Intelligent judgment system for artifact elimination processing

Abstract

The invention relates to an intelligent judgment system for artifact elimination processing, and the system comprises an elimination judgment device which is used for taking the mean square error of each gray value corresponding to each pixel point of a to-be-judged image as the current mean square error, taking the mean square error of each gray value corresponding to each pixel point of a reference processing image as the auxiliary mean square error, and determining the current mean square error; when the absolute value of the difference value of the current mean square error and the auxiliary mean square error is smaller than or equal to a set mean square error threshold value, it is judged that the image to be judged is subjected to image processing of artifact elimination in the super-definition camera equipment; and a state transmission device for transmitting the artifact-cancelled correlation determination signal. According to the invention, intelligent visual analysis can be carried out on whether the image to be judged is subjected to image processing of artifact elimination or not based on the various visual parameters of the image to be judged and the various visual parameters of the reference processing picture subjected to artifact elimination processing; therefore, an effective basis is provided for accurate judgment of the original content of the to-be-judged image.

Description

Technical Field

[0001] The present invention relates to the field of image optimization, and in particular to an intelligent determination system for artifact elimination processing. Background Art

[0002] 2 Artifact elimination is one of the main processing types of image optimization. Artifacts refer to various forms of images that appear on the image even though the scanned object does not exist. For example, CT image artifacts refer to abnormal density changes on the image that do not match the actual anatomical structure. It involves CT machine component failure, insufficient calibration, algorithm errors, and even errors. To eliminate such artifacts, it is necessary to conduct specific analysis of specific problems based on the shape of the image artifacts, density change values, and scanning parameters. Image artifacts of CT machines are somewhat universal, and ring artifacts are the most common. In addition, by selecting appropriate filters, artifacts can be effectively reduced or eliminated. For example, polarization filters can effectively reduce artifacts caused by lens reflections, and neutral density filters can reduce exposure and reduce the brightness of the light source.

[0003] Currently, when facing a frame of image to be determined, it is possible to determine whether an artifact removal operation needs to be performed on it according to the presence of artifacts in the image. However, it is difficult to determine whether the artifact removal operation has been performed on the image content of the image to be determined after the artifact removal operation has been performed, which makes it difficult to restore the original content of the image to be determined. Summary of the invention

[0004] In order to solve the technical problems in the prior art, the present invention provides an intelligent determination system for artifact elimination processing, which obtains a photoelectric sensing picture obtained by a certain sensing operation of the photoelectric sensing component of the ultra-high-definition camera device in the past, performs image processing for artifact elimination on the received photoelectric sensing picture, and obtains and outputs a corresponding reference processing picture, thereby providing reliable basic data for visual analysis of whether the image to be determined is subjected to image processing for artifact elimination in the ultra-high-definition camera device, and uses the mean square error of each grayscale value corresponding to each pixel point of the image to be determined as the current mean square error, and uses the mean square error of each grayscale value corresponding to each pixel point of the reference processing picture as the auxiliary Mean square error is used to respectively complete targeted numerical analysis of the image to be determined and the reference processing picture, and when the absolute value of the difference between the current mean square error and the auxiliary mean square error is less than or equal to the set mean square error threshold, it is judged that the image to be determined has been processed for artifact elimination in the ultra-high-definition camera device; when the absolute value of the difference between the current mean square error and the auxiliary mean square error is greater than the set mean square error threshold, it is judged that the image to be determined has not been processed for artifact elimination in the ultra-high-definition camera device, thereby completing the visual analysis of whether the image to be determined has been processed for artifact elimination in the ultra-high-definition camera device, and providing an effective basis for the accurate judgment of the original content of the image to be determined.

[0005] According to the present invention, there is provided an intelligent determination system for artifact elimination processing, the system comprising: 6. Content acquisition mechanism, used to acquire the photoelectric sensing image obtained by a certain sensing operation in the history of the photoelectric sensing component of the ultra-high-definition camera device; 7. A processing execution mechanism connected to the content acquisition mechanism, configured to perform image processing for removing artifacts on the received photoelectric sensing picture, so as to obtain and output a corresponding reference processing picture; 8. A generation component for performing each learning action on the recurrent neural network to obtain a recurrent neural network after each learning action and output it as a recurrent neural network model, wherein the number of learning actions performed by the recurrent neural network is proportional to the number of pixel circuits of the photoelectric sensing component of the ultra-high-definition camera device; 9 elimination judgment device, connected to the sub-generation component, the content acquisition mechanism and the processing execution mechanism, respectively, for taking the mean square error of each gray value corresponding to each pixel of the image to be determined as the current mean square error, taking the mean square error of each gray value corresponding to each pixel of the reference processing picture as the auxiliary mean square error, and judging that the image to be determined has been subjected to the image processing of artifact elimination in the ultra-clear camera device when the absolute value of the difference between the current mean square error and the auxiliary mean square error is less than or equal to the set mean square error threshold; 10. A state transmission device connected to the elimination judgment device, configured to transmit a first judgment signal to a remote blockchain service network element through a wireless transmission channel when it is determined that the image to be judged has been subjected to image processing for artifact elimination in the ultra-high-definition camera device; 11 Wherein, the elimination judgment device is further used to judge that the image to be determined has not been subjected to the image processing for artifact elimination in the ultra-high-definition camera device when the absolute value of the difference between the current mean square error and the auxiliary mean square error is greater than the set mean square error threshold; 12 Wherein, the state transmission device is further used to transmit the second determination signal to the remote blockchain service network element through the wireless transmission channel when it is determined that the image to be determined has not been subjected to the image processing for artifact elimination in the ultra-high-definition camera device; 13 Wherein, the mean square error of each grayscale value corresponding to each pixel point of the image to be determined is taken as the current mean square error, and the mean square error of each grayscale value corresponding to each pixel point of the reference processing picture is taken as the auxiliary mean square error. When the absolute value of the difference between the current mean square error and the auxiliary mean square error is less than or equal to the set mean square error threshold, it is judged that the image processing of artifact elimination has been performed on the image to be determined in the ultra-high-definition camera device, including: the set mean square error threshold is pre-stored in the parameter storage component built into the elimination judgment device.

[0006] 14 It can be seen that the present invention has at least the following main inventive concepts: 15 Inventive concept A: Acquire a photoelectric sensing picture obtained by a certain sensing operation of a photoelectric sensing component of an ultra-high-definition camera device in history, perform image processing for artifact removal on the received photoelectric sensing picture, so as to obtain and output a corresponding reference processing picture, thereby providing reliable basic data for visual analysis of whether an image to be determined has been subjected to image processing for artifact removal in the ultra-high-definition camera device; Inventive concept B: The mean square error of each grayscale value corresponding to each pixel point of the image to be determined is used as the current mean square error, and the mean square error of each grayscale value corresponding to each pixel point of the reference processing picture is used as the auxiliary mean square error, so as to respectively complete the targeted numerical analysis of the image to be determined and the reference processing picture; 17 Inventive concept C: when the absolute value of the difference between the current mean square error and the auxiliary mean square error is less than or equal to the set mean square error threshold, it is judged that the image to be determined has been processed for artifact elimination in the ultra-high definition camera device; when the absolute value of the difference between the current mean square error and the auxiliary mean square error is greater than the set mean square error threshold, it is judged that the image to be determined has not been processed for artifact elimination in the ultra-high definition camera device, thereby completing the visual analysis of whether the image to be determined has been processed for artifact elimination in the ultra-high definition camera device, and providing an effective basis for accurately judging the original content of the image to be determined. DETAILED DESCRIPTION

[0007] 18 The following is a detailed description of an embodiment of the intelligent determination system for artifact elimination processing of the present invention.

[0008] 19 According to the primary embodiment of the present invention, the intelligent determination system for artifact elimination processing includes: 20. Content acquisition mechanism, used to acquire a photoelectric sensing image obtained by a certain sensing operation of a photoelectric sensing component of an ultra-high-definition camera device in history; 21 For example, the content acquisition mechanism is used to acquire a photoelectric sensing picture obtained by a certain sensing operation of a photoelectric sensing component of an ultra-high-definition camera device in history, including: the photoelectric sensing component is a CMOS sensing component or a CCD sensing component; 22 a processing execution mechanism connected to the content acquisition mechanism, used to perform image processing for removing artifacts on the received photoelectric sensing picture to obtain and output a corresponding reference processing picture; 23 a generation component for performing each learning action on the recurrent neural network to obtain a recurrent neural network after each learning action and output it as a recurrent neural network model, wherein the number of learning actions performed by the recurrent neural network is proportional to the number of pixel circuits of the photoelectric sensing component of the ultra-high-definition camera device; 24 elimination judgment device, connected to the sub-generation component, the content acquisition mechanism and the processing execution mechanism, respectively, for taking the mean square error of each gray value corresponding to each pixel of the image to be determined as the current mean square error, taking the mean square error of each gray value corresponding to each pixel of the reference processing picture as the auxiliary mean square error, and judging that the image to be determined has been subjected to the image processing of artifact elimination in the ultra-clear camera device when the absolute value of the difference between the current mean square error and the auxiliary mean square error is less than or equal to the set mean square error threshold; 25 a state transmission device, connected to the elimination judgment device, for transmitting a first judgment signal to a remote blockchain service network element through a wireless transmission channel when it is determined that the image to be judged has been subjected to image processing for artifact elimination in the ultra-high-definition camera device; 26 Wherein, the elimination judgment device is further used to judge that the image to be determined has not been subjected to the image processing for artifact elimination in the ultra-high-definition camera device when the absolute value of the difference between the current mean square error and the auxiliary mean square error is greater than the set mean square error threshold; 27 Wherein, the mean square error of each grayscale value corresponding to each pixel point of the image to be determined is used as the current mean square error, and the mean square error of each grayscale value corresponding to each pixel point of the reference processing picture is used as the auxiliary mean square error, and when the absolute value of the difference between the current mean square error and the auxiliary mean square error is less than or equal to the set mean square error threshold, it is determined that the image to be determined has been subjected to the image processing of artifact elimination in the ultra-high-definition camera device, including: the set mean square error threshold is pre-stored in the parameter storage component built into the elimination judgment device; 28 Wherein, the state transmission device is further used to transmit the second determination signal to the remote blockchain service network element through the wireless transmission channel when it is determined that the image to be determined has not been subjected to the image processing for artifact elimination in the ultra-high-definition camera device; 29 Among them, the mean square error of each grayscale value corresponding to each pixel point of the image to be determined is taken as the current mean square error, and the mean square error of each grayscale value corresponding to each pixel point of the reference processing picture is taken as the auxiliary mean square error. When the absolute value of the difference between the current mean square error and the auxiliary mean square error is less than or equal to the set mean square error threshold, it is determined that the image to be determined has been subjected to the image processing for artifact elimination in the ultra-high definition camera device. The image processing also includes: using a numerical calculation formula to realize parallel calculation processing of the current mean square error and the auxiliary mean square error.

[0009] Compared with the primary embodiment of the present invention, the intelligent determination system for artifact elimination processing in the secondary embodiment of the present invention may further include: 31. A pressure detection mechanism, comprising a plurality of pressure detection units, for respectively detecting current surface pressure values ​​of the elimination judgment device, the batch generation component, the content acquisition mechanism and the processing execution mechanism; 32 Wherein, the pressure detection mechanism includes a plurality of pressure detection units for respectively detecting the current surface pressure values ​​of the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism, including: the plurality of pressure detection units respectively used by the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism are a plurality of contact pressure sensors; 33 Wherein, the pressure detection mechanism includes a plurality of pressure detection units for respectively detecting the current surface pressure values ​​of the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism, and further includes: the internal structures of the plurality of contact pressure sensors respectively used for the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism are the same; 34 Wherein, the pressure detection mechanism includes a plurality of pressure detection units for respectively detecting the current surface pressure values ​​of the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism, and further includes: a plurality of non-contact pressure sensors respectively used for the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism have the same pressure measurement upper limit threshold and pressure measurement lower limit threshold; 35 Wherein, the pressure detection mechanism includes a plurality of pressure detection units for respectively detecting the current surface pressure values ​​of the elimination judgment device, the batch generation component, the content acquisition mechanism and the processing execution mechanism, and further includes: a plurality of contact pressure sensors respectively used for the elimination judgment device, the batch generation component, the content acquisition mechanism and the processing execution mechanism all perform the detection of the corresponding current surface pressure value based on the difference between the air pressure and the internal pressure of the detected device.

[0010] Compared with the primary embodiment of the present invention, the intelligent determination system for artifact elimination processing in the secondary embodiment of the present invention may further include: 37 a real-time warning mechanism, connected to the plurality of contact pressure sensors respectively used by the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism, for performing corresponding pressure warning operations based on the pressure measurement results of the plurality of contact pressure sensors respectively used by the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism; 38 Wherein, the real-time warning mechanism is respectively connected to a plurality of contact pressure sensors respectively used by the elimination judgment device, the fractional generation component, the content acquisition mechanism and the processing execution mechanism, and is used to perform corresponding pressure warning operations based on the pressure measurement results of the plurality of contact pressure sensors respectively used by the elimination judgment device, the fractional generation component, the content acquisition mechanism and the processing execution mechanism, including: the real-time warning mechanism includes a timing analysis unit and a warning operation unit; 39 and wherein the real-time warning mechanism is respectively connected to a plurality of contact pressure sensors respectively used for the elimination judgment device, the batch generation component, the content acquisition mechanism and the processing execution mechanism, and is used to perform corresponding pressure warning operations based on the pressure measurement results of the plurality of contact pressure sensors respectively used for the elimination judgment device, the batch generation component, the content acquisition mechanism and the processing execution mechanism, and also includes: within the real-time warning mechanism, the timing analysis unit is connected to the warning operation unit.

[0011] 40 In addition, in the artifact elimination processing intelligent determination system, the mean square error of each grayscale value corresponding to each pixel point of the image to be determined is used as the current mean square error, and the mean square error of each grayscale value corresponding to each pixel point of the reference processing screen is used as the auxiliary mean square error. When the absolute value of the difference between the current mean square error and the auxiliary mean square error is less than or equal to the set mean square error threshold, it is determined that the image to be determined has been subjected to artifact elimination in the ultra-clear camera device. The image processing also includes: using the MATLAB toolbox to implement the test and simulation of the data processing process of the image processing of using the mean square error of each grayscale value corresponding to each pixel point of the image to be determined as the current mean square error, and using the mean square error of each grayscale value corresponding to each pixel point of the reference processing screen as the auxiliary mean square error. When the absolute value of the difference between the current mean square error and the auxiliary mean square error is less than or equal to the set mean square error threshold, it is determined that the image to be determined has been subjected to artifact elimination in the ultra-clear camera device. 41 and wherein, the mean square error of each grayscale value corresponding to each pixel point of the image to be determined is used as the current mean square error, and the mean square error of each grayscale value corresponding to each pixel point of the reference processing picture is used as the auxiliary mean square error. When the absolute value of the difference between the current mean square error and the auxiliary mean square error is less than or equal to the set mean square error threshold, it is determined that the image to be determined has been subjected to image processing for artifact elimination in the ultra-high definition camera device. The image processing also includes: the grayscale value of each pixel point is between 0 and 255.

[0012] 42 The intelligent determination system for artifact removal processing of the present invention can solve the technical problem in the prior art that it is difficult to effectively identify whether the current image content has undergone artifact removal operations. It can perform intelligent visual analysis on whether the image to be determined has been subjected to artifact removal processing based on various visualization parameters of the image to be determined and various visualization parameters of the reference processing picture that has undergone artifact removal processing, thereby providing an effective basis for accurately determining the original content of the image to be determined, thereby solving the above-mentioned technical problem.

[0013] 43 In the foregoing specification, the invention has been described with reference to specific exemplary embodiments thereof. It will be apparent, however, that various modifications and changes may be made thereto without departing from the broad spirit and scope of the invention as set forth in the appended claims. The specification is therefore to be regarded as illustrative rather than restrictive.

Claims

1. An intelligent determination system for artifact elimination processing, characterized in that: The system comprises: A content acquisition mechanism, used to acquire a photoelectric sensing image obtained by a certain sensing operation in the history of a photoelectric sensing component of an ultra-high-definition camera device; A processing execution mechanism, connected to the content acquisition mechanism, for performing image processing for artifact elimination on the received photoelectric sensing picture to obtain and output a corresponding reference processing picture; A multiple generation component is used to perform each learning action on the recurrent neural network to obtain a recurrent neural network after each learning action and output it as a recurrent neural network model, wherein the number of learning actions performed by the recurrent neural network is proportional to the number of pixel circuits of the photoelectric sensing component of the ultra-high-definition camera device; an elimination judgment device, connected to the sub-generation component, the content acquisition mechanism and the processing execution mechanism, respectively, for taking the mean square error of each grayscale value corresponding to each pixel point of the image to be determined as the current mean square error, taking the mean square error of each grayscale value corresponding to each pixel point of the reference processing picture as the auxiliary mean square error, and judging that the image to be determined has been subjected to image processing for artifact elimination in the ultra-clear camera device when the absolute value of the difference between the current mean square error and the auxiliary mean square error is less than or equal to a set mean square error threshold; A state transmission device, connected to the elimination judgment device, is used to transmit a first judgment signal to a remote blockchain service network element through a wireless transmission channel when it is determined that the image to be judged has been subjected to image processing for artifact elimination in the ultra-high-definition camera device; The elimination judgment device is further used to judge that the image to be determined has not been subjected to the image processing for artifact elimination in the ultra-high-definition camera device when the absolute value of the difference between the current mean square error and the auxiliary mean square error is greater than the set mean square error threshold; Among them, the mean square error of each grayscale value corresponding to each pixel point of the image to be judged is used as the current mean square error, and the mean square error of each grayscale value corresponding to each pixel point of the reference processing picture is used as the auxiliary mean square error. When the absolute value of the difference between the current mean square error and the auxiliary mean square error is less than or equal to the set mean square error threshold, it is judged that the image processing of artifact elimination has been performed on the image to be judged in the ultra-high-definition camera device, including: the set mean square error threshold is pre-stored in the parameter storage component built into the elimination judgment device.

2. The intelligent determination system for artifact elimination processing according to claim 1, characterized in that: The state transmission device is also used to transmit the second determination signal to the remote blockchain service network element through the wireless transmission channel when it is determined that the image to be determined has not been subjected to the image processing for artifact elimination in the ultra-high-definition camera device; Among them, the mean square error of each grayscale value corresponding to each pixel point of the image to be determined is used as the current mean square error, and the mean square error of each grayscale value corresponding to each pixel point of the reference processing picture is used as the auxiliary mean square error. When the absolute value of the difference between the current mean square error and the auxiliary mean square error is less than or equal to the set mean square error threshold, it is determined that the image to be determined has been subjected to image processing for artifact elimination in the ultra-high-definition camera device, and the image processing also includes: using a numerical calculation formula to realize parallel calculation processing of the current mean square error and the auxiliary mean square error.

3. The intelligent determination system for artifact elimination processing according to claim 2, characterized in that: The system further comprises: A pressure detection mechanism, comprising a plurality of pressure detection units, for respectively detecting current surface pressure values ​​of the elimination judgment device, the batch generation component, the content acquisition mechanism and the processing execution mechanism; Among them, the pressure detection mechanism includes multiple pressure detection units, which are used to respectively detect the current surface pressure values ​​of the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism, including: the multiple pressure detection units respectively used for the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism are multiple contact pressure sensors.

4. The intelligent determination system for artifact elimination processing according to claim 3, characterized in that: The pressure detection mechanism includes multiple pressure detection units, which are used to respectively detect the current surface pressure values ​​of the elimination judgment device, the multiple generation components, the content acquisition mechanism and the processing execution mechanism. It also includes: the internal structures of multiple contact pressure sensors respectively used for the elimination judgment device, the multiple generation components, the content acquisition mechanism and the processing execution mechanism are the same.

5. The intelligent determination system for artifact elimination processing according to claim 3, characterized in that: The pressure detection mechanism includes multiple pressure detection units, which are used to respectively detect the current surface pressure values ​​of the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism. It also includes: multiple non-contact pressure sensors respectively used for the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism have the same pressure measurement upper limit threshold and pressure measurement lower limit threshold.

6. The intelligent determination system for artifact elimination processing according to claim 5, characterized in that: The pressure detection mechanism includes multiple pressure detection units, which are used to respectively detect the current surface pressure values ​​of the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism. It also includes: multiple contact pressure sensors respectively used for the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism all perform corresponding current surface pressure value detection based on the difference between the air pressure and the internal pressure of the detected device.

7. The intelligent determination system for artifact elimination processing according to claim 2, characterized in that: The system further comprises: The real-time warning mechanism is respectively connected to multiple contact pressure sensors respectively used for the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism, and is used to perform corresponding pressure warning operations based on the pressure measurement results of the multiple contact pressure sensors respectively used for the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism.

8. The intelligent determination system for artifact elimination processing according to claim 7, characterized in that: The real-time warning mechanism is respectively connected to multiple contact pressure sensors respectively used for the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism, and is used to perform corresponding pressure warning operations based on the pressure measurement results of the multiple contact pressure sensors respectively used for the elimination judgment device, the multiple generation component, the content acquisition mechanism and the processing execution mechanism. The real-time warning mechanism includes a timing analysis unit and a warning operation unit.

9. The intelligent determination system for artifact elimination processing according to claim 8, characterized in that: A real-time warning mechanism is respectively connected to a plurality of contact pressure sensors respectively used for the elimination judgment device, the batch generation component, the content acquisition mechanism and the processing execution mechanism, and is used to perform corresponding pressure warning operations based on the pressure measurement results of the plurality of contact pressure sensors respectively used for the elimination judgment device, the batch generation component, the content acquisition mechanism and the processing execution mechanism. It also includes: within the real-time warning mechanism, the timing analysis unit is connected to the warning operation unit.