Digital optical imaging system

2A‧‧‧Optical module

2B‧‧‧Image Restoration Module

3‧‧‧Digital optical imaging system

3A‧‧‧Optical Module

3B‧‧‧Image Restoration Module

4‧‧‧Software products

IS‧‧‧Digital Optical Imaging System

MI1‧‧‧First Image Restore Module

MI2‧‧‧Second image restoration module

Fuzzy minimum of MIO‧‧‧ optical point spread function

Fuzzy minimum of MID‧‧‧ image reduction point spread function

MO1‧‧‧ first optical module

MO2‧‧‧Second optical module

PD‧‧‧predetermined point spread function

PI‧‧‧ image reduction point spread function

PI1‧‧‧ image reduction point spread function

PI2‧‧‧ image reduction point spread function

PIF‧‧‧Fixed image reduction point spread function

PO‧‧‧ optical point spread function

PO1‧‧‧ optical point spread function

PO2‧‧‧ optical point spread function

POF‧‧‧Fixed optical point spread function

PSF1‧‧‧ Point spread function previously generated or output

PSF2‧‧‧Point spread function generated or output next time

T‧‧‧ threshold

Step SA1‧‧‧Set a desired goal

Step SA2‧‧‧ Design an optical module

Step SA3‧‧‧ Design a digital image module

Step SA4‧‧‧ output an optical image and a digital restored image

Step SB1‧‧‧ Generate an optical point spread function from the optical module

Step SB2‧‧‧Comparison of the similarity between the optical point spread function and the predetermined point spread function

Step SB3‧‧‧ When the similarity between the optical point spread function and the predetermined point spread function is equal to or greater than the critical value, the parameters of the output optical module

Step SB4‧‧‧ When the similarity between the optical point spread function and the predetermined point spread function is less than the critical value, the optical module is optimized and the steps are repeated

Step SC1‧‧‧ Generate an image restoration point spread function from the image restoration module

Step SC2‧‧‧Comparing the similarity between the image reduction point spread function and the predetermined point spread function

Step SC3‧‧‧ When the similarity between the image reduction point spread function and the predetermined point spread function is equal to or greater than the critical value, the parameters of the digital image restoration module are output

Step SC4‧‧‧ When the similarity between the image reduction point spread function and the predetermined point spread function is less than the critical value, the digital image is restored Group optimization and repeat step SC2

Step SD1‧‧‧ provides a fixed image restoration point spread function by the digital image restoration module

Step SD2‧‧‧ generates an optical point spread function from the optical module

Step SD3‧‧‧Comparison of the similarity between the optical point spread function and the fixed image reduction point spread function

Step SD4‧‧‧ When the similarity between the optical point spread function and the fixed image reduction point spread function is equal to or greater than a critical value, the parameters of the output optical module

Step SD5‧‧‧ When the similarity between the optical point spread function and the fixed image reduction point spread function is less than the critical value, the optical module is optimized and the step SD2 is repeated.

Step SE1‧‧‧ provides a fixed optical point spread function by the optical module;

Step SE2‧‧‧ Generate an image restoration point spread function by the digital image restoration module

Step SE3‧‧‧Comparison of the similarity between fixed optical point spread function and image reduction point spread function

Step SE4‧‧‧ When the similarity between the fixed optical point spread function and the image reduction point spread function is equal to or greater than a critical value, the parameters of the digital image restoration module are output.

Step SE5‧‧‧ When the similarity between the fixed optical point spread function and the image reduction point spread function is less than the critical value, the digital image restoration module is optimized and the step SE2 is repeated.

Step SF1‧‧‧ Generate at least two optical point spread functions from the optical module

Step SF2‧‧‧ at least two optical point spreads generated by analyzing the optical module Dispersion function to optimize optical modules

Step SF3‧‧‧Compared whether the similarity of the optical point spread function is greater than or equal to the critical value T

Step SF4‧‧‧ If it is greater than or equal to a critical value T, the output optical result, such as optical parameters

Step SF5‧‧‧ If it is less than the critical value T, repeat step SF1

Step SG1‧‧‧ Generate at least two image restoration point spread functions from the image restoration module

Step SG2‧‧‧ Optimize the image restoration module by analyzing at least two image restoration point spread functions generated by the image restoration module

Step SG3‧‧‧Compared whether the similarity of the image reduction point spread function is greater than or equal to the critical value T

Step SG4‧‧‧ If it is greater than or equal to a critical value T, output image restoration results, such as control parameter values

Step SG5‧‧‧ If it is less than the critical value T, repeat step SG1

Step SH1‧‧‧Modular digital imaging system with several optical variable definitions

Step SH2‧‧‧ Optimize the optical performance of the digital optical system by the similarity of the point spread function

Step SH3‧‧‧ to optimize the optical variable by optimizing and repeating step SH1

1 is a flow chart showing the design of a conventional hybrid digital optical imaging system; FIG. 2 is a block diagram showing the digital optical imaging of the present invention; FIG. 3 is a block diagram showing a first embodiment of the present invention; FIG. 5 is a block diagram showing a third embodiment of the present invention; FIG. 6 is a block diagram showing a fourth embodiment of the present invention; and FIG. 7 is a block diagram showing a fifth embodiment of the present invention; Figure 8 is a block diagram showing a sixth embodiment of the present invention; Figure 9 is a block diagram showing the application of the present invention to a software product; Figure 10 is a graph showing a simulation result of the Doublet software before optimization; Figure 11 A graph showing the results of the Doublet software simulation after optimization; and FIG. 12 is a list of the simulation variables of the present invention.

3‧‧‧Digital optical imaging system

3A‧‧‧Optical Module

3B‧‧‧Image Restoration Module

PD‧‧‧predetermined point spread function

PI‧‧‧ image reduction point spread function

PO‧‧‧ optical point spread function

T‧‧‧ threshold

Step SA1‧‧‧Set a desired goal

Step SA2‧‧‧ Design an optical module

Step SA3‧‧‧ Design a digital image module

Step SA4‧‧‧ output an optical image and a digital restored image

Step SB1‧‧‧ Generate an optical point spread function from the optical module

Step SB2‧‧‧Comparison of the similarity between the optical point spread function and the predetermined point spread function

Step SB3‧‧‧ When the similarity between the optical point spread function and the predetermined point spread function is equal to or greater than the critical value, the parameters of the output optical module

Step SB4‧‧‧ When the similarity between the optical point spread function and the predetermined point spread function is less than the critical value, the optical module is optimized and the steps are repeated

Step SC1‧‧‧ Generate an image restoration point spread function from the image restoration module

Step SC2‧‧‧Compared image reduction point spread function with predetermined point spread function Similarity

Step SC3‧‧‧ When the similarity between the image reduction point spread function and the predetermined point spread function is equal to or greater than the critical value, the parameters of the digital image restoration module are output

Step SC4‧‧‧ When the similarity between the image reduction point spread function and the predetermined point spread function is less than the critical value, the digital image restoration module is optimized and the step SC2 is repeated

Claims (21)

A digital optical imaging design method, the steps comprising: A. a desired target setting step; B. an optical module design step, the optical module design step comprises: B1. generating an optical point spread by an optical module a function; B2. comparing the similarity between the optical point spread function and the predetermined point spread function; B3. outputting the optical module when the similarity between the optical point spread function and the predetermined point spread function is equal to or greater than the critical value And B4. when the similarity between the optical point spread function and the predetermined point spread function is less than the critical value, optimizing the optical module and repeating step B1; and C. a digital image restoration module design step The digital image restoration module design step comprises: C1. generating an image restoration point diffusion function by a digital image restoration module; C2. comparing the similarity between the image reduction point diffusion function and the predetermined point diffusion function; C3. And outputting the parameter of the digital image restoration module when the similarity between the image reduction point spread function and the predetermined point spread function is equal to or greater than the threshold value; and C4. The point spread is smaller than the threshold value to the predetermined similarity function of the point spread function, the digital image optimization module and repeat the step of reducing a C1; design wherein the step of the optical module and the module design digital image restoration step The synchronization is performed sequentially or sequentially. The digital optical imaging design method according to claim 1, wherein the desired target setting step provides a predetermined point spread function and a threshold. The design method of digital optical imaging according to claim 2, wherein the step B2 further comprises comparing the blur minimization of the optical point spread function with the predetermined point spread function. The design method of digital optical imaging according to claim 2, wherein the parameters of the optical module include at least a refractive index, a curvature value, a thickness value, and an aspheric coefficient. The design method of digital optical imaging according to claim 2, wherein the step C2 further comprises comparing the blur minimization of the optical point spread function with the predetermined point spread function. The digital optical imaging design method according to claim 5, wherein the parameter of the digital image restoration module includes at least one control parameter value. A digital optical imaging design method includes the steps of: D1. providing a fixed image reduction point spread function by a digital image restoration module; D2. generating an optical point spread function by an optical module; D3. comparing the optical a similarity between the point spread function and the fixed image reduction point spread function; D4. outputting the optical module when the similarity between the optical point spread function and the fixed image reduction point spread function is equal to or greater than a critical value Parameters; D5. When the similarity between the optical point spread function and the fixed image reduction point spread function is less than the critical value, the optical module is optimized and step D2 is repeated. According to the design method of digital optical imaging described in claim 7, wherein the step D3 further comprises comparing the blurring degree minimization of the optical point spread function and the fixed image reduction point spread function. The design method of digital optical imaging according to claim 7, wherein the parameters of the optical module include at least a refractive index, a curvature value, a thickness value, and an aspheric coefficient. A digital optical imaging design method, the steps comprising: E1. providing a fixed optical point spread function by an optical module; E2. generating an image reduction point spread function by a digital image restoration module; E3. comparing the fixed The similarity between the optical point spread function and the image reduction point spread function; E4. when the fixed optical point spread function and the image reduction point spread function have a similarity equal to or greater than a critical value, output the digital image reduction mode The parameter of the group; and E5. When the similarity between the fixed optical point spread function and the image reduction point spread function is less than the critical value, the digital image restoration module is optimized and step E2 is repeated. The method of designing digital optical imaging according to claim 10, wherein the step E3 further comprises comparing the fixed optical point spread function with the ambiguity minimization of the image reduction point spread function. According to the digital optical imaging design method described in claim 10, wherein the parameters of the digital image restoration module include at least one tone Control parameter values. A method for combining a digital optical imaging system, the digital optical imaging system comprising a plurality of optical modules and a plurality of digital image restoration modules, the method comprising: selecting one of the optical modules, and obtaining at least one of the optical modules a diffusion function; selecting one of the image restoration modules, and obtaining at least one diffusion function of the image restoration module; and separately or sequentially analyzing the point spread function of the optical module and the image restoration module The optical module and the image reduction mode are combined to form the digital optical imaging system according to a similarity threshold. The method for combining the digital optical imaging system according to claim 13 of the patent application scope, further comprising: obtaining a minimum value of the ambiguity of the at least one diffusion function of the optical mode structure, and obtaining at least a point of the diffusion function blur of the image restoration module The minimum value of the degree, when the point spread function ambiguity minimization value of the optical module is substantially equal to the diffusion function ambiguity minimization value of the image restoration module, or is greater than or equal to a predetermined threshold value, The optical module and the image reduction mode constitute the digital optical imaging system. A digital optical imaging design method, the method comprising: F1. generating at least two optical point spread functions by an optical module; F2. comparing similarities of the optical point spread functions; F3. when the optical point spread functions are When the similarity is equal to or greater than a critical value, the parameters of the optical module are output; and F4. When the similarity of the optical point spread functions is less than the critical value, The optical module is replaced and step F1 is repeated. The method of designing digital optical imaging according to claim 15 wherein the step F2 further comprises comparing the blur minimization of the optical point spread functions. The design method of digital optical imaging according to claim 15, wherein the parameters of the optical module include at least a refractive index, a curvature value, a thickness value, and an aspheric coefficient. A digital optical imaging design method, the method comprising: G1. generating a diffusion function of at least two image reduction points by a digital image restoration module; G2. comparing similarities of the diffusion functions of the image reduction points; G3. When the similarity of the reduction point spread function is equal to or greater than a critical value, the parameters of the digital image restoration module are output; and G4. when the similarity of the image reduction point spread function is less than the critical value, the digital image restoration is optimized. Module and repeat step G1. According to the design method of digital optical imaging described in claim 18, the step G2 further includes comparing the blur minimization of the image reduction point spread function. The digital optical imaging design method according to claim 18, wherein the parameter of the digital image restoration module includes at least one control parameter value. A computer software product comprising at least one non-transitory computer readable medium, wherein the medium includes computer program instructions, wherein the instructions cause the at least one computer to perform a digital optical imaging design method when reading at least one computer, The method comprises at least the following steps: H1. setting a target to provide a predetermined point spread function and a threshold value; H2. designing an optical module, comprising generating an optical point spread function from the optical module, and comparing the point spread of the optical And a similarity between the function and the predetermined point spread function, when the similarity between the point spread function of the optical point and the predetermined point spread function is equal to or greater than the threshold value, outputting at least one variable of the optical module; and when optical The similarity between the point spread function and the predetermined point spread function is to optimize the optical module and return to the step of generating an optical point spread function from the optical module when the threshold value is corrected; and H3. Designing an image restoration module; wherein the step of designing an optical module and the step of designing an image restoration module are performed synchronously or sequentially