CN103475828A - Method for rectifying missing pixels and image sensor - Google Patents
Method for rectifying missing pixels and image sensor Download PDFInfo
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Abstract
The invention discloses a method for rectifying missing pixels and an image sensor. The method for rectifying missing pixels and the image sensor are efficient and accurate. According to the method for rectifying missing pixels, a 5*5Bayer color matrix is established with a pixel to be detected as a center pixel. Firstly, missing pixel rectifying is performed on pixels surrounding the center pixel of the 5*5Bayer color matrix; the pixels surrounding the center pixel of the 5*5Bayer color matrix server as reference points and whether the differential values between the color value of the center pixel and the color values of the surrounding pixels are larger than a first threshold value or not is judged, if yes, the center pixel is determined as a missing pixel and if not, the center pixel is determined as a normal pixel; the center pixel determined as the missing pixel undergoes image rectifying. The method for rectifying missing pixels is accurate in judgment of missing pixels, high in speed and good in effect of rectifying missing pixels.
Description
Technical field
The present invention relates to technical field of image processing, be specifically related to a kind of bad point bearing calibration and imageing sensor of image.
Background technology
The security protection industry has entered the high definition epoch at present, adopts the cmos sensor of 1,000,000 resolution to become trend.Because the imageing sensor manufacturing process is limit, the dead pixel points of images of cmos sensor below long-time, hot environment can get more and more, so-called bad point does not refer to and changes with sensitization, all the time (for example present a kind of color, white, black or colour) pixel, thereby destroyed clear figure and the integrality of high-definition image.The existence of bad point is one of reason of image quality decrease, and the while, the low noise environment hypograph can be poorer, affected the use of high definition product because bad point increases.And the method that traditional bad point is corrected adopts power-up initializing mode once, determine bad point position when this powers on, the bad point judged when thereby fixing solution powers on, if do not restart and power on, therefore the rectification of bad point will be confined to initialized several bad point, be not suitable for the rectification of the bad point that camera produces in long-time use procedure.
Summary of the invention
For the problems referred to above, the invention provides that a kind of bad point correction rate is fast, precision is high, image rectification bad point method and the imageing sensor of the bad point in can the correcting sensor use procedure.
For achieving the above object, dead pixel points of images bearing calibration of the present invention, the method comprises:
Centered by pixel to be detected, pixel is set up 5 * 5Bayer color matrices;
Colour variation according to described central pixel point interlacing every the surrounding pixel point of the same color of row, carry out the bad point judgement to the described surrounding pixel point of the central pixel point of described 5 * 5Bayer color matrices;
The pixel that is judged to be bad point is proofreaied and correct;
The described surrounding pixel point of described central pixel point of take is reference point, judge whether the colour of described central pixel point and the difference of described surrounding pixel point all are greater than first threshold, and if so, this central pixel point is bad point, if not, this central pixel point is normal point;
The central pixel point that is judged to be bad point is carried out to image rectification.
Further, whether described surrounding pixel point is that the determination methods of bad point is: the order of described surrounding pixel being pressed to row or column is subtracted each other successively in twos, gets every two interlacing or every the absolute value of the pixel difference of row, and described absolute value is sorted successively;
If there are two values to be greater than max-thresholds in described absolute value, and described two absolute values that are greater than described Second Threshold are continuous, the intermediary image vegetarian refreshments that calculates these two absolute values is bad point, gets the colour that the mean value of other two pixel colours is this pixel;
If there is value more than two to be greater than max-thresholds in described absolute value, all described surrounding pixel points are normal value;
If described absolute value all is less than minimum threshold, all described surrounding pixel points are normal value.
Further, the pixel around described central pixel point is and the pixel of described central pixel point interlacing every 8 same colors of row.
Further, to the bearing calibration of described center bad point pixel, be to get the described center bad point pixel colour that the mean value of the colour of the pixel of 9 same colors is this central pixel point on every side.
For achieving the above object, imageing sensor of the present invention, comprise the dead pixel points of images correcting unit, and wherein said dead pixel points of images correcting unit comprises:
Face the territory creating unit, for pixel centered by pixel to be detected, set up 5 * 5Bayer color matrices;
Judge pretreatment unit, for the colour variation every the surrounding pixel point of the same color of row according to described central pixel point interlacing, the described surrounding pixel point of the central pixel point of described 5 * 5Bayer color matrices is carried out to the bad point judgement;
The bad point identifying unit, for take the described surrounding pixel point of described central pixel point, it is reference point, judge whether the colour of described central pixel point and the difference of described surrounding pixel point all are greater than first threshold, if, this central pixel point is bad point, if not, this central pixel point is normal point;
The bad point correcting unit, carry out image rectification for the central pixel point to being judged to be bad point.
Further, described judgement pretreatment unit comprises:
Computing unit, subtract each other successively in twos for the order of described surrounding pixel being pressed to row or column, gets every two interlacing or every the absolute value of pixel difference of row, and described absolute value is sorted successively;
Comparing unit, for the size of more described absolute value and max-thresholds and minimum threshold, take and judge whether described surrounding pixel point is bad point;
If there are two values to be greater than max-thresholds in described absolute value, and described two absolute values that are greater than described Second Threshold are continuous, the intermediary image vegetarian refreshments that calculates these two absolute values is bad point, gets the colour that the mean value of other two pixel colours is this pixel;
If there is value more than two to be greater than max-thresholds in described absolute value, all described surrounding pixel points are normal value;
If described absolute value all is less than minimum threshold, all described surrounding pixel points are normal value.
Especially, described transducer comprises the four lines buffer unit, and every line buffer unit comprises four registers.
The present invention, judge by the difference degree to current pixel and surrounding pixel whether it is bad point, and carry out bad point at the pixel to around current pixel point and judge in advance, if it first proofreaies and correct it processing for bad point, using it as current pixel point, whether be the basis for estimation of bad point again, thereby make the bad point judgement more accurate, improved picture quality.From hardware configuration, because the bad point detection algorithm is based on, 5 * 5 filter window judges, when hardware is realized, need 4 row bufferings to carry out temporal data, every row has 4 single pixel values of register-stored simultaneously, thereby forms the data processing window of 5 * 5.
The accompanying drawing explanation
Fig. 1 is 5 * 5Bayer color matrices figure that the present invention sets up;
Fig. 2 is the matrix schematic diagram of 5 * 5Bayer color matrices of corresponding diagram 1 foundation of the present invention;
Fig. 3 is the structural representation of memory cell of the present invention;
The flow chart that Fig. 4 is method for correcting image of the present invention.
Embodiment
Below in conjunction with Figure of description, the present invention will be further described.
Dead pixel points of images bearing calibration of the present invention, the method comprises:
Centered by pixel to be detected, pixel is set up 5 * 5Bayer color matrices;
Colour variation according to described central pixel point interlacing every the surrounding pixel point of the same color of row, carry out the bad point judgement to the described surrounding pixel point of the central pixel point of described 5 * 5Bayer color matrices;
The pixel that is judged to be bad point is proofreaied and correct;
The described surrounding pixel point of described central pixel point of take is reference point, judge whether the colour of described central pixel point and the difference of described surrounding pixel point all are greater than first threshold, and if so, this central pixel point is bad point, if not, this central pixel point is normal point;
The central pixel point that is judged to be bad point is carried out to image rectification.
Imageing sensor of the present invention, comprise the dead pixel points of images correcting unit, and wherein said dead pixel points of images correcting unit comprises:
Face the territory creating unit, for pixel centered by pixel to be detected, set up 5 * 5Bayer color matrices;
Judge pretreatment unit, for the colour variation every the surrounding pixel point of the same color of row according to described central pixel point interlacing, the described surrounding pixel point of the central pixel point of described 5 * 5Bayer color matrices is carried out to the bad point judgement;
The bad point identifying unit, for take the described surrounding pixel point of described central pixel point, it is reference point, judge whether the colour of described central pixel point and the difference of described surrounding pixel point all are greater than first threshold, if, this central pixel point is bad point, if not, this central pixel point is normal point;
The bad point correcting unit, carry out image rectification for the central pixel point to being judged to be bad point.
Embodiment 1
As shown in Figures 1 to 3, the bearing calibration of the present embodiment dead pixel points of images, the method comprises:
Centered by pixel to be detected, pixel is set up 5 * 5Bayer color matrices;
Colour variation according to described central pixel point interlacing every the surrounding pixel point of the same color of row, carry out the bad point judgement to the described surrounding pixel point of the central pixel point of described 5 * 5Bayer color matrices;
The pixel that is judged to be bad point is proofreaied and correct;
The described surrounding pixel point of described central pixel point of take is reference point, judge whether the colour of described central pixel point and the difference of described surrounding pixel point all are greater than first threshold, and if so, this central pixel point is bad point, if not, this central pixel point is normal point;
The central pixel point that is judged to be bad point is carried out to image rectification.
In the present embodiment, whether described surrounding pixel point is that the determination methods of bad point is: the order of described surrounding pixel being pressed to row or column is subtracted each other successively in twos, gets every two interlacing or every the absolute value of the pixel difference of row, and described absolute value is sorted successively;
If there are two values to be greater than max-thresholds in described absolute value, and described two absolute values that are greater than described Second Threshold are continuous, the intermediary image vegetarian refreshments that calculates these two absolute values is bad point, gets the colour that the mean value of other two pixel colours is this pixel; Also except " have two values to be greater than max-thresholds in described absolute value, and described two absolute values that are greater than described Second Threshold being continuous ", in this case, other situation judges that this pixel is the normal pixel point.
If there is value more than two to be greater than max-thresholds in described absolute value, all described surrounding pixel points are normal value;
If described absolute value all is less than minimum threshold, all described surrounding pixel points are normal value.
Pixel around described central pixel point is and 8 pixels of described central pixel point interlacing every row.
For R, G, tri-components of B, central point p22 and 8 some p00 of being separated by every side, p02, p04, p20, p24, p40, p42, p44 is same component, can determine whether utmost point dim spot or incandescent degree according to the difference of p22 point and these 8 points.
Before judging whether central point is bad point, first want the filtering bad point of 8 surrounding pixel points on every side, the absolute difference of the pixel around first calculating, the present embodiment, counterclockwise to subtract each other by adjacent interlacing or every the pixel of two pixel values of row successively, is got the absolute value of difference:
d0 = |p00 – p20|;
d1 = |p20 – p40|;
d2 = |p40 – p42|;
d3 = |p42 – p44|;
d4 = |p44 – p24|;
d5= |p24 – p04|;
d6 = |p04 – p02|;
d7 = |p02 – p00|;
The absolute difference d0 of pixel in certain computation structure of certain color component, d1, d2, d3, d4, d5, d6, have and only have two values to be greater than max-thresholds, and be continuous in d7, can determine " bad point " position, the mean value of putting former and later two pixels with this replaces being somebody's turn to do the value of " bad point "; Di-1 and the di when certain color component is greater than threshold value, can determine that i pixel pi in this computation structure is " bad point ", with the mean value of pi-1 and pi+1, replaces Pi, Pi=(Pi-1+Pi+1)/2; In certain computation structure of certain color component, the absolute interpolation of all pixels all is less than threshold value dpc_th, and around this computation structure, 8 pixels do not have bad point; In the absolute interpolation of all pixels, have and only have two values to be greater than threshold value dpc_th, but this even individual absolute difference is not continuous, thinks that can't determine whether is " bad point "; In the absolute interpolation of all pixels, there is value more than two to be greater than threshold value dpc_th, think that these change violent pixel is not " bad point ", but the border of image will not be revised;
After handling the surrounding pixel point of each computation structure, then central pixel point is revised.P22 when the luminance difference of 8 pixels all is greater than first threshold, can think that this central pixel point is bad point on every side, and wherein said first threshold can be established according to different situations.
If((|diff(p22.p00)|>dpc_th)&&(|diff(p22.p02)|>dpc_th)&&(|diff(p22.p04)|>dpc_th) &&(|diff(p22.p20)|>dpc_th)&&(|diff(p22.p24)|>dpc_th)&&(|diff(p22.p40)|>dpc_th) &&(|diff(p22.p42)|>dpc_th) && (|diff(p22.p44)|>dpc_th))
P22 is bad point.
Further, to the bearing calibration of described center bad point pixel, be to get the described center bad point pixel colour that the mean value of the colour of the pixel of 9 same colors is this central pixel point on every side.
The present embodiment imageing sensor, comprise the dead pixel points of images correcting unit, and wherein said dead pixel points of images correcting unit comprises:
Face the territory creating unit, for pixel centered by pixel to be detected, set up 5 * 5Bayer color matrices;
Judge pretreatment unit, for the colour variation every the surrounding pixel point of the same color of row according to described central pixel point interlacing, the described surrounding pixel point of the central pixel point of described 5 * 5Bayer color matrices is carried out to the bad point judgement;
The bad point identifying unit, for take the described surrounding pixel point of described central pixel point, it is reference point, judge whether the colour of described central pixel point and the difference of described surrounding pixel point all are greater than first threshold, if, this central pixel point is bad point, if not, this central pixel point is normal point;
The bad point correcting unit, carry out image rectification for the central pixel point to being judged to be bad point.
Further, described judgement pretreatment unit comprises:
Computing unit, subtract each other successively in twos for the order of described surrounding pixel being pressed to row or column, gets every two interlacing or every the absolute value of pixel difference of row, and described absolute value is sorted successively;
Comparing unit, for the size of more described absolute value and max-thresholds and minimum threshold, take and judge whether described surrounding pixel point is bad point;
If there are two values to be greater than max-thresholds in described absolute value, and described two absolute values that are greater than described Second Threshold are continuous, the intermediary image vegetarian refreshments that calculates these two absolute values is bad point, gets the colour that the mean value of other two pixel colours is this pixel;
If there is value more than two to be greater than max-thresholds in described absolute value, all described surrounding pixel points are normal value;
If described absolute value all is less than minimum threshold, all described surrounding pixel points are normal value.
As shown in Figure 4, because the bad point detection algorithm is based on, the filter window of 5X5 judges, when hardware is realized, needs 4 row bufferings carry out temporal data, and every row has 4 single pixel values of register-stored simultaneously, thereby forms the data processing window of a 5X5.
Above; be only preferred embodiment of the present invention, but protection scope of the present invention is not limited to this, anyly is familiar with those skilled in the art in the technical scope that the present invention discloses; the variation that can expect easily or replacement, within all should being encompassed in protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range that claim was defined.
Claims (7)
1. a dead pixel points of images bearing calibration, it is characterized in that: the method comprises:
Centered by pixel to be detected, pixel is set up 5 * 5Bayer color matrices;
Colour variation according to described central pixel point interlacing every the surrounding pixel point of the same color of row, carry out the bad point judgement to the described surrounding pixel point of the central pixel point of described 5 * 5Bayer color matrices;
The pixel that is judged to be bad point is proofreaied and correct;
The described surrounding pixel point of described central pixel point of take is reference point, judge whether the colour of described central pixel point and the difference of described surrounding pixel point all are greater than first threshold, and if so, this central pixel point is bad point, if not, this central pixel point is normal point;
The central pixel point that is judged to be bad point is carried out to image rectification.
2. dead pixel points of images bearing calibration according to claim 1, it is characterized in that: whether described surrounding pixel point is that the determination methods of bad point is: the order of described surrounding pixel being pressed to row or column is subtracted each other successively in twos, get every two interlacing or every the absolute value of pixel difference of row, and described absolute value is sorted successively;
If there are two values to be greater than max-thresholds in described absolute value, and described two absolute values that are greater than described Second Threshold are continuous, the intermediary image vegetarian refreshments that calculates these two absolute values is bad point, gets the colour that the mean value of other two pixel colours is this pixel;
If there is value more than two to be greater than max-thresholds in described absolute value, all described surrounding pixel points are normal value;
If described absolute value all is less than minimum threshold, all described surrounding pixel points are normal value.
3. dead pixel points of images bearing calibration according to claim 1 is characterized in that: the pixel around described central pixel point is and the pixel of described central pixel point interlacing every 8 same colors of row.
4. dead pixel points of images bearing calibration according to claim 1 is characterized in that: the bearing calibration to described center bad point pixel is to get the described center bad point pixel colour that the mean value of the colour of the pixel of 9 same colors is this central pixel point on every side.
5. an imageing sensor, it is characterized in that: comprise the dead pixel points of images correcting unit, wherein said dead pixel points of images correcting unit comprises:
Face the territory creating unit, for pixel centered by pixel to be detected, set up 5 * 5Bayer color matrices;
Judge pretreatment unit, for the colour variation every the surrounding pixel point of the same color of row according to described central pixel point interlacing, the described surrounding pixel point of the central pixel point of described 5 * 5Bayer color matrices is carried out to the bad point judgement;
The bad point identifying unit, for take the described surrounding pixel point of described central pixel point, it is reference point, judge whether the colour of described central pixel point and the difference of described surrounding pixel point all are greater than first threshold, if, this central pixel point is bad point, if not, this central pixel point is normal point;
The bad point correcting unit, carry out image rectification for the central pixel point to being judged to be bad point.
6. imageing sensor according to claim 4, it is characterized in that: described judgement pretreatment unit comprises:
Computing unit, subtract each other successively in twos for the order of described surrounding pixel being pressed to row or column, gets every two interlacing or every the absolute value of pixel difference of row, and described absolute value is sorted successively;
Comparing unit, for the size of more described absolute value and max-thresholds and minimum threshold, take and judge whether described surrounding pixel point is bad point;
If there are two values to be greater than max-thresholds in described absolute value, and described two absolute values that are greater than described Second Threshold are continuous, the intermediary image vegetarian refreshments that calculates these two absolute values is bad point, gets the colour that the mean value of other two pixel colours is this pixel;
If there is value more than two to be greater than max-thresholds in described absolute value, all described surrounding pixel points are normal value;
If described absolute value all is less than minimum threshold, all described surrounding pixel points are normal value.
7. described imageing sensor according to claim 4, it is characterized in that: described transducer comprises the four lines buffer unit, every line buffer unit comprises four registers.
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