Image quality evaluation method, system, equipment and medium for cubic phase mask imaging system

Abstract

The invention discloses an image quality evaluation method, system and equipment for a cubic phase mask imaging system, and a medium, belongs to the technical field of image quality evaluation methods for computational imaging systems, and solves the problem of low accuracy of image evaluation of the cubic phase mask imaging system caused by an existing evaluation method. Obtaining a clear non-coding image; obtaining a fuzzy coding image; carrying out registration on the clear non-coding image and the fuzzy coding image, and obtaining a registered image and recording the registered image as an image # imgabs0 #; the method comprises the following steps: processing a clear non-coding image, and recording the image as an image # imgabs1 #; and reconstructing the image # imgabs2, storing a # imgabs4 # area of the reconstructed image # imgabs3 # as an image # imgabs5 #, and determining the maximum structural similarity # imgabs9 # as an evaluation result of the three-time phase mask coding imaging system based on the temporary structural similarity # imgabs8 # of the recorded image # imgabs6 # and the recorded image # imgabs7 #.

Description

Technical Field

[0001] The present invention relates to the technical field of image quality evaluation methods for computational imaging systems, and particularly to image quality evaluation methods, systems, devices, and media for three-phase mask imaging systems. Background Art

[0002] The three-phase mask coded computational imaging technology is one of the hotspots in the current research of computational imaging technology. In traditional imaging systems, the performance of the optical system highly depends on the precise manufacturing of optical components and the strict control of the imaging environment. Minor errors in optical components or minor changes in the imaging environment may lead to a significant decline in image quality. Defocus of the optical system will make the image blurred, aberrations will cause image distortion, and environmental disturbances such as temperature changes and vibrations will affect the stability of optical components, thereby affecting the clarity and accuracy of imaging. These adverse factors are difficult to completely avoid in many practical application scenarios, especially in fields with extremely high requirements for image clarity and accuracy, such as aerospace remote sensing, biomedical imaging, high-end industrial inspection, etc. Therefore, it is particularly important to develop imaging technologies that can effectively cope with these adverse factors. The emergence of wavefront coding computational imaging technology provides a new idea for solving these problems. It introduces a specific phase mask on the pupil plane of the optical system to shape the (point spread function). This shaped has the characteristic of being insensitive to image quality degradation factors such as defocus and aberrations, enabling the imaging system to still obtain relatively stable blurred images under different defocus amounts and the presence of certain aberrations. Subsequently, by means of corresponding digital signal processing algorithms, these blurred images are deconvolved and restored to reconstruct high-quality clear images. Compared with traditional imaging technologies, wavefront coding computational imaging technology is more robust during the imaging process, does not require extremely precise adjustment of the optical system during imaging, reduces the requirements of the optical system for manufacturing processes and assembly accuracy, and also reduces the influence of environmental factors on image quality, greatly expanding the applicable range of the imaging system.

[0003] However, the current three - phase mask encoding computational imaging technology still faces some challenges. With the development of intelligent recognition and machine vision, simply using subjective evaluation and no - reference evaluation cannot guarantee the accuracy of image data. The three - phase mask encoding computational imaging system is limited by the phase plate installation error and the modulation effect of the three - phase mask plate in experiments. Using traditional image registration algorithms, the blurred encoded image cannot be perfectly registered with the clear non - encoded image, lacking the clear reference image required for full - reference evaluation and the precisely registered blurred encoded image. The commonly used evaluation indicators for the three - phase mask encoding computational imaging system are subjective evaluation indicators and no - reference evaluation indicators. And during the restoration process of the encoded image, some adverse phenomena such as ringing effect and over - sharpening will occur. The ringing effect usually appears as alternating bright and dark circular stripes near the image edge, which not only affects the visual effect of the image but also may obscure important details in the image, resulting in a decline in image quality. Traditional subjective evaluation and no - reference evaluation cannot accurately reflect these deviations. In such a situation, continuing to use traditional no - reference image quality assessment indicators, their accuracy and reliability will be severely affected.

[0004] In summary, in the prior art, the commonly used evaluation indicators for the three - phase mask encoding computational imaging system are subjective evaluation indicators and no - reference evaluation indicators. However, during the restoration process of the encoded image, image sharpening and ringing effect will lead to low accuracy of image evaluation. Summary of the Invention

[0005] The present invention solves the problem that the existing evaluation method leads to low accuracy of image evaluation for the three - phase mask imaging system.

[0006] The method for evaluating the image quality of the three - phase mask imaging system according to the present invention includes the following steps: Step S1: Obtain a clear non - encoded image; Step S2: Obtain a blurred encoded image; Step S3: Register the clear non - encoded image and the blurred encoded image, and denote the registered blurred encoded image as image ; After processing the clear non - encoded image, denote it as image ; Step S4: Reconstruct image , and save the area of the reconstructed image as image . Based on the temporary structural similarity between the recorded image and image , determine the maximum structural similarity as the evaluation result of the three - phase mask encoding imaging system.

[0007] Further, in the embodiment of the present invention, in step S1, the obtaining of the clear and non-coded image is specifically as follows: After removing the three-phase mask coding plate from the three-phase mask coding imaging system, the target scene is photographed to obtain a clear and non-coded image.

[0008] Further, in the embodiment of the present invention, in step S2, the obtaining of the blurred and coded image is specifically as follows: After installing the three-phase mask coding plate in the three-phase mask coding imaging system, the target scene is photographed to obtain a blurred and coded image.

[0009] Further, in the embodiment of the present invention, in step S3, after processing the clear and non-coded image, it is denoted as image , specifically as follows: In the clear and non-coded image, a clear area within the depth of focus is selected to obtain area, and the area of the clear and non-coded image is denoted as image .

[0010] Further, in the embodiment of the present invention, in step S3, the registration of the clear and non-coded image and the blurred and coded image is performed to obtain the registered blurred and coded image denoted as image , including the following steps: Step S301, respectively define the maximum offset as , the range of the reconstruction algorithm parameter is , the iteration step of the reconstruction algorithm is and the storage matrix is , where and are respectively and the pixel offsets in the Step S302, respectively initialize , and the reconstruction algorithm parameter ; Step S303, use the reconstruction algorithm with the reconstruction algorithm parameter to reconstruct the blurred and coded image, and move the reconstructed blurred and coded image , and denote the blurred and coded image after moving in the area as image ; Step S304, calculate the current for the image with the image of and store it into After the storage is completed, make ; Step S305, repeat Step S303 - Step S304 until is completed, then execute Step S306, where and store it into After the storage is completed, make ; Step S306, reset and repeat Step S303 - Step S305 until the reconstruction algorithm parameters when the pixel offset is then execute Step S307, where , and store it into After the storage is completed, make the reconstruction algorithm parameters ; Step S307, reset , respectively, and repeat Step S303 - Step S306 until the reconstruction algorithm parameters is completed, then execute Step S308 and store it into ; Step S308, obtain the index of the largest in Convert the index of the largest to the optimal registration parameter, and then register the blurred encoded image to obtain the registered blurred encoded image denoted as image .

[0011] Furthermore, in the embodiment of the present invention, in Step S4, when reconstructing the image , save the region of the reconstructed image as image . Based on the recorded temporary structural similarity between image and image , determine the maximum structural similarity as the evaluation result of the three - phase mask coded imaging system, including the following steps: Step S401, initialize the maximum structural similarity ; Step S402, use the reconstruction algorithm with the reconstruction algorithm parameters to reconstruct the image , and the reconstructed image in The area is recorded as an image ; Step S403, record the image and the image of the temporary structural similarity , if the temporary structural similarity is greater than the maximum structural similarity , then update the maximum structural similarity to the temporary structural similarity , otherwise, do not update the maximum structural similarity , and set the reconstruction algorithm parameter , where is the iteration step size of the reconstruction algorithm; Step S404, repeat steps S402 - S403 until the reconstruction algorithm parameter is completed, and then obtain the final maximum structural similarity as the evaluation result of the three - phase mask coded imaging system.

[0012] The image quality evaluation method system of the three - phase mask imaging system described in the present invention includes the following modules: The first acquisition module, which acquires a clear non - coded image; The second acquisition module, which acquires a blurred coded image; The registration module, which registers the clear non - coded image and the blurred coded image, and acquires the registered blurred coded image, recorded as the image ; After processing the clear non - coded image, it is recorded as the image ; The evaluation module, which reconstructs the image , saves the area of the reconstructed image as the image , and determines the maximum structural similarity based on the recorded temporary structural similarity between the image and the image to be the evaluation result of the three - phase mask coded imaging system.

[0013] An electronic device described in the present invention includes a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus; The memory is used to store a computer program; The processor, when executing the program stored on the memory, implements the image quality evaluation method of the three - phase mask imaging system described in any one of the above.

[0014] ​A computer-readable storage medium according to the present invention stores a computer program therein, and when the computer program is executed by a processor, the image quality evaluation method of the three-phase mask imaging system described above is implemented.

[0015] The present invention solves the problem that the existing evaluation method leads to low accuracy in image evaluation of the three-phase mask imaging system. The specific beneficial effects include: 1. For the image quality evaluation method of the three-phase mask imaging system described in the present invention, the existing evaluation method leads to low accuracy in image evaluation. To solve the technical problems existing in the prior art, the present invention uses the characteristic sensitive to pixel misalignment and uses a full-reference evaluation index to evaluate the reconstructed image, which has higher accuracy and robustness compared with the subjective evaluation or no-reference evaluation index used in the prior art; 2. For the image quality evaluation method of the three-phase mask imaging system described in the present invention, when registering the reference image and the test image, on the basis of the registration algorithm, the reconstruction algorithm of the phase mask encoded image and the characteristic that the index is sensitive to pixel misalignment are combined to correct the offset of the misaligned image, solving the problem of incomplete registration caused by the modulation of the image of the three-phase mask encoding imaging system by the three-phase mask encoding plate, and providing a prerequisite for the full-reference image quality evaluation of the three-phase mask encoding imaging system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and / or additional aspects and advantages of the present invention will become apparent and easy to understand from the following description of the embodiments in conjunction with the drawings, where: Figure 1 is a diagram of the three-phase mask encoding imaging system described in Embodiment 1; Figure 2 is a diagram of a clear non-encoded image described in Embodiment 1; Figure 3 is a diagram of a blurred encoded image described in Embodiment 1; Figure 4 is a diagram of the registered image described in Embodiment 1. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] The following will clearly and completely describe various embodiments of the present invention in conjunction with the drawings. The embodiments described by referring to the drawings are exemplary and are intended to explain the present invention, and should not be construed as limiting the present invention.

[0018] Embodiment 1. The image quality evaluation method of the three-phase mask imaging system described in this embodiment includes the following steps: Step S1, obtaining a clear non-encoded image; Step S2, obtaining a blurred encoded image; Step S3: Register the clear non-coded image and the blurred coded image to obtain the registered blurred coded image, denoted as image ; After processing the clear non-coded image, it is denoted as image ; Step S4: Reconstruct image , and save the region of the reconstructed image as image . Based on the recorded temporary structural similarity between image , determine the maximum structural similarity as the evaluation result of the three-phase mask coded imaging system.

[0019] In this embodiment, in step S1, the obtaining of the clear non-coded image is specifically as follows: After removing the three-phase mask coding plate from the three-phase mask coded imaging system, photograph the target scene to obtain the clear non-coded image.

[0020] In this embodiment, in step S2, the obtaining of the blurred coded image is specifically as follows: After installing the three-phase mask coding plate in the three-phase mask coded imaging system, photograph the target scene to obtain the blurred coded image.

[0021] In this embodiment, in step S3, after processing the clear non-coded image, it is denoted as image , specifically: Select the clear region within the depth of focus in the clear non-coded image to obtain region, and denote the region of the clear non-coded image as image .

[0022] In this embodiment, in step S3, the registration of the clear non-coded image and the blurred coded image to obtain the registered image, denoted as image , includes the following steps: Step S301: Define the maximum offset as , the range of the reconstruction algorithm parameter is , the iteration step size of the reconstruction algorithm is and The storage matrix is , where and are respectively and ​Pixel offset in the direction; Step S302, initialize respectively , and the reconstruction algorithm parameters ; Step S303, use the reconstruction algorithm with the reconstruction algorithm parameters to reconstruct the blurred encoded image, and move the reconstructed blurred encoded image , and record the blurred encoded image after moving in the area as image ; Step S304, calculate the of the current image and image , and store it in . After the storage is completed, let ; Step S305, repeat Step S303 - Step S304 until is completed, then execute Step S306, where , and store it in . After the storage is completed, let ; Step S306, reset , and repeat Step S303 - Step S305 until the pixel offset is when the reconstruction algorithm parameters are completed, then execute Step S307, where , , , and store it in . After the storage is completed, let the reconstruction algorithm parameters ; Step S307, reset respectively , , and repeat Step S303 - Step S306 until the reconstruction algorithm parameters are completed, then execute Step S308 and store it in ; Step S308, obtain the index of the maximum in . After converting the index of the maximum to the optimal registration parameter, register the blurred encoded image to obtain the registered blurred encoded image denoted as image .

[0023] In this embodiment, in Step S4, when reconstructing the image , the reconstructed image of The area is saved as an image , based on the recorded image and the image has a temporary structural similarity , and determine the maximum structural similarity as the evaluation result of the three - phase - mask encoded imaging system, including the following steps: Step S401, initialize the maximum structural similarity ; Step S402, use the reconstruction algorithm with the reconstruction algorithm parameters to reconstruct the image , and denote the reconstructed image in the area as image ; Step S403, record the temporary structural similarity between image and image . If the temporary structural similarity is greater than the maximum structural similarity , then update the maximum structural similarity to the temporary structural similarity , otherwise, do not update the maximum structural similarity , and let the reconstruction algorithm parameters , where is the iteration step of the reconstruction algorithm; Step S404, repeat Step S402 - Step S403 until after completing the reconstruction algorithm parameters , and obtain the final maximum structural similarity as the evaluation result of the three - phase - mask encoded imaging system .

[0024] The existing evaluation methods generally use subjective evaluation indicators and no - reference evaluation indicators. However, during the restoration process of the encoded image, image sharpening and ringing effects will lead to low accuracy of image evaluation

[0025] To solve the technical problems existing in the prior art, this embodiment proposes an image quality evaluation method for a three - phase - mask imaging system, including the following steps: The reconstruction algorithm uses the classical algorithm (spatial - domain image restoration algorithm based on Bayesian theory), and the reconstruction parameters are ( , number of iterations), the iteration step is 1, and the optical system parameters are shown in Table 1; Table 1 Optical system parameters

[0026] Step S1, obtain a clear non-coded image, specifically: As Figure 1 shown, the three-phase mask coded imaging system includes a three-phase mask coding plate, an imaging lens, and a detector. Remove the three-phase mask coding plate in the three-phase mask coding optical system, and fix the three-phase mask coded imaging system on a stable optical flat plate to photograph the target scene. At least one area of the target scene needs to be within the focal depth of the imaging lens to ensure that a clear area that can be used as a reference image can be obtained. The obtained clear non-coded image is as Figure 2 shown; Step S2, obtain a blurred coded image, specifically: Install the three-phase mask coding plate back into the three-phase mask coded imaging system, and photograph the same target scene again at the same angle to obtain a blurred coded image of the same target scene. The obtained blurred coded image is as Figure 3 shown; Step S3, register the clear non-coded image and the blurred coded image, including the following steps: After the clear non-coded image and the blurred coded image are acquired, due to the human error in the installation process and the surface shape of the three-phase mask coding plate, the clear non-coded image and the blurred coded image cannot meet the requirements of the full-reference evaluation of the image for image registration. Therefore, before performing the full-reference evaluation of the image, it is necessary to register the misaligned coded image and non-coded image in combination with the imaging principle of the three-phase mask coded imaging system; Step S301, select a clear area within the focal depth in the clear non-coded image to obtain (rectangular) area , The area includes the abscissa of the upper left corner point of the area, the ordinate of the upper left corner point of the area, the width and height of the area. Save the area of the clear non-coded image as image , and image is the reference image; Step S302, respectively define the maximum offset as , the range of the reconstruction algorithm parameter is [1, 10], the iteration step of the reconstruction algorithm is and the storage matrix is , where and are respectively and the pixel offsets in the Step S303, respectively initialize , and the reconstruction algorithm parameter ; Step S304: Use the reconstruction algorithm with the reconstruction algorithm parameters to reconstruct the blurred encoded image, and move the reconstructed blurred encoded image by the pixel offset . Then, record the blurred encoded image with the pixel offset in the area as image . Image is the test image; Step S305: Calculate the , , of the image and the image ( , an evaluation index in the field of digital image processing), and store it in for subsequent obtaining of the optimal offset. After storage, let ; ; Step S306: Repeat Step S304 - Step S305 until is completed. Then, execute Step S307, where , and store it in . After storage, let ; Step S307: Reset , and repeat Step S304 - Step S306 until the pixel offset is when the reconstruction algorithm parameters are completed. Then, execute Step S308, where , , and store it in . After storage, let the reconstruction algorithm parameters ; Step S308: Reset , respectively, and repeat S304 - Step S307 until the reconstruction algorithm parameters are completed. Then, execute Step S309 and store it in ; Step S309: Obtain the index of the maximum in . According to the three - dimensional size of , convert the index to the optimal registration parameter , . After that, register the blurred encoded image to obtain the registered image, denoted as image ; Step S4: For image Perform reconstruction and save the reconstructed image of the area as an image , and based on the recorded image and the image calculate the temporary structural similarity , and determine the maximum structural similarity as the evaluation result of the three - phase mask coded imaging system, including the following steps: Step S401, initialize the maximum structural similarity , and the reconstruction algorithm parameters ; Step S402, use the reconstruction algorithm with the reconstruction algorithm parameters to reconstruct the image , and then record the reconstructed image in the area as the image ; Step S403, record the temporary structural similarity between the image and the image . If the temporary structural similarity is greater than the maximum structural similarity , then update the maximum structural similarity to the temporary structural similarity , otherwise, do not update the maximum structural similarity , and let the reconstruction algorithm parameters ; Step S404, repeat Step S402 - Step S403 until the reconstruction algorithm parameters are completed, then obtain the final maximum structural similarity . The final maximum structural similarity is used as the evaluation result of the three - phase mask coded imaging system. The reconstructed image at this time is as shown in Figure 4 . Figure 4 Compared with the blurred coded image without reconstruction registration as shown in Figure 3 , it is obviously closer in the clear area Figure 2 .

[0027] Therefore, for the full - reference image quality evaluation method of the coded imaging system proposed in this embodiment, taking the obtained maximum structural similarity as the evaluation result of the three - phase mask coded imaging system is significantly more accurate than the maximum structural similarity between the reference image and the test image without using this registration method.

[0028] In summary, the image quality evaluation method for the three - phase mask imaging system according to the present invention realizes the full - reference image quality evaluation of the three - phase mask coded imaging system, effectively avoiding the problem of low accuracy of subjective evaluation and no - reference evaluation caused by image sharpening and ringing effect during the restoration process of coded images. Compared with the current no - reference and subjective evaluation methods for the three - phase mask coded imaging system, the evaluation effect is more accurate and the robustness is higher.

[0029] Embodiment 2. The image quality evaluation method system for the three - phase mask imaging system described in this embodiment includes the following modules: The first acquisition module acquires a clear non - coded image; The second acquisition module acquires a blurred coded image; The registration module registers the clear non - coded image and the blurred coded image, and acquires the registered blurred coded image denoted as image ; After processing the clear non - coded image, it is denoted as image ; The evaluation module reconstructs image , saves the area of the reconstructed image as image . Based on the temporary structural similarity between the recorded image and image , determines the maximum structural similarity as the evaluation result of the three - phase mask coded imaging system.

[0030] Embodiment 3. An electronic device described in this embodiment includes a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus; The memory is used to store a computer program; When the processor is used to execute the program stored in the memory, it realizes the image quality evaluation method for the three - phase mask imaging system described in Embodiment 1.

[0031] Embodiment 4. A computer - readable storage medium described in this embodiment stores a computer program inside. When the computer program is executed by a processor, it realizes the image quality evaluation method for the three - phase mask imaging system described in Embodiment 1.

[0032] The above has introduced in detail the image quality evaluation method, system, device and medium of the three-phase mask imaging system proposed by the present invention. In this article, specific examples are used to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention. At the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. Method for evaluating image quality of a three - phase mask imaging system, characterized in that, Including the following steps: Step S1: Obtain a clear and unencoded image; Step S2: Obtain a blurred encoded image; Step S3, register the clear image without coding and the blurred coded image, and obtain the registered blurred coded image, denoted as image ; After processing the clear and unencoded image, it is denoted as image ; Step S4, reconstruct the image and save the area of the reconstructed image as image . Based on the temporary structural similarity between the recorded image and the image , determine the maximum structural similarity as the evaluation result of the three - phase mask encoding imaging system.

2. The image quality evaluation method of the three - phase mask imaging system according to claim 1, wherein In the said step S1, the obtaining of the clear and unencoded image is specifically: After removing the three - phase mask encoding plate from the three - phase mask encoding imaging system, photograph the target scene to obtain a clear and unencoded image.

3. The image quality evaluation method of the three - phase mask imaging system according to claim 1, characterized in that, In the said step S2, the obtaining of the blurred encoded image is specifically: After installing the three - phase mask encoding plate in the three - phase mask encoding imaging system, photograph the target scene to obtain a blurred encoded image.

4. The image quality evaluation method for a three - phase mask imaging system according to claim 1, characterized in that, In the said step S3, after processing the clear image without coding, it is denoted as image , specifically: Select a clear area within the depth of focus in the clear and unencoded image to obtain the area, and mark the area of the clear and unencoded image as image .

5. The image quality evaluation method of the three - phase mask imaging system according to claim 1, characterized in that In the said step S3, the clear non-coded image and the blurred coded image are registered to obtain the registered blurred coded image denoted as image , which includes the following steps: Step S301, define the maximum offset as , the range of the reconstruction algorithm parameter is , the iteration step of the reconstruction algorithm is and the storage matrix is , where and are respectively and the pixel offsets in the Step S302, initialize respectively , and the reconstruction algorithm parameters ; Step S303, using the reconstruction algorithm parameters to reconstruct the blurred encoded image with the reconstruction algorithm, and move the reconstructed blurred encoded image , and record the blurred encoded image after the movement in the area as image ; Step S304, calculate the current image under and the image of , and store it into . After the storage is completed, make ; Step S305: Repeat Step S303 - Step S304 until completion , then execute Step S306, where , and store it in . After the storage is completed, let ; Step S306, reset , and repeat Step S303 - Step S305 until the reconstruction algorithm parameters are completed When the pixel offset is , then execute Step S307, where , , and store it into . After the storage is completed, set the reconstruction algorithm parameters ; Step S307, reset respectively , , and repeat Step S303 - Step S306 until the reconstruction algorithm parameters are completed, then execute Step S308 and store it into ; Step S308, in obtain the index of the maximum . After converting the index of the maximum into the optimal registration parameters, register the blurred coded image, and obtain the registered blurred coded image denoted as image .

6. The image quality evaluation method of the three - phase mask imaging system according to claim 1, characterized in that In the said step S4, for the image to be reconstructed, and save the area of the reconstructed image as an image . Based on the recorded image and the temporal structural similarity of the image, determine the maximum structural similarity as the evaluation result of the three - phase mask encoding imaging system, including the following steps: Step S401, initialize the maximum structural similarity ; Step S402, use the reconstruction algorithm parameters of the reconstruction algorithm to reconstruct the image , and mark the reconstructed image in the area as image ; Step S403, record the image The temporal structural similarity with the image If the temporal structural similarity is greater than the maximum structural similarity , then update the maximum structural similarity to the temporal structural similarity , otherwise, do not update the maximum structural similarity . Let the reconstruction algorithm parameter , where is the iteration step size of the reconstruction algorithm; ​ Step S404, repeat Step S402 - Step S403 until the reconstruction algorithm parameters are completed After that, obtain the final maximum structural similarity As the evaluation result of the three - phase - mask encoded imaging system.

7. Method and system for evaluating image quality of a three - phase mask imaging system, characterized in that, Including the following modules: The first obtaining module, which obtains a clear and unencoded image; The second obtaining module, which obtains a blurred encoded image; A registration module registers the clear non-coded image and the blurred coded image, and obtains the registered blurred coded image, denoted as image ; After processing the clear and unencoded image, it is denoted as image ; Evaluation module, for the image Perform reconstruction, and save the reconstructed image of the region as an image , and based on the recorded image and the image temporal structural similarity , determine the maximum structural similarity as the evaluation result of the three - phase mask encoded imaging system.

8. An electronic device, characterized in that, Including a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus; The memory is used for storing computer programs; When the processor is used to execute the program stored on the memory, it realizes the image quality evaluation method of the three - phase mask imaging system according to any one of claims 1 - 6.

9. A computer-readable storage medium, characterized in that, The computer - readable storage medium stores a computer program, and when the computer program is executed by the processor, it realizes the image quality evaluation method of the three - phase mask imaging system according to any one of claims 1 - 6.

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