CN117714674A - Dynamic dead pixel detection method and terminal based on exposure time and temperature compensation - Google Patents
Dynamic dead pixel detection method and terminal based on exposure time and temperature compensation Download PDFInfo
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Abstract
The invention discloses a dynamic dead pixel detection method and a terminal based on exposure time and temperature compensation, wherein the method comprises the following steps: acquiring exposure time, sensor temperature and shooting mode of a camera and generating exposure compensation quantity and temperature compensation quantity; calculating the difference value between the detected pixel point and the neighborhood pixel point and the gradient values in the four directions of horizontal, vertical, 45 degrees and 135 degrees, and generating a self-adaptive dead pixel discriminant by combining the exposure compensation quantity and the temperature compensation quantity; and carrying out dead pixel judgment on the detected pixel point by utilizing the self-adaptive dead pixel judgment formula and outputting a judgment result. According to the invention, the dead pixel judgment conditions are adaptively adjusted according to the exposure time of the camera, the temperature of the sensor and the shooting mode, and the dead pixel judgment conditions are generated, so that the influence of the exposure time shot by the camera and the temperature of the sensor on the dead pixel detection is weakened, the accuracy of the dead pixel detection is improved, a good dead pixel correction effect can be achieved under the long exposure condition, and the dead pixel misjudgment and missing judgment are reduced.
Description
Technical neighborhood
The invention relates to an image processing neighborhood, in particular to a dynamic dead point detection method and a terminal based on exposure time and temperature compensation.
Background
Because of the defects of the process technology of the photosensitive chip or the chip defects caused by long-term use and errors in the process of optical signal conversion, the information of certain pixel points of an image is wrong, the pixel values are deviated, and the defective pixel points are called dead pixels in the industry.
The dead pixel comprises a static dead pixel and a dynamic dead pixel, wherein the static dead pixel is caused by a chip defect of an image sensor technology and is mainly corrected through a static dead pixel table; and the dynamic dead pixels are related to the temperature and the exposure time of the sensor, and the higher the temperature is, the longer the exposure time is, and the more dead pixels are.
The dynamic dead pixel is required to compare the relation between the pixel to be detected and the rest of the neighborhood to judge whether the pixel is dead pixel or not, and then correcting the dead pixel in a certain mode. However, the conventional dynamic dead pixel detection technology does not consider the influence of temperature or exposure time, and the dead pixel missing judgment and misjudgment under long exposure are more, so that the defects of image edges and details or the bad pixel removal effect are easy to cause.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: the dynamic dead pixel detection method and the terminal based on exposure time and temperature compensation are provided, and the problem that the dynamic dead pixel detection is misjudged or missed is more is solved.
In order to solve the technical problems, the invention adopts the following technical scheme:
a dynamic dead pixel detection method based on exposure time and temperature compensation comprises the following steps:
s1, acquiring exposure time, sensor temperature and shooting mode of a camera and generating exposure compensation quantity and temperature compensation quantity;
s2, generating a self-adaptive dead pixel discriminant according to the exposure compensation quantity and the temperature compensation quantity;
and S3, performing dead pixel judgment on the detected pixel point by utilizing the self-adaptive dead pixel discriminant, and outputting a judgment result.
In order to solve the technical problems, the invention adopts another technical scheme that:
a dynamic dead-spot detection terminal based on exposure time and temperature compensation, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor performing the following steps when executing the computer program:
s1, acquiring exposure time, sensor temperature and shooting mode of a camera and generating exposure compensation quantity and temperature compensation quantity;
s2, generating a self-adaptive dead pixel discriminant according to the exposure compensation quantity and the temperature compensation quantity;
and S3, performing dead pixel judgment on the detected pixel point by utilizing the self-adaptive dead pixel discriminant, and outputting a judgment result.
The invention has the beneficial effects that: the method and the terminal for detecting the dynamic dead pixel based on the exposure time and the temperature compensation are provided, dead pixel judging conditions are adaptively adjusted according to the exposure time, the sensor temperature and the shooting mode of a camera, dead pixel judging conditions are generated, the influence of the exposure time and the sensor temperature shot by the camera on the dead pixel detection is weakened, the accuracy of the dead pixel detection is improved, a good dead pixel correcting effect can be achieved under the long exposure condition, and dead pixel misjudgment and missing judgment are reduced.
Drawings
FIG. 1 is a flow chart of a dynamic dead point detection method based on exposure time and temperature compensation in an embodiment of the invention;
FIG. 2 is a flowchart of a dynamic dead point detection method based on exposure time and temperature compensation according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a third-order window of a dynamic dead pixel detection method based on exposure time and temperature compensation in an embodiment of the invention;
fig. 4 is a schematic diagram of a dynamic dead-spot detection terminal based on exposure time and temperature compensation in an embodiment of the invention.
Description of the reference numerals:
1. dynamic dead pixel detection terminal based on exposure time and temperature compensation; 2. a memory;
3. a processor.
Detailed Description
In order to describe the technical contents, the achieved objects and effects of the present invention in detail, the following description will be made with reference to the embodiments in conjunction with the accompanying drawings.
Referring to fig. 1 to 3, a dynamic dead point detection method based on exposure time and temperature compensation includes the steps of:
s1, acquiring exposure time, sensor temperature and shooting mode of a camera and generating exposure compensation quantity and temperature compensation quantity;
s2, generating a self-adaptive dead pixel discriminant according to the exposure compensation quantity and the temperature compensation quantity;
and S3, performing dead pixel judgment on the detected pixel point by utilizing the self-adaptive dead pixel discriminant, and outputting a judgment result.
From the above description, the beneficial effects of the invention are as follows: the method for detecting the dynamic dead pixel based on the exposure time and the temperature compensation is provided, the dead pixel judging conditions are adaptively adjusted according to the exposure time, the sensor temperature and the shooting mode of the camera, the dead pixel judging formula is generated, the influence of the exposure time shot by the camera and the sensor temperature on the dead pixel detection is weakened, the accuracy of the dead pixel detection is improved, a good dead pixel correcting effect can be achieved under the long exposure condition, and the dead pixel misjudging and the missing judging are reduced.
In some embodiments of the present invention, the exposure compensation amount calculation formula is as follows:
wherein:
exp_comp is expressed as an exposure compensation amount;
k_exp is expressed as an exposure proportionality coefficient, and is a numerical interval for controlling exposure compensation amount;
cur_exp is expressed as exposure time;
comp_para is expressed as a shooting mode compensation coefficient, and the shooting modes include an HDR mode, a HighGain mode, and a LowGain mode;
the calculation formula of the temperature compensation quantity is as follows:
wherein:
temp_comp is expressed as a temperature compensation amount;
k_temp is expressed as a temperature proportionality coefficient, and is a numerical interval for controlling the temperature compensation amount;
P 0 expressed as a reference gray value at a reference temperature;
sen—temp is expressed as sensor temperature;
tempori is expressed as the reference temperature of the camera, which is positively correlated with the camera usage time.
As can be seen from the above description, in order to reduce the influence of the exposure time and the sensor temperature on the dead pixel judgment, the exposure compensation amount and the temperature compensation amount are controlled by introducing the exposure proportionality coefficient and the temperature proportionality coefficient, respectively, and the exposure compensation amount and the temperature compensation amount are calculated in combination with the photographing mode of the camera.
Specifically, the photographing modes can be classified into three modes of HDR (high dynamic range), highGain (high gain), and LowGain (low gain), and the compensation coefficient cmop_para is set according to the modes, specifically as follows:
1) HDR mode: comp_para=comp_para_hdr;
2) HighGain mode: comp_para=comp_para_h;
3) LowGain mode: comp_para=comp_para_l.
In some embodiments of the present invention, the step S2 specifically includes:
s21, respectively calculating the difference value between the neighborhood pixel point and the detected pixel point in a third-order window (please refer to fig. 3 for the arrangement situation of the third-order window pixel points) and the gradient values in four directions of horizontal, vertical, 45 degrees and 135 degrees by taking the detected pixel point as a center, wherein the calculation formula is as follows:
the calculation formula of the difference value between the detected pixel point and each pixel point in the neighborhood is as follows:
sub_p i ＝P 5 -P i ,i∈[1,9]&i≠5；
wherein:
sub_p i the difference value is expressed as the difference value between the detected pixel point and the surrounding ith neighborhood pixel point;
P i expressed as the gray value of the ith pixel point, P 5 A gray value expressed as a detected pixel;
the calculation formula of the horizontal gradient value grad_hor is:
grad_hor＝abs(P 6 -P 4 )；
the calculation formula of the vertical gradient value grad_ver is:
grad_ver＝abs(P 8 -P 2 )；
the calculation formula of the 45 DEG gradient value grad_45 is:
grad_45＝abs(P 3 -P 7 )；
the calculation formula of the 135 ° gradient value grad_135 is:
grad_135＝abs(P 1 -P 9 )；
from the above description, taking the detected pixel as the center, taking the difference value between the neighborhood pixel and the detected pixel in the size of the third-order window into consideration, and comprehensively evaluating the gradient change condition of the detected point;
s22, generating an adaptive dead pixel discriminant according to the difference value, the gradient value, the exposure compensation amount and the temperature compensation amount, wherein the adaptive dead pixel discriminant is expressed as follows:
or (b)
abs(sub_p i )＞detect_ratio*offset+comp,i∈[1,9]&i≠5；
comp＝exp_comp+temp_comp；
Wherein:
sub_grad is expressed as the difference between the maximum and minimum of the four directional gradient values;
max_th is represented as a preset gradient threshold value;
the detection_ratio is expressed as a preset dead pixel detection coefficient;
the offset is expressed as the difference between the next largest value and the next smallest value in the pixel values of the neighborhood pixel points;
comp is expressed as the integrated compensation amount.
From the above description, the difference value between the detected pixel point and the field pixel point, the gradient information in four directions and the compensation for the exposure time of the camera and the temperature of the sensor are comprehensively considered, so as to generate a self-adaptive dead pixel discriminant, and improve the discriminant accuracy of the dynamic dead pixel.
Specifically, the preset gradient threshold value max_th and the preset dead pixel detection coefficient detect_ratio are set according to the dead pixel correction intensity and the shooting mode of the actual requirement, and the principle is that: the change coefficients of the gray values of the images with the exposure time in different shooting modes are different, for example, the following: the dead pixel correction intensity is divided into three levels, and the three levels are divided as follows:
1) Dead pixel correction intensity=1, detect_ratio=ratio1, max_th=max_th1;
2) Dead pixel correction intensity=2, detect_ratio=ratio2, max_th=max_th2;
3) Dead pixel correction intensity=3, detection_ratio=ratio3, max_th=max_th3.
In some embodiments of the present invention, the step S3 specifically includes:
and carrying out dead pixel judgment on the detected pixel point by using the self-adaptive dead pixel discriminant, and if any discriminant in the self-adaptive discriminant is met, considering the detected pixel point as a dead pixel.
As can be seen from the above description, if the data of the detected pixel point satisfies any one of the adaptive discriminants, it is indicated that the detected pixel point is a dead pixel, and the principle thereof is that: according to the parameters in the self-adaptive discriminant, a first discriminant in the discriminant detects a flat region in an image, a second discriminant in the discriminant detects an edge region in the image, and edge information of the image is reserved, namely, the algorithm in the invention adopts different judging conditions for the flat region and the edge region of the image, so that image details can be reserved well, image quality is improved, the algorithm is simple to realize, the calculated amount is small, and the occupied resources are small.
Specifically, in order to facilitate the detection of the dead pixel on the image edge, step S1 further includes step S0, specifically:
the image shot by the camera is acquired, and the image boundary is expanded, for example, as follows: if the image size is h×m. The size of the image after expansion processing is (H+X) ×M+X, X is a preset image expansion factor, the value range of X is between 2 and 10 pixel points, preferably 2 pixel points, and the operation amount during dead pixel judgment is prevented from being increased.
In some embodiments of the present invention, the step S3 further includes:
if the detected pixel point is judged to be a dead point, weighting correction is carried out by using the pixel value of the neighborhood pixel point;
the weighting correction by using the pixel values of the neighborhood pixel points is as follows:
calculating the median value of the neighborhood pixel points, and generating the absolute value of the difference value between the neighborhood pixel points and the median value;
generating the weight of each neighborhood pixel according to the absolute value of the difference value between the field pixel and the median value, and correcting the detected pixel by using the weight of each pixel;
the expression is as follows:
sub_median_P i ＝abs(P i -median_P),i∈[1,9]&i≠5；
namely, calculating median_P of 8 neighborhood pixels around the detected pixel point, and calculating the absolute value of the difference between the values of the 8 neighborhood pixels around and the median;
namely, the weights of 8 neighborhood pixel points around the detected pixel point are calculated, so that the subsequent weighted calculation is convenient;
wherein:
media_P is expressed as the median value of the surrounding neighborhood pixel points of the detected pixel point;
sub_median_P i the absolute value of the difference value between the pixel point and the median value in the field;
weight i the weight value of the surrounding neighborhood pixel points expressed as the detected pixel points;
p_calib is represented as a correction value of the detected pixel point.
Referring to fig. 4, a dynamic dead point detection terminal 1 based on exposure time and temperature compensation includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3, wherein the processor 3 executes the computer program to perform the following steps:
s1, acquiring exposure time, sensor temperature and shooting mode of a camera and generating exposure compensation quantity and temperature compensation quantity;
s2, generating a self-adaptive dead pixel discriminant according to the exposure compensation quantity and the temperature compensation quantity;
and S3, performing dead pixel judgment on the detected pixel point by utilizing the self-adaptive dead pixel discriminant, and outputting a judgment result.
As can be seen from the above description, an execution carrier of a dynamic dead pixel detection method based on exposure time and temperature compensation is provided, when steps in the method are operated, dead pixel judgment conditions are adaptively adjusted according to the exposure time, the sensor temperature and the shooting mode of a camera, and dead pixel judgment formulas are generated, so that the influence of the exposure time and the sensor temperature of the camera on the dead pixel detection is weakened, the accuracy of the dead pixel detection is improved, a good dead pixel correction effect can be still achieved under the long exposure condition, and dead pixel misjudgment and missing judgment are reduced.
The invention provides a dynamic dead pixel detection method and a terminal based on exposure time and temperature compensation, which are mainly applied to detection of dynamic dead pixels, and are specifically described below with reference to embodiments:
referring to fig. 1 to 3, a first embodiment of the present invention is as follows:
a dynamic dead pixel detection method based on exposure time and temperature compensation comprises the following steps:
s1, acquiring exposure time, sensor temperature and shooting mode of a camera and generating exposure compensation quantity and temperature compensation quantity;
s2, generating a self-adaptive dead pixel discriminant according to the exposure compensation quantity and the temperature compensation quantity;
and S3, performing dead pixel judgment on the detected pixel point by utilizing the self-adaptive dead pixel discriminant, and outputting a judgment result.
In this embodiment, the dead pixel judgment conditions are adaptively adjusted according to the exposure time, the sensor temperature and the shooting mode of the camera, and the dead pixel judgment formula is generated, so that the influence of the exposure time and the sensor temperature of the camera on the dead pixel detection is weakened, the accuracy of the dead pixel detection is improved, a good dead pixel correction effect can be achieved under the long exposure condition, and the dead pixel misjudgment and missing judgment are reduced.
Referring to fig. 1 to 3, a second embodiment of the present invention is as follows:
on the basis of the first embodiment, the exposure compensation amount calculation formula is as follows:
wherein:
exp_comp is expressed as an exposure compensation amount;
k_exp is expressed as an exposure proportionality coefficient, and is a numerical interval for controlling exposure compensation amount;
cur_exp is expressed as exposure time;
comp_para is expressed as a shooting mode compensation coefficient, and the shooting modes include an HDR mode, a HighGain mode, and a LowGain mode;
the calculation formula of the temperature compensation amount is as follows:
wherein:
temp_comp is expressed as a temperature compensation amount;
k_temp is expressed as a temperature proportionality coefficient, and is a numerical interval for controlling the temperature compensation amount;
P 0 expressed as a reference gray value at a reference temperature;
sen—temp is expressed as sensor temperature;
tempori is expressed as the reference temperature of the camera, which is positively correlated with the camera usage time.
That is, in this embodiment, in order to reduce the influence of the exposure time and the sensor temperature on the dead pixel judgment, the exposure proportional coefficient and the temperature proportional coefficient are respectively introduced to control the exposure compensation amount and the temperature compensation amount, and the exposure compensation amount and the temperature compensation amount are calculated in combination with the photographing mode of the camera.
Specifically, the photographing modes can be classified into three modes of HDR (high dynamic range), highGain (high gain), and LowGain (low gain), and the compensation coefficient cmop_para is set according to the modes, specifically as follows:
1) HDR mode: comp_para=comp_para_hdr;
2) HighGain mode: comp_para=comp_para_h;
3) LowGain mode: comp_para=comp_para_l.
Referring to fig. 1 to 3, a third embodiment of the present invention is as follows:
on the basis of the second embodiment, step S2 specifically includes:
s21, respectively calculating the difference value between the neighborhood pixel point and the detected pixel point in a third-order window (please refer to fig. 3 for the arrangement situation of the third-order window pixel points) and the gradient values in four directions of horizontal, vertical, 45 degrees and 135 degrees by taking the detected pixel point as a center, wherein the calculation formula is as follows:
the calculation formula of the difference value between the detected pixel point and each pixel point in the neighborhood is as follows:
sub_p i ＝P 5 -P i ,i∈[1,9]&i≠5；
wherein:
sub_p i the difference value is expressed as the difference value between the detected pixel point and the surrounding ith neighborhood pixel point;
P i expressed as the gray value of the ith pixel point, P 5 Expressed as gray scale of pixel to be detectedA value;
the calculation formula of the horizontal gradient value grad_hor is:
grad_hor＝abs(P 6 -P 4 )；
the calculation formula of the vertical gradient value grad_ver is:
grad_ver＝abs(P 8 -P 2 )；
the calculation formula of the 45 DEG gradient value grad_45 is:
grad_45＝abs(P 3 -P 7 )；
the calculation formula of the 135 ° gradient value grad_135 is:
grad_135＝abs(P 1 -P 9 )；
in the step, taking the detected pixel point as a center, taking the difference value between the neighborhood pixel point and the detected pixel point in the size of the third-order window into consideration, and comprehensively evaluating the gradient change condition of the detected point;
s22, generating a self-adaptive dead point discriminant according to the difference value, the gradient value, the exposure compensation quantity and the temperature compensation quantity, wherein the self-adaptive dead point discriminant is expressed as follows:
or (b)
abs(sub_p i )＞detect_ratio*offset+comp,i∈[1,9]&i≠5；
comp＝exp_comp+temp_comp；
Wherein:
sub_grad is expressed as the difference between the maximum and minimum of the four directional gradient values;
max_th is represented as a preset gradient threshold value;
the detection_ratio is expressed as a preset dead pixel detection coefficient;
the offset is expressed as the difference between the next largest value and the next smallest value in the pixel values of the neighborhood pixel points;
comp is expressed as the integrated compensation amount.
The difference value between the detected pixel point and the pixel point in the field, the gradient change condition in four directions and the compensation to the exposure time of the camera and the temperature of the sensor are comprehensively considered, so that a self-adaptive dead pixel discriminant is generated, and the accuracy of judging the dynamic dead pixel is improved.
Specifically, the preset gradient threshold value max_th and the preset dead pixel detection coefficient detect_ratio are set according to the dead pixel correction intensity and the shooting mode of the actual requirement, for example, as follows: the dead pixel correction intensity is divided into three levels, and the three levels are divided as follows:
1) Dead pixel correction intensity=1, detect_ratio=ratio1, max_th=max_th1;
2) Dead pixel correction intensity=2, detect_ratio=ratio2, max_th=max_th2;
3) Dead pixel correction intensity=3, detection_ratio=ratio3, max_th=max_th3.
The step S3 specifically comprises the following steps:
and carrying out dead pixel judgment on the detected pixel point by using the self-adaptive dead pixel judgment formula, and if any judgment formula in the self-adaptive judgment formula is met, considering the detected pixel point as the dead pixel.
That is, in this embodiment, if the data of the detected pixel point satisfies any one of the adaptive discriminants, it is indicated that the detected pixel point is a dead point, and the principle thereof is that: according to the parameters in the self-adaptive discriminant, a first discriminant in the discriminant detects a flat region in an image, a second discriminant in the discriminant detects an edge region in the image, and edge information of the image is reserved, namely, the algorithm in the invention adopts different judging conditions for the flat region and the edge region of the image, so that image details can be reserved well, image quality is improved, the algorithm is simple to realize, the calculated amount is small, and the occupied resources are small.
Specifically, in order to facilitate the detection of the dead pixel on the image edge, step S1 further includes step S0, specifically:
the image shot by the camera is acquired, and the image boundary is expanded, for example, as follows: if the image size is h×m. The image size after expansion processing is (H+X) ×M+X, X is a preset image expansion factor, preferably 2 pixels, so as to avoid increasing the operand in dead pixel discrimination.
Referring to fig. 1 to 3, a fourth embodiment of the present invention is as follows:
on the basis of the third embodiment, step S3 further includes:
if the detected pixel point is judged to be a dead point, weighting correction is carried out by using the pixel value of the neighborhood pixel point;
the weighting correction by using the pixel values of the neighborhood pixel points is as follows:
calculating the median value of the neighborhood pixel points, and generating the absolute value of the difference value between the neighborhood pixel points and the median value;
generating the weight of each neighborhood pixel according to the absolute value of the difference value between the field pixel and the median value, and correcting the detected pixel by using the weight of each pixel;
the expression is as follows:
sub_median_P i ＝abs(P i -median_P),i∈[1,9]&i≠5；
namely, calculating median_P of 8 neighborhood pixels around the detected pixel point, and calculating the absolute value of the difference between the 8 neighborhood pixel values and the median;
namely, the weights of 8 neighborhood pixel points around the detected pixel point are calculated, so that the subsequent weighted calculation is convenient;
wherein:
media_P is expressed as the median value of the surrounding neighborhood pixel points of the detected pixel point;
sub_median_P i the absolute value of the difference value between the pixel point and the median value in the field;
weight i the weight value of the surrounding neighborhood pixel points expressed as the detected pixel points;
p_calib is represented as a correction value of the detected pixel point.
That is, in this embodiment, weight distribution is performed based on the difference information between the 8 neighborhood pixel values around the detected pixel and the median value of the data, and the correction value is calculated in a weight accumulation manner.
Referring to fig. 4, a fifth embodiment of the present invention is as follows:
the dynamic dead pixel detection terminal 1 based on exposure time and temperature compensation comprises a memory 2, a processor 3 and a computer program stored on the memory 2 and capable of running on the processor 3, wherein the processor executes the computer program to complete any one of the steps of the first to fourth embodiments.
In summary, the method and the terminal for detecting the dead pixel based on the exposure time and the temperature compensation provided by the invention can adaptively adjust the dead pixel judging condition according to the exposure time and the working temperature of the camera, dynamically detect the dead pixel in real time, improve the accuracy of dead pixel detection in a self-adaptive dynamic compensation mode, still achieve a good dead pixel correcting effect under a long exposure condition, reduce dead pixel misjudgment and missed judgment, and greatly weaken the influence of the exposure time and the working temperature of the camera on the dead pixel detection;
meanwhile, the self-adaptive discriminant in the invention adopts different judging conditions for the flat area and the edge area of the image, so that the image detail can be well reserved, the image quality is improved, the algorithm is simple to realize, the calculated amount is small, and the occupied resources are less.
The foregoing description is only illustrative of the present invention and is not intended to limit the scope of the invention, and all equivalent modifications made by the present invention and the accompanying drawings, or direct or indirect application in the relevant technical field, are included in the scope of the present invention.
Claims (10)
1. A dynamic dead pixel detection method based on exposure time and temperature compensation is characterized in that: the method comprises the following steps:
s1, acquiring exposure time, sensor temperature and shooting mode of a camera and generating exposure compensation quantity and temperature compensation quantity;
s2, generating a self-adaptive dead pixel discriminant according to the exposure compensation quantity and the temperature compensation quantity;
and S3, performing dead pixel judgment on the detected pixel point by utilizing the self-adaptive dead pixel discriminant, and outputting a judgment result.
2. The method for detecting the dynamic dead pixel based on exposure time and temperature compensation according to claim 1, wherein the method comprises the following steps:
the exposure compensation amount calculation formula is as follows:
wherein:
exp_comp is expressed as an exposure compensation amount;
k_exp is expressed as an exposure proportionality coefficient, and is a numerical interval for controlling exposure compensation amount;
cur_exp is expressed as exposure time;
comp_para is expressed as a shooting mode compensation coefficient, and the shooting modes include an HDR mode, a HighGain mode, and a LowGain mode;
the calculation formula of the temperature compensation quantity is as follows:
wherein:
temp_comp is expressed as a temperature compensation amount;
k_temp is expressed as a temperature proportionality coefficient, and is a numerical interval for controlling the temperature compensation amount;
P 0 expressed as a reference gray value at a reference temperature;
sen—temp is expressed as sensor temperature;
tempori is expressed as the reference temperature of the camera, which is positively correlated with the camera usage time.
3. The method for detecting the dynamic dead pixel based on exposure time and temperature compensation according to claim 2, wherein the method comprises the following steps: the step S2 specifically comprises the following steps:
s21, taking a detected pixel point as a center, respectively calculating the difference value between a neighborhood pixel point in a third-order window and the detected pixel point and gradient values in four directions of horizontal, vertical, 45-degree and 135-degree, wherein the calculation formula is as follows:
the calculation formula of the difference value between the detected pixel point and each pixel point in the neighborhood is as follows:
sub_p i ＝P 5 -P i ,i∈[1,9]&i≠5；
wherein:
sub_p i the difference value is expressed as the difference value between the detected pixel point and the surrounding ith neighborhood pixel point;
P i expressed as the gray value of the ith pixel point, P 5 A gray value expressed as a detected pixel;
the calculation formula of the horizontal gradient value grad_hor is:
grad_hor＝abs(P 6 -P 4 )；
the calculation formula of the vertical gradient value grad_ver is:
grad_ver＝abs(P 8 -P 2 )；
the calculation formula of the 45 DEG gradient value grad_45 is:
grad_45＝abs(P 3 -P 7 )；
the calculation formula of the 135 ° gradient value grad_135 is:
grad_135＝abs(P 1 -P 9 )；
s22, generating an adaptive dead pixel discriminant according to the difference value, the gradient value, the exposure compensation amount and the temperature compensation amount, wherein the adaptive dead pixel discriminant is expressed as follows:
or (b)
abs(sub_p i )＞detect_ratio*offset+comp,i∈[1,9]&i≠5；
comp＝exp_comp+temp_comp；
Wherein:
sub_grad is expressed as the difference between the maximum and minimum of the four directional gradient values;
max_th is represented as a preset gradient threshold value;
the detection_ratio is expressed as a preset dead pixel detection coefficient;
the offset is expressed as the difference between the next largest value and the next smallest value in the pixel values of the neighborhood pixel points;
comp is expressed as the integrated compensation amount.
4. The method for detecting dynamic dead pixel based on exposure time and temperature compensation according to claim 3, wherein the method comprises the following steps: the step S3 specifically comprises the following steps:
and carrying out dead pixel judgment on the detected pixel point by using the self-adaptive dead pixel discriminant, and if any discriminant in the self-adaptive discriminant is met, considering the detected pixel point as a dead pixel.
5. The method for detecting dynamic dead pixel based on exposure time and temperature compensation according to claim 4, wherein the method comprises the following steps: the step S3 further includes:
if the detected pixel point is judged to be a dead point, weighting correction is carried out by using the pixel value of the neighborhood pixel point;
the weighting correction by using the pixel values of the neighborhood pixel points is as follows:
calculating the median value of the neighborhood pixel points, and generating the absolute value of the difference value between the neighborhood pixel points and the median value;
generating the weight of each neighborhood pixel according to the absolute value of the difference value between the field pixel and the median value, and correcting the detected pixel by using the weight of each pixel;
the expression is as follows:
sub_median_P i ＝abs(P i -median_P),i∈[1,9]&i≠5；
wherein:
media_P is expressed as the median value of the surrounding neighborhood pixel points of the detected pixel point;
sub_median_P i the absolute value of the difference value between the pixel point and the median value in the field;
weight i the weight value of the surrounding neighborhood pixel points expressed as the detected pixel points;
p_calib is represented as a correction value of the detected pixel point.
6. A dynamic dead pixel detection terminal based on exposure time and temperature compensation is characterized in that: comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor performing the following steps when the computer program is executed:
s1, acquiring exposure time, sensor temperature and shooting mode of a camera and generating exposure compensation quantity and temperature compensation quantity;
s2, generating a self-adaptive dead pixel discriminant according to the exposure compensation quantity and the temperature compensation quantity;
and S3, performing dead pixel judgment on the detected pixel point by utilizing the self-adaptive dead pixel discriminant, and outputting a judgment result.
7. The dynamic dead pixel detection terminal based on exposure time and temperature compensation according to claim 6, wherein:
the exposure compensation amount calculation formula is as follows:
wherein:
exp_comp is expressed as an exposure compensation amount;
k_exp is expressed as an exposure proportionality coefficient, and is a numerical interval for controlling exposure compensation amount;
cur_exp is expressed as exposure time;
comp_para is expressed as a shooting mode compensation coefficient, and the shooting modes include an HDR mode, a HighGain mode, and a LowGain mode;
the calculation formula of the temperature compensation quantity is as follows:
wherein:
temp_comp is expressed as a temperature compensation amount;
k_temp is expressed as a temperature proportionality coefficient, and is a numerical interval for controlling the temperature compensation amount;
P 0 expressed as a reference gray value at a reference temperature;
sen—temp is expressed as sensor temperature;
tempori is expressed as the reference temperature of the camera, which is positively correlated with the camera usage time.
8. The dynamic dead pixel detection terminal based on exposure time and temperature compensation according to claim 7, wherein: the step S2 specifically comprises the following steps:
s21, taking a detected pixel point as a center, respectively calculating the difference value between a neighborhood pixel point in a third-order window and the detected pixel point and gradient values in four directions of horizontal, vertical, 45-degree and 135-degree, wherein the calculation formula is as follows:
the calculation formula of the difference value between the detected pixel point and each pixel point in the neighborhood is as follows:
sub_p i ＝P 5 -P i ,i∈[1,9]&i≠5；
wherein:
sub_p i the difference value is expressed as the difference value between the detected pixel point and the surrounding ith neighborhood pixel point;
P i expressed as the gray value of the ith pixel point, P 5 Represented as quiltDetecting the gray value of the pixel point;
the calculation formula of the horizontal gradient value grad_hor is:
grad_hor＝abs(P 6 -P 4 )；
the calculation formula of the vertical gradient value grad_ver is:
grad_ver＝abs(P 8 -P 2 )；
the calculation formula of the 45 DEG gradient value grad_45 is:
grad_45＝abs(P 3 -P 7 )；
the calculation formula of the 135 ° gradient value grad_135 is:
grad_135＝abs(P 1 -P 9 )；
s22, generating an adaptive dead pixel discriminant according to the difference value, the gradient value, the exposure compensation amount and the temperature compensation amount, wherein the adaptive dead pixel discriminant is expressed as follows:
or (b)
abs(sub_p i )＞detect_ratio*offset+comp,i∈[1,9]&i≠5；
comp＝exp_comp+temp_comp；
Wherein:
sub_grad is expressed as the difference between the maximum and minimum of the four directional gradient values;
max_th is represented as a preset gradient threshold value;
the detection_ratio is expressed as a preset dead pixel detection coefficient;
the offset is expressed as the difference between the next largest value and the next smallest value in the pixel values of the neighborhood pixel points;
comp is expressed as the integrated compensation amount.
9. The dynamic dead-spot detection terminal based on exposure time and temperature compensation of claim 9, wherein: the step S3 specifically comprises the following steps:
and carrying out dead pixel judgment on the detected pixel point by using the self-adaptive dead pixel discriminant, and if any discriminant in the self-adaptive discriminant is met, considering the detected pixel point as a dead pixel.
10. The dynamic dead pixel detection terminal based on exposure time and temperature compensation according to claim 4, wherein: the step S3 further includes:
if the detected pixel point is judged to be a dead point, weighting correction is carried out by using the pixel value of the neighborhood pixel point;
the weighting correction by using the pixel values of the neighborhood pixel points is as follows:
calculating the median value of the neighborhood pixel points, and generating the absolute value of the difference value between the neighborhood pixel points and the median value;
generating the weight of each neighborhood pixel according to the absolute value of the difference value between the field pixel and the median value, and correcting the detected pixel by using the weight of each pixel;
the expression is as follows:
sub_median_P i ＝abs(P i -median_P),i∈[1,9]&i≠5；
wherein:
media_P is expressed as the median value of the surrounding neighborhood pixel points of the detected pixel point;
sub_median_P i the absolute value of the difference value between the pixel point and the median value in the field;
weight i the weight value of the surrounding neighborhood pixel points expressed as the detected pixel points; p_calib is represented as a correction value of the detected pixel point.
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