Building monitoring image quality optimization system

Abstract

The invention relates to a building monitoring image quality optimization system, and the system comprises a floor capturing mechanism which is used for carrying out the directional image data capturing operation of a set floor, so as to obtain a directional floor image; the traversal selection mechanism is arranged at the big data server side and is used for intelligently analyzing various contrast ratios of a smoothed image obtained by performing smoothing operation on a content enhanced image obtained by performing optimization processing on the directional floor image by adopting various smoothing algorithms; and the algorithm screening mechanism is used for taking the smoothing algorithm corresponding to the contrast with the maximum numerical value as a target smoothing algorithm so as to perform smoothing operation on the content enhanced image. According to the invention, the smoothing algorithm corresponding to the contrast with the maximum value in the contrast obtained through intelligent analysis of various smoothing algorithms can be used as the target smoothing algorithm for executing the smoothing operation on the content-enhanced image obtained after the customized upgrading processing of the directional floor image; therefore, the picture quality of the floor monitoring image is improved.

Description

Technical Field

[0001] The present invention relates to the field of building monitoring, and in particular to a building monitoring image quality optimization system. Background Art

[0002] Image quality optimization is an issue that needs to be addressed and focused on in every application scenario that performs screen monitoring or image monitoring. For example, for game image quality, there are many game image quality optimization software recommendations that give users a particularly good experience. The software functions are particularly powerful, helping users to enjoy the highest image quality without lag, giving players the best game image quality experience. Obviously, image quality optimization in other application scenarios can also give users and monitors a better experience.

[0003] Currently, floor monitoring images need to be smoothed to improve the contrast of the final output and displayed images. However, there are various types of smoothing algorithms in image processing. For each monitoring image acquired in time-sharing, due to the change in content, it is difficult to determine which smoothing algorithm is most suitable for each monitoring image, resulting in the final smoothed image often not having the best contrast-enhanced picture content.

[0004] The technology of image smoothing processing has been disclosed in public documents. For example, the invention with application publication number CN113996499A discloses an intelligent positioning system for an automated industrial dispensing robot, including an image acquisition drive module, an image acquisition module, an image processing module, a visual positioning module and a dispensing module. The image acquisition drive module is used to drive the image acquisition module, the image acquisition module is used to acquire the target image, the image processing module is used to process the target image so that the processed target image can be intelligently positioned, and the visual positioning module is used to locate and capture the target image. When the invention is used, the image smoothing processing unit and the binarization processing unit are set in the image processing module to pre-process the acquired target image, and then the morphological processing unit and the center coordinate extraction unit are used to extract the dispensing position coordinates. Summary of the invention

[0005] In order to solve the technical problems in the related fields, the present invention provides a building monitoring image quality optimization system, the system comprising: An operation detection mechanism is connected to the motor of the elevator on the set floor of the shopping mall, and is used to determine the current operation state of the elevator based on the rotation speed of the motor, and the current operation state of the elevator includes a stop state and a start state; A floor capture mechanism is arranged at the elevator exit end of a set floor of the shopping mall and is connected to the operation detection mechanism, and is used to perform a directional image data capture operation on the set floor when the current operation state of the elevator is the departure state, so as to obtain and output a corresponding directional floor image; A smoothing device, which is arranged at the big data server end of the supermarket and connected to the floor capture mechanism, is used to perform a non-scaling transformation blur process on the received directional floor image to obtain and output a corresponding smoothed image; A tilt correction device, connected to the smoothing device, for performing a tilt correction process on the received smoothing image to obtain and output a corresponding tilt correction image; a content enhancement device, connected to the tilt correction device, for performing image SVD enhancement processing on the received tilt-corrected image to obtain and output a corresponding content-enhanced image; A traversal selection mechanism is arranged at the big data server end of the supermarket and connected to the content enhancement device. The traversal selection mechanism includes a channel analysis unit, a noise analysis unit, a model building unit and a smooth prediction unit. The smooth prediction unit is connected to the channel analysis unit, the noise analysis unit and the model building unit respectively. The traversal selection mechanism is used to determine the color channel values ​​corresponding to each pixel of the content enhancement image, analyze the maximum noise amplitude, the minimum noise amplitude and the number of pixels occupied by the background area of ​​the content enhancement image, and intelligently analyze the contrast of the smoothed image obtained after the current smoothing algorithm is used to perform a smoothing operation on the content enhancement image according to the binary value of the algorithm code corresponding to the current smoothing algorithm, the color channel values ​​corresponding to each pixel of the content enhancement image, the maximum noise amplitude, the minimum noise amplitude and the number of pixels occupied by the background area of ​​the content enhancement image. The intelligent analysis uses a feedforward neural network model, and the number of training times of the feedforward neural network model is positively correlated with the maximum noise amplitude of the content enhancement image. an algorithm screening mechanism, connected to the traversal selection mechanism, for using the smoothing algorithm corresponding to the contrast with the largest value among the contrasts obtained by intelligent analysis of various smoothing algorithms as a target smoothing algorithm for performing a smoothing operation on the content-enhanced image, so as to obtain a display image to be displayed on the giant screen display mechanism of the big data server end of the supermarket; Among them, various smoothing algorithms include a non-scaling transformation fuzzy algorithm, a median fuzzy algorithm, a Gaussian fuzzy algorithm, and a bilateral filtering fuzzy algorithm.

[0006] A building monitoring image quality optimization system provided by the present invention can use the smoothing algorithm corresponding to the contrast with the largest value in each contrast obtained by intelligent analysis of various smoothing algorithms as the target smoothing algorithm to perform a smoothing operation on the content enhanced image obtained after customized quality improvement processing of the directional floor image, so as to obtain a display image to be displayed on the giant screen display mechanism of the big data server end of the supermarket, thereby improving the picture quality of the floor monitoring image. DETAILED DESCRIPTION

[0007] The following is a detailed description of an embodiment of the building monitoring image quality optimization system of the present invention.

[0008] First embodiment

[0009] According to a first embodiment of the present invention, a system for optimizing image quality of a building monitoring image is shown, and the system comprises: An operation detection mechanism is connected to the motor of the elevator on the set floor of the shopping mall, and is used to determine the current operation state of the elevator based on the rotation speed of the motor, and the current operation state of the elevator includes a stop state and a start state; For example, the operation detection mechanism is connected to the motor of the elevator on the set floor of the shopping mall, and is used to determine the current operation state of the elevator based on the rotation speed of the motor, and the current operation state of the elevator includes the stop state and the start state, including: the motor is a brushless DC motor; A floor capture mechanism is arranged at the elevator exit end of a set floor of the shopping mall and is connected to the operation detection mechanism, and is used to perform a directional image data capture operation on the set floor when the current operation state of the elevator is the departure state, so as to obtain and output a corresponding directional floor image; A smoothing device, which is arranged at the big data server end of the supermarket and connected to the floor capture mechanism, is used to perform a non-scaling transformation blur process on the received directional floor image to obtain and output a corresponding smoothed image; A tilt correction device, connected to the smoothing device, for performing a tilt correction process on the received smoothing image to obtain and output a corresponding tilt correction image; a content enhancement device, connected to the tilt correction device, for performing image SVD enhancement processing on the received tilt-corrected image to obtain and output a corresponding content-enhanced image; A traversal selection mechanism is arranged at the big data server end of the supermarket and connected to the content enhancement device. The traversal selection mechanism includes a channel analysis unit, a noise analysis unit, a model building unit and a smooth prediction unit. The smooth prediction unit is connected to the channel analysis unit, the noise analysis unit and the model building unit respectively. The traversal selection mechanism is used to determine the color channel values ​​corresponding to each pixel of the content enhancement image, analyze the maximum noise amplitude, the minimum noise amplitude and the number of pixels occupied by the background area of ​​the content enhancement image, and intelligently analyze the contrast of the smoothed image obtained after the current smoothing algorithm is used to perform a smoothing operation on the content enhancement image according to the binary value of the algorithm code corresponding to the current smoothing algorithm, the color channel values ​​corresponding to each pixel of the content enhancement image, the maximum noise amplitude, the minimum noise amplitude and the number of pixels occupied by the background area of ​​the content enhancement image. The intelligent analysis uses a feedforward neural network model, and the number of training times of the feedforward neural network model is positively correlated with the maximum noise amplitude of the content enhancement image. an algorithm screening mechanism, connected to the traversal selection mechanism, for using the smoothing algorithm corresponding to the contrast with the largest value among the contrasts obtained by intelligent analysis of various smoothing algorithms as a target smoothing algorithm for performing a smoothing operation on the content-enhanced image, so as to obtain a display image to be displayed on the giant screen display mechanism of the big data server end of the supermarket; Among them, various smoothing algorithms include non-scaling transformation fuzzy algorithm, median fuzzy algorithm, Gaussian fuzzy algorithm and bilateral filtering fuzzy algorithm; The floor capture mechanism is further used to stop the directional image data capture operation performed on the set floor when the current operating state of the elevator is a shutdown state; Among them, the operation detection mechanism is connected to the motor of the elevator on the set floor of the shopping mall, and is used to determine the current operating state of the elevator based on the rotational speed of the motor. The current operating state of the elevator includes a stop state and a start state. When the rotational speed of the motor is less than the set speed limit, the current operating state of the elevator is determined to be a stop state.

[0010] Second embodiment

[0011] According to a second embodiment of the present invention, a building monitoring image quality optimization system is shown, which may include: An operation detection mechanism is connected to the motor of the elevator on the set floor of the shopping mall, and is used to determine the current operation state of the elevator based on the rotation speed of the motor, and the current operation state of the elevator includes a stop state and a start state; A floor capture mechanism is arranged at the elevator exit end of a set floor of the shopping mall and is connected to the operation detection mechanism, and is used to perform a directional image data capture operation on the set floor when the current operation state of the elevator is the departure state, so as to obtain and output a corresponding directional floor image; A smoothing device, which is arranged at the big data server end of the supermarket and connected to the floor capture mechanism, is used to perform a non-scaling transformation blur process on the received directional floor image to obtain and output a corresponding smoothed image; A tilt correction device, connected to the smoothing device, for performing a tilt correction process on the received smoothing image to obtain and output a corresponding tilt correction image; a content enhancement device, connected to the tilt correction device, for performing image SVD enhancement processing on the received tilt-corrected image to obtain and output a corresponding content-enhanced image; A traversal selection mechanism is arranged at the big data server end of the supermarket and connected to the content enhancement device. The traversal selection mechanism includes a channel analysis unit, a noise analysis unit, a model building unit and a smooth prediction unit. The smooth prediction unit is connected to the channel analysis unit, the noise analysis unit and the model building unit respectively. The traversal selection mechanism is used to determine the color channel values ​​corresponding to each pixel of the content enhancement image, analyze the maximum noise amplitude, the minimum noise amplitude and the number of pixels occupied by the background area of ​​the content enhancement image, and intelligently analyze the contrast of the smoothed image obtained after the current smoothing algorithm is used to perform a smoothing operation on the content enhancement image according to the binary value of the algorithm code corresponding to the current smoothing algorithm, the color channel values ​​corresponding to each pixel of the content enhancement image, the maximum noise amplitude, the minimum noise amplitude and the number of pixels occupied by the background area of ​​the content enhancement image. The intelligent analysis uses a feedforward neural network model, and the number of training times of the feedforward neural network model is positively correlated with the maximum noise amplitude of the content enhancement image. an algorithm screening mechanism, connected to the traversal selection mechanism, for using the smoothing algorithm corresponding to the contrast with the largest value among the contrasts obtained by intelligent analysis of various smoothing algorithms as a target smoothing algorithm for performing a smoothing operation on the content-enhanced image, so as to obtain a display image to be displayed on the giant screen display mechanism of the big data server end of the supermarket; a thickness sensor, connected to the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism, respectively, for measuring the current real-time thickness values ​​of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism; Wherein, the thickness sensor device is respectively connected with the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism, and is used to respectively measure the current real-time thickness values ​​of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism, including: the thickness sensor device includes a plurality of thickness measurement units, which are respectively connected with the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism, so as to complete the measurement of the current real-time thickness values ​​of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism; Wherein, the thickness sensor device comprises a plurality of thickness measuring units, which are respectively connected to the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism to complete the respective measurement of the current real-time thickness values ​​of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism, including: the plurality of thickness measuring units are a plurality of thickness sensors, which are respectively connected to the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism to complete the respective measurement of the current real-time thickness values ​​of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism; Wherein, the plurality of thickness measuring units are a plurality of thickness sensors, which are used to be connected to the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism respectively, so as to complete the respective measurement of the current real-time thickness values ​​of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism respectively, including: the plurality of thickness sensors have the same structure; Among them, the multiple thickness measuring units are multiple thickness sensors, which are used to be connected to the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism respectively, so as to complete the respective measurements of the current real-time thickness values ​​of the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism, and also include: the multiple thickness sensors have the same thickness measurement upper limit value and thickness measurement lower limit value.

[0012] Third embodiment

[0013] According to the third embodiment of the present invention, a system for optimizing image quality of a building monitoring image is shown, which may include: An operation detection mechanism is connected to the motor of the elevator on the set floor of the shopping mall, and is used to determine the current operation state of the elevator based on the rotation speed of the motor, and the current operation state of the elevator includes a stop state and a start state; A floor capture mechanism is arranged at the elevator exit end of a set floor of the shopping mall and is connected to the operation detection mechanism, and is used to perform a directional image data capture operation on the set floor when the current operation state of the elevator is the departure state, so as to obtain and output a corresponding directional floor image; A smoothing device, which is arranged at the big data server end of the supermarket and connected to the floor capture mechanism, is used to perform a non-scaling transformation blur process on the received directional floor image to obtain and output a corresponding smoothed image; A tilt correction device, connected to the smoothing device, for performing a tilt correction process on the received smoothing image to obtain and output a corresponding tilt correction image; a content enhancement device, connected to the tilt correction device, for performing image SVD enhancement processing on the received tilt-corrected image to obtain and output a corresponding content-enhanced image; A traversal selection mechanism is arranged at the big data server end of the supermarket and connected to the content enhancement device. The traversal selection mechanism includes a channel analysis unit, a noise analysis unit, a model building unit and a smooth prediction unit. The smooth prediction unit is connected to the channel analysis unit, the noise analysis unit and the model building unit respectively. The traversal selection mechanism is used to determine the color channel values ​​corresponding to each pixel of the content enhancement image, analyze the maximum noise amplitude, the minimum noise amplitude and the number of pixels occupied by the background area of ​​the content enhancement image, and intelligently analyze the contrast of the smoothed image obtained after the current smoothing algorithm is used to perform a smoothing operation on the content enhancement image according to the binary value of the algorithm code corresponding to the current smoothing algorithm, the color channel values ​​corresponding to each pixel of the content enhancement image, the maximum noise amplitude, the minimum noise amplitude and the number of pixels occupied by the background area of ​​the content enhancement image. The intelligent analysis uses a feedforward neural network model, and the number of training times of the feedforward neural network model is positively correlated with the maximum noise amplitude of the content enhancement image. an algorithm screening mechanism, connected to the traversal selection mechanism, for using the smoothing algorithm corresponding to the contrast with the largest value among the contrasts obtained by intelligent analysis of various smoothing algorithms as a target smoothing algorithm for performing a smoothing operation on the content-enhanced image, so as to obtain a display image to be displayed on the giant screen display mechanism of the big data server end of the supermarket; a temporary value storage mechanism, connected to the plurality of thickness measuring units of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism, respectively, and used for temporarily storing input data and output data of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism respectively; Wherein, the temporary value storage mechanism is respectively connected to the plurality of thickness measuring units of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism, and is used to temporarily store the input data and output data of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism respectively, including: the temporary value storage mechanism is a FLASH flash memory; Among them, the numerical temporary storage mechanism is respectively connected to the smoothing processing device, the tilt correction device, the content enhancement device and multiple thickness measurement units of the traversal selection mechanism, and is used to temporarily store the input data and output data of the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism respectively, including: the numerical temporary storage mechanism is an MMC storage chip.

[0014] In addition, in the building monitoring image quality optimization system, the operation detection mechanism is connected to the motor of the elevator on the set floor of the shopping mall, and is used to determine the current operation state of the elevator based on the rotation speed of the motor, and the current operation state of the elevator includes the stop state and the start state, and further includes: when the rotation speed of the motor is greater than or equal to the set rotation speed limit, determining that the current operation state of the elevator is the start state; And wherein, the operation detection mechanism is connected to the motor of the elevator on the set floor of the shopping mall, and is used to determine the current operating state of the elevator based on the rotational speed of the motor. The current operating state of the elevator includes a stopped state and a started state, and also includes: using a rotational speed measurement unit to measure the rotational speed of the motor.

[0015] Compared with the prior art, the technical solution of the present invention has the following significant improvements: (1) Introducing a traversal selection mechanism including a channel analysis unit, a noise analysis unit, a model building unit, and a smooth prediction unit, wherein the smooth prediction unit is connected to the channel analysis unit, the noise analysis unit, and the model building unit, respectively, so as to provide hardware resources for early prediction of the smoothing effect of the smoothing algorithm; (2) determining the values ​​of each color channel corresponding to each pixel of the content enhanced image, analyzing the maximum noise amplitude, the minimum noise amplitude and the number of pixels occupied by the background area of ​​the content enhanced image, and intelligently analyzing the contrast of the smoothed image obtained by smoothing the content enhanced image using the current smoothing algorithm according to the binary value of the algorithm code corresponding to the current smoothing algorithm, the values ​​of each color channel corresponding to each pixel of the content enhanced image, the maximum noise amplitude, the minimum noise amplitude and the number of pixels occupied by the background area of ​​the content enhanced image; (3) The intelligent analysis adopts a feedforward neural network model, and the number of training times of the feedforward neural network model is positively correlated with the maximum noise amplitude of the content enhanced image, thereby realizing a customized design of the structure of the feedforward neural network model; (4) The smoothing algorithm corresponding to the contrast with the largest value among the contrasts obtained by intelligent analysis of various smoothing algorithms is used as the target smoothing algorithm to perform a smoothing operation on the content enhanced image obtained after the customized quality improvement processing of the directional floor image, so as to obtain a display image to be displayed on the giant screen display mechanism of the big data server end of the supermarket, thereby improving the picture quality of the floor monitoring image.

[0016] The building monitoring image quality optimization system of the present invention solves the technical problem in the prior art that it is difficult to find a smoothing algorithm with the best contrast for the floor images of a shopping mall. The smoothing algorithm corresponding to the contrast with the largest value among the contrasts obtained by intelligent analysis of various smoothing algorithms is used as the target smoothing algorithm to perform smoothing operations on the content enhanced image obtained after customized quality improvement processing of the directional floor image, thereby improving the picture quality of the floor monitoring image.

[0017] Many details of the present invention may be changed without departing from its spirit and scope. In addition, the description of the preferred embodiments of the present invention is provided for illustrative purposes only, not for limiting the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A building monitoring image quality optimization system, It is characterized in that The system comprises: An operation detection mechanism is connected to the motor of the elevator on the set floor of the shopping mall, and is used to determine the current operation state of the elevator based on the rotation speed of the motor, and the current operation state of the elevator includes a stop state and a start state; A floor capture mechanism is arranged at the elevator exit end of a set floor of the shopping mall and is connected to the operation detection mechanism, and is used to perform a directional image data capture operation on the set floor when the current operation state of the elevator is the departure state, so as to obtain and output a corresponding directional floor image; A smoothing device, which is arranged at the big data server end of the supermarket and connected to the floor capture mechanism, is used to perform a non-scaling transformation blur process on the received directional floor image to obtain and output a corresponding smoothed image; A tilt correction device, connected to the smoothing device, for performing a tilt correction process on the received smoothing image to obtain and output a corresponding tilt correction image; a content enhancement device, connected to the tilt correction device, for performing image SVD enhancement processing on the received tilt-corrected image to obtain and output a corresponding content-enhanced image; A traversal selection mechanism is arranged at the big data server end of the supermarket and connected to the content enhancement device. The traversal selection mechanism includes a channel analysis unit, a noise analysis unit, a model building unit and a smooth prediction unit. The smooth prediction unit is connected to the channel analysis unit, the noise analysis unit and the model building unit respectively. The traversal selection mechanism is used to determine the color channel values ​​corresponding to each pixel of the content enhancement image, analyze the maximum noise amplitude, the minimum noise amplitude and the number of pixels occupied by the background area of ​​the content enhancement image, and intelligently analyze the contrast of the smoothed image obtained after the current smoothing algorithm is used to perform a smoothing operation on the content enhancement image according to the binary value of the algorithm code corresponding to the current smoothing algorithm, the color channel values ​​corresponding to each pixel of the content enhancement image, the maximum noise amplitude, the minimum noise amplitude and the number of pixels occupied by the background area of ​​the content enhancement image. The intelligent analysis uses a feedforward neural network model, and the number of training times of the feedforward neural network model is positively correlated with the maximum noise amplitude of the content enhancement image. an algorithm screening mechanism, connected to the traversal selection mechanism, for using the smoothing algorithm corresponding to the contrast with the largest value among the contrasts obtained by intelligent analysis of various smoothing algorithms as a target smoothing algorithm for performing a smoothing operation on the content-enhanced image, so as to obtain a display image to be displayed on the giant screen display mechanism of the big data server end of the supermarket; Among them, various smoothing algorithms include a non-scaling transformation fuzzy algorithm, a median fuzzy algorithm, a Gaussian fuzzy algorithm, and a bilateral filtering fuzzy algorithm.

2. The building monitoring image quality optimization system according to claim 1, Features: The floor capture mechanism is also used to stop the directional image data capture operation performed on the set floor when the current operating state of the elevator is a shutdown state; Among them, the operation detection mechanism is connected to the motor of the elevator on the set floor of the shopping mall, and is used to determine the current operating state of the elevator based on the rotational speed of the motor. The current operating state of the elevator includes a stop state and a start state. When the rotational speed of the motor is less than the set speed limit, the current operating state of the elevator is determined to be a stop state.

3. The building monitoring image quality optimization system as claimed in claim 2, It is characterized in that The system further comprises: a thickness sensor, connected to the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism, respectively, for measuring the current real-time thickness values ​​of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism; Among them, the thickness sensor device is respectively connected to the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism, and is used to respectively measure the current real-time thickness values ​​of the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism. The thickness sensor device includes multiple thickness measurement units, which are respectively connected to the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism to complete the respective measurements of the current real-time thickness values ​​of the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism.

4. The building monitoring image quality optimization system as claimed in claim 3, Features: The thickness sensor device includes a plurality of thickness measuring units, which are used to be respectively connected to the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism to complete the respective measurements of the current real-time thickness values ​​of the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism. The plurality of thickness measuring units are a plurality of thickness sensors, which are used to be respectively connected to the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism to complete the respective measurements of the current real-time thickness values ​​of the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism.

5. The building monitoring image quality optimization system as claimed in claim 4, Features: The multiple thickness measuring units are multiple thickness sensors, which are used to be connected to the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism respectively, so as to complete the respective measurements of the current real-time thickness values ​​of the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism, including: the structures of the multiple thickness sensors are the same.

6. The building monitoring image quality optimization system as claimed in claim 5, Features: The multiple thickness measuring units are multiple thickness sensors, which are used to be connected to the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism respectively to complete the respective measurements of the current real-time thickness values ​​of the smoothing processing device, the tilt correction device, the content enhancement device and the traversal selection mechanism, and also include: the multiple thickness sensors have the same thickness measurement upper limit value and thickness measurement lower limit value.

7. The building monitoring image quality optimization system according to any one of claims 3 to 6, It is characterized in that The system further comprises: The numerical temporary storage mechanism is respectively connected to the plurality of thickness measuring units of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism, and is used for temporarily storing the input data and output data of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism respectively.

8. The building monitoring image quality optimization system as claimed in claim 7, Features: The numerical temporary storage mechanism is respectively connected to the smoothing device, the tilt correction device, the content enhancement device and multiple thickness measurement units of the traversal selection mechanism, and is used to temporarily store the input data and output data of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism respectively, including: the numerical temporary storage mechanism is a FLASH flash memory.

9. The building monitoring image quality optimization system according to claim 7, Features: The numerical temporary storage mechanism is respectively connected to the smoothing device, the tilt correction device, the content enhancement device and the multiple thickness measurement units of the traversal selection mechanism, and is used to temporarily store the input data and output data of the smoothing device, the tilt correction device, the content enhancement device and the traversal selection mechanism respectively, including: the numerical temporary storage mechanism is an MMC storage chip.