CN115118887B - Automatic exposure method applied to domestic anti-radiation camera - Google Patents
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Abstract
The invention discloses an automatic exposure method applied to a domestic radiation-resistant camera, which comprises the following steps: constructing a characteristic point coordinate matrix of the image; collecting image data under different illumination conditions, selecting characteristic points in a frame of image according to the constructed characteristic point coordinate matrix, carrying out central key weighted average on the characteristic points, and calculating a weighted average WA; and comparing WA with an optimal threshold range [ TH min,THmax ] to reduce exposure time if WA > TH max indicates that the current image is an overexposed image and to increase exposure time if WA < TH min indicates that the current image is an underexposed image. The invention can enable the camera to adjust the exposure time parameter according to the light change, automatically adjust the brightness of the image, enable the image to have certain self-adaptive capacity and improve the image quality.
Description
Technical Field
The invention relates to an automatic exposure method applied to domestic anti-radiation cameras, in particular to an automatic exposure method which adopts an FPGA technology to process real-time video frames of the cameras and adjust exposure parameters of the cameras so as to achieve the aim of automatic exposure.
Background
In nuclear environments such as a nuclear power station, equipment needs to be monitored, and normal operation of instruments and equipment is guaranteed. And has higher nuclear radiation in the nuclear environment, the traditional camera can not bear the nuclear radiation with high dosage. Therefore, it is necessary to equip a dedicated radiation-resistant camera in a nuclear environment. The foreign radiation-resistant camera is high in price and is not beneficial to the mass application of the environments such as nuclear power stations. In view of this need, domestic radiation-resistant cameras have grown. The institute of photoelectric technology of the Chinese academy of sciences, beijing microelectronic technology institute and other units are working against localization of radiation cameras. However, due to the limitation of technical conditions, the domestic anti-radiation device has a large difference between the energy storage capacity and the calculation speed and the non-anti-radiation device, and the complicated calculation cannot be performed.
When the illumination conditions change, the camera needs to be exposed to light in order to see the image clearly. If overexposure occurs, the image is overall bright, possibly losing some high-brightness information; if the exposure is insufficient, the whole image is dark, and detailed information of the object is easy to be invisible. Under the nuclear environment, the manual exposure adjustment can not be realized, and the automatic exposure technology without manual intervention can meet the requirement of camera exposure.
In most of the conventional automatic exposure methods, a gray average value is calculated for the whole image by using a gray average value method, and the exposure parameters of the camera are adjusted by using the gray average value as a threshold value. However, the gray average value method only reflects the whole average value of the image, and when the difference between the target and the background of the image is large, the image cannot be correctly exposed. Still other algorithms, such as calculating the threshold of the image using histograms, entropy, or artificial intelligence based methods, are complex, require high hardware, have low processing speed, and are difficult to apply on a resource-limited platform.
The nuclear power station area is relatively fixed in position, the image type is single, and when an automatic exposure algorithm is designed, images of different scenes and different types are not required to be acquired, and only images with different brightness in the nuclear power station environment are required to be acquired. According to the observation habit of human eyes, the method sets the central area of the image as a key area, the automatic exposure algorithm applies higher weight to the central area, sets the peripheral area of the image as a non-key area, and applies lower weight to the peripheral area.
In order to ensure that the automatic exposure algorithm is only sensitive to light changes, is insensitive to suddenly-flashing objects, such as suddenly-walking people, high-energy light beams generated when equipment is started and stopped, or the situation that light contact is poor and light are alternately turned on and off, if the situations are exposed, images can always flash, and the images cannot be displayed correctly. In order to display the images correctly, the method adopts a delay exposure strategy, namely, a fixed time interval t is set, one frame of image is acquired at intervals of t, after three frames of images are acquired, if at least two frames in the three frames of images are images exceeding a threshold value, an automatic exposure process is started, and otherwise, the automatic exposure process is not started.
Disclosure of Invention
The technical solution of the invention is as follows: the method is based on a central key weighted average algorithm, the designed algorithm can be realized on an FPGA, and the problems that the existing automatic exposure method has high utilization rate of hardware resources, high time cost and difficulty in real-time application on a platform with limited resources are solved.
The technical scheme of the invention is as follows: an automatic exposure method applied to a domestic radiation-resistant camera comprises the following steps:
(1) The camera starts an automatic exposure function;
(2) Selecting representative M x N points in a frame of image to replace the whole image, and selecting coordinates of the M x N points to construct an image feature point coordinate matrix I (M, N);
(3) For any time T 1, calculating a central key weighted average WA 1、WA2、WA3 of pixel points corresponding to the input image feature point coordinate matrix I (M, N) at the time T 1, the time T 1 +t and the time T 1 +2t; t represents a specified time interval;
(4) Judging whether WA 1、WA2、WA3 is in the optimal threshold range [ TH min,THmax ], if more than two of the three images exceed the optimal threshold range, indicating that the current image is not a normally exposed image, entering a step (5), and executing an automatic exposure process; otherwise, the current image is an image with normal exposure, no processing is performed, and the step (3) is returned;
(5) Calculating a central key weighted average WA of an input image at the current moment, and acquiring the current set exposure time ET i of the camera;
(6) According to WA 1、WA2、WA3 and exposure time ET i, the camera is controlled to increase the exposure time or decrease the exposure time, so that automatic exposure is realized.
In the step (6), the specific determination process for increasing the exposure time is as follows: if WA is smaller than TH min and ET i<ETmax indicates that the camera is underexposed, increasing the exposure time to enable the exposure time ET i+1＝ETi +L of the next moment, wherein ET max is the maximum value of the exposure time supported by the camera, L is the step length of changing the exposure time, and returning to the step (5) after the execution is completed; otherwise, step (7) is entered.
In the step (6), the specific determination process for reducing the exposure time is as follows: (7) If WA > TH max and ET i>ETmin indicate that the camera is overexposed, reducing the exposure time, and enabling the exposure time ET i+1＝ETi -L at the next moment, wherein ET min is the minimum value of the exposure time supported by the camera, L is the step length of changing the exposure time, and returning to the step (5) after the execution is completed; otherwise, returning to the step (3).
The step lengthWhere g is the number of steps with adjustable exposure time.
And (3) the camera in the step (1) adopts a radiation-resistant camera, and the exposure time is controlled through upper computer software and FPGA software.
And (3) the camera in the step (1) is controlled by software, and the automatic exposure function is started by default after power-on initialization.
The camera in the step (1) controls the opening and closing of the automatic exposure function through the upper computer software, when the automatic exposure function is closed, the manual exposure is executed through the upper computer software, and when the automatic exposure function is opened, the manual exposure function of the upper computer software does not work.
The central emphasis weighted average algorithm in the step (3) is to apply more weight to the central region of interest of the human eye and less weight to the peripheral regions of less interest of the human eye when the weighted average is performed on one frame of the input image.
The specific process of the step (3) is as follows: dividing an image into a central area A 1 and a peripheral area A 2, and respectively calculating central emphasis weighted average WA 1、WA2、WA3 of pixel points corresponding to a coordinate matrix I (M, N) of the feature points of the input image at the time of T 1, the time of T 1 +t and the time of T 1 +2t according to a formula WA=lambda 1*A1+λ2*A2 based on a designed central emphasis weighted average algorithm; wherein λ 1、λ2 is the weighting coefficient.
The weighting coefficient λ 1 is greater than λ 2, and λ 1+λ2 =1.
Compared with the prior art, the invention has the beneficial effects that:
(1) Since the human eye is always interested in the central region of the image when viewing the image. Therefore, when the method calculates the image threshold, a higher weight is applied to the central area of the image, a lower weight is applied to the peripheral area of the image, and the image is weighted and averaged, so that the method has better exposure effect than the method of directly averaging the image;
(2) The method selects representative characteristic points in the image to replace the whole image, uses the characteristic points to participate in the calculation of the automatic exposure algorithm, does not need to store the whole image, greatly saves hardware resources, and ensures that the algorithm can be realized on an FPGA platform with limited resources.
(3) The method adopts a delay exposure strategy, when the calculation of an automatic exposure algorithm is carried out, three-taking two operation is adopted, namely three images with fixed time intervals are selected, weighted average values of the three images are calculated respectively, and if more than two images exceed the optimal threshold range, the automatic exposure is carried out.
Drawings
FIG. 1 is a schematic diagram showing the switching between the automatic exposure mode and the manual exposure mode according to the present invention.
FIG. 2 is a flow chart of the automatic exposure mode of the present invention.
Detailed Description
The invention discloses an automatic exposure method applied to a domestic radiation-resistant camera, which comprises the following steps:
(1) The camera starts an automatic exposure function;
(2) Selecting representative M x N points in a frame of image to replace the whole image, and selecting coordinates of the M x N points to construct an image feature point coordinate matrix I (M, N);
(3) For any time T 1, calculating a central key weighted average WA 1、WA2、WA3 of pixel points corresponding to the input image feature point coordinate matrix I (M, N) at the time T 1, the time T 1 +t and the time T 1 +2t; t represents a specified time interval;
(4) Judging whether WA 1、WA2、WA3 is in the optimal threshold range [ TH min,THmax ], if more than two of the three images exceed the optimal threshold range, indicating that the current image is not a normally exposed image, entering a step (5), and executing an automatic exposure process; otherwise, the current image is an image with normal exposure, no processing is performed, and the step (3) is returned;
(5) Calculating a central key weighted average WA of an input image at the current moment, and acquiring the current set exposure time ET i of the camera;
(6) According to WA 1、WA2、WA3 and exposure time ET i, the camera is controlled to increase the exposure time or decrease the exposure time, so that automatic exposure is realized. The specific determination process for increasing the exposure time is as follows: if WA is smaller than TH min and ET i<ETmax indicates that the camera is underexposed, increasing the exposure time to enable the exposure time ET i+1＝ETi +L of the next moment, wherein ET max is the maximum value of the exposure time supported by the camera, L is the step length of changing the exposure time, and returning to the step (5) after the execution is completed; otherwise, step (7) is entered. The specific determination process for reducing the exposure time is as follows: (7) If WA > TH max and ET i>ETmin indicate that the camera is overexposed, reducing the exposure time, and enabling the exposure time ET i+1＝ETi -L at the next moment, wherein ET min is the minimum value of the exposure time supported by the camera, L is the step length of changing the exposure time, and returning to the step (5) after the execution is completed; otherwise, returning to the step (3). The step length Where g is the number of steps with adjustable exposure time.
The camera adopts a radiation-resistant camera, and exposure time is controlled through upper computer software and FPGA software. The camera is controlled by software, the automatic exposure function is started by default after the camera is electrified and initialized, the automatic exposure function is controlled to be started and closed by the upper computer software, when the automatic exposure function is closed, the manual exposure is executed by the upper computer software, and when the automatic exposure function is started, the manual exposure function of the upper computer software does not work.
The central emphasis weighted average algorithm is that when a weighted average is carried out on an input frame of image, more weights are applied to a central area concerned by human eyes, and less weights are applied to peripheral areas which are not concerned by human eyes, and the specific process is as follows: dividing an image into a central area A 1 and a peripheral area A 2, and respectively calculating central emphasis weighted average WA 1、WA2、WA3 of pixel points corresponding to a coordinate matrix I (M, N) of the feature points of the input image at the time of T 1, the time of T 1 +t and the time of T 1 +2t according to a formula WA=lambda 1*A1+λ2*A2 based on a designed central emphasis weighted average algorithm; wherein λ 1、λ2 is the weighting coefficient. The weighting coefficient λ 1 is greater than λ 2, and λ 1+λ2 =1.
The specific implementation flow of the automatic exposure method applied to the domestic radiation-resistant camera is shown in fig. 1 and 2.
(1) The camera automatically starts the automatic exposure function after being powered on for the first time, or the automatic exposure function is selectively started on the upper computer software.
(2) In order to improve the processing speed, a designed automatic exposure algorithm can run on the FPGA to construct an image characteristic point coordinate matrix I (M, N). Let m=16, let n=16, and then m=n=256, i.e. 256 pixels in one frame of image are selected as feature points to replace the whole image. Since the PAL image has 720×576 pixels, if the selected feature points are representative, the PAL image can replace the whole image, and the feature points are uniformly distributed in the whole image, the feature point coordinates corresponding to the selected feature point coordinate matrix I (M, N) are (s×c, s×d), where
(3) Of the 256 feature points, 39% of the feature points are selected, and 100 feature points at the central position are used as key areas to calculate the average valueWherein n 1 = 100; selecting 61% of points, taking 156 feature points around as non-key areas, and calculating the average value/>Where n 2 = 156. According to the formula wa=λ 1*A1+λ2*A2, λ 1 =0.66, λ 2 =0.34, the central emphasis weighted average of the input image is calculated. Taking T 1 =0, t=400 ms, i.e. calculating the 0 moment, 400ms moment, 800ms moment, the central emphasis weighted average WA 1、WA2、WA3 of the input image.
(4) Judging whether WA 1、WA2、WA3 is in the optimal threshold range, if more than 2 WA's exceed the threshold range, entering step (5), executing the automatic exposure flow, otherwise, returning to step (3).
(5) And calculating a central key weighted average WA of a frame of image input at the current moment, and acquiring the exposure time ET i currently set by the camera.
(6) The exposure time range supported by the known radiation-resistant camera is [ ET min,ETmax ], according to the formulaCalculating the step length L of automatic exposure, wherein g is the number of steps with adjustable exposure time, and if g=15 is set, i.e. the exposure time can be adjusted by 15 steps, calculating the step length/> If WA is less than TH min and ET i<ETmax indicates that the camera is underexposed, increasing the exposure time to enable the exposure time ET i+1＝ETi +L at the next moment, and returning to the step (5) after the execution is completed; otherwise, step (7) is entered.
(7) If WA > TH max and ET i>ETmin indicate that the camera is overexposed, reducing the exposure time, enabling the exposure time ET i+1＝ETi -L at the next moment, and returning to the step (5) after the execution is completed; otherwise, returning to the step (3).
Although the present invention has been described with respect to the preferred embodiments, it is not intended to be limited thereto, and any person skilled in the art can make any possible variations and modifications to the technical solution of the present invention by using the technical matters disclosed above without departing from the spirit and scope of the present invention, so any simple modifications, equivalent variations and modifications to the above embodiments according to the technical matters of the present invention fall within the scope of the technical solution of the present invention.
Claims (5)
1. An automatic exposure method applied to a domestic radiation-resistant camera is characterized by comprising the following steps:
(1) The camera starts an automatic exposure function;
(2) Selecting representative M x N points in a frame of image to replace the whole image, and selecting coordinates of the M x N points to construct an image feature point coordinate matrix I (M, N);
(3) Calculating central key weighted average WA 1、WA2、WA3;T1 of pixel points corresponding to the coordinate matrix I (M, N) of the feature points of the input image at the moment T 1, the moment T 1 +t and the moment T 1 +2t to represent any moment, wherein T represents a designated time interval;
The central key weighted average algorithm in the step (3) refers to that when weighted average is carried out on an input frame of image, more weight is applied to a central area concerned by human eyes, and less weight is applied to peripheral areas which are not concerned by human eyes;
The specific process of the step (3) is as follows: dividing the image into a central area A 1 and a peripheral area A 2, and based on a designed central emphasis weighted average algorithm, performing a weighted average according to the formula Calculating central key weighted average WA 1、WA2、WA3 of pixel points corresponding to the coordinate matrix I (M, N) of the feature points of the input image at the moment T 1, the moment T 1 +t and the moment T 1 +2t respectively; wherein,For the weighting coefficient/>
The weighting coefficient；
(4) Judging whether WA 1、WA2、WA3 is in the optimal threshold range [ TH min,THmax ], if more than two of the three images exceed the optimal threshold range, indicating that the current image is not a normally exposed image, entering a step (5), and executing an automatic exposure process; otherwise, the current image is an image with normal exposure, no processing is performed, and the step (3) is returned;
(5) Calculating a central key weighted average WA of an input image at the current moment, and acquiring the current set exposure time ET i of the camera;
(6) According to WA 1、WA2、WA3 and exposure time ET i, controlling a camera to increase the exposure time or decrease the exposure time, so as to realize automatic exposure;
In the step (6), the specific determination process for increasing the exposure time is as follows: if WA is smaller than TH min and ET i< ETmax indicates that the camera is underexposed, increasing the exposure time to enable the exposure time ET i+1 = ETi +L of the next moment, wherein ET max is the maximum value of the exposure time supported by the camera, L is the step length of changing the exposure time, and returning to the step (5) after the execution is completed; otherwise, entering step (7);
In the step (6), the specific determination process for reducing the exposure time is as follows: (7) If WA > TH max and ET i> ETmin indicate that the camera is overexposed, reducing the exposure time, and enabling the exposure time ET i+1 = ETi -L at the next moment, wherein ET min is the minimum value of the exposure time supported by the camera, L is the step length of changing the exposure time, and returning to the step (5) after the execution is completed; otherwise, returning to the step (3).
2. The automatic exposure method applied to the domestic radiation-resistant camera according to claim 1, wherein the method comprises the following steps: the saidWhere g is the number of steps with adjustable exposure time.
3. The automatic exposure method applied to the domestic radiation-resistant camera according to claim 1, wherein the method comprises the following steps: and (3) the camera in the step (1) adopts a radiation-resistant camera.
4. The automatic exposure method applied to the domestic radiation-resistant camera according to claim 1, wherein the method comprises the following steps: and (3) the camera in the step (1) is controlled by software, and the automatic exposure function is started by default after power-on initialization.
5. The automatic exposure method applied to the domestic radiation-resistant camera according to claim 4, wherein the method comprises the following steps: the camera in the step (1) controls the opening and closing of the automatic exposure function through the upper computer software, when the automatic exposure function is closed, the manual exposure is executed through the upper computer software, and when the automatic exposure function is opened, the manual exposure function of the upper computer software does not work.
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