CN116709046A - Fixed pattern noise calculation and compensation method - Google Patents
Fixed pattern noise calculation and compensation method Download PDFInfo
- Publication number
- CN116709046A CN116709046A CN202310802301.5A CN202310802301A CN116709046A CN 116709046 A CN116709046 A CN 116709046A CN 202310802301 A CN202310802301 A CN 202310802301A CN 116709046 A CN116709046 A CN 116709046A
- Authority
- CN
- China
- Prior art keywords
- central control
- control module
- amplitude
- mode
- preset
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 33
- 238000004364 calculation method Methods 0.000 title description 9
- 238000013507 mapping Methods 0.000 claims abstract description 102
- 238000012360 testing method Methods 0.000 claims abstract description 28
- 238000012545 processing Methods 0.000 claims abstract description 26
- 238000001514 detection method Methods 0.000 claims abstract description 10
- 230000008030 elimination Effects 0.000 claims abstract description 8
- 238000003379 elimination reaction Methods 0.000 claims abstract description 8
- 238000012937 correction Methods 0.000 claims description 33
- 230000002457 bidirectional effect Effects 0.000 claims description 30
- 238000012797 qualification Methods 0.000 claims description 16
- 238000012549 training Methods 0.000 claims description 15
- 230000001105 regulatory effect Effects 0.000 claims description 11
- 230000008859 change Effects 0.000 claims description 5
- 230000001276 controlling effect Effects 0.000 claims description 3
- 230000002950 deficient Effects 0.000 claims 2
- 230000000694 effects Effects 0.000 description 8
- 238000012986 modification Methods 0.000 description 4
- 230000004048 modification Effects 0.000 description 4
- 239000011159 matrix material Substances 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000006467 substitution reaction Methods 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/60—Noise processing, e.g. detecting, correcting, reducing or removing noise
- H04N25/67—Noise processing, e.g. detecting, correcting, reducing or removing noise applied to fixed-pattern noise, e.g. non-uniformity of response
- H04N25/671—Noise processing, e.g. detecting, correcting, reducing or removing noise applied to fixed-pattern noise, e.g. non-uniformity of response for non-uniformity detection or correction
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Picture Signal Circuits (AREA)
Abstract
The invention relates to the technical field of video image processing, in particular to a method for calculating and compensating fixed pattern noise, which comprises the following steps: step S1, a self-learning module acquires image data of learning samples in different light source environments and generates a mapping relation; s2, processing a preset number of test samples by using a camera, performing noise compensation on the image information of each test sample by using a noise elimination module, detecting the vertical line density in each piece of compensated image information by using a detection module, and judging whether the noise compensation of each piece of image information meets the standard or not; step S3, the central control module counts whether the noise compensation of each image data accords with the standard judgment result so as to control the noise elimination module to perform self-learning again, and the corresponding learning parameters are adjusted to the corresponding values during self-learning; the invention can completely eliminate vertical stripes while ensuring fixed pattern noise calculated for environments with lower brightness, and improves the efficiency of camera image processing.
Description
Technical Field
The invention relates to the technical field of video image processing, in particular to a method for calculating and compensating fixed pattern noise.
Background
The fixed pattern noise of the linear scanning camera causes the problem of vertical stripes in the image, so that the fixed pattern noise in a bright scene can be accurately calculated in the prior art, and the vertical stripes in the bright scene can be eliminated, however, when the same parameters or a calculation method is applied to an environment with lower brightness, the calculated fixed pattern noise is often incorrect, so that the vertical stripes cannot be eliminated even more obviously after SUM-X operation (accumulation of adjacent X X pixels, such as n X n X resolution images are processed into SUM-X images) is performed.
The reason why the prior art cannot use the same set of parameters or calculation methods to be compatible with the fixed pattern noise calculation under different brightness environments is that the parameters or calculation methods express mathematical relations between the brightness values of the pixels collected by the sensor and the brightness values of the target pixels, and the mathematical relations cannot accurately calculate the fixed noise under different scenes.
Chinese patent application No.: CN202110622979.6 discloses a fixed pattern noise dynamic compensation device, method and terminal device, and the embodiment of the invention discloses a fixed pattern noise dynamic compensation device, method and terminal device, where the fixed pattern noise dynamic compensation device includes a compensation matrix determining module and a dynamic compensation module, the compensation matrix determining module is used for determining a plurality of fixed pattern noise compensation matrices, and the dynamic compensation module is used for determining a fixed pattern noise compensation matrix corresponding to a pixel mean value of a photosensitive image frame from the plurality of fixed pattern noise compensation matrices according to the pixel mean value of the photosensitive image frame so as to compensate the photosensitive image frame. According to the dynamic compensation mode, different fixed mode noises can exist in each pixel point of the photosensitive device in different photosensitive states, so that the influence of different fixed mode noises in different photosensitive states on optical flow method calculation is avoided. The compensated photosensitive image frame is used for optical flow method calculation, so that the influence of fixed pattern noise on the accuracy of optical flow calculation can be avoided; it can be seen that the fixed pattern noise dynamic compensation device, method and terminal equipment have the following problems: the incorrectly calculated fixed pattern noise for a lower brightness environment results in no cancellation of the vertical stripes at all.
Disclosure of Invention
Therefore, the invention provides a method for calculating and compensating fixed pattern noise, which is used for solving the problem that the vertical stripes cannot be eliminated completely due to incorrect fixed pattern noise calculated for the environment with lower brightness in the prior art.
In order to achieve the above object, the present invention provides a method for calculating and compensating fixed pattern noise, comprising:
step S1, a self-learning module acquires image data of a learning sample in a full black environment and a uniform light source environment, and generates a mapping relation according to the image data;
s2, processing a preset number of test samples by using a camera, performing noise compensation on image information of each test sample by using a noise elimination module according to the brightness of the test sample, and controlling a detection module to detect the vertical line density in each compensated image information by using a central control module when the noise compensation is completed so as to judge whether the noise compensation of each image information accords with a standard or not according to the vertical line density;
and S3, when finishing judging whether the noise compensation of each image information meets the standard, the central control module counts the judging result of whether the noise compensation of each image data meets the standard or not so as to control the noise elimination module to carry out self-learning again according to the judging result, and the corresponding learning parameters are adjusted to the corresponding values during self-learning.
Further, for the step S1, it includes:
step S11, placing the camera in a full black environment and keeping the camera still;
step S12, acquiring m gain values by using a preset gain step value in a preset dark field gain amplitude, and acquiring n exposure durations by using a preset exposure duration step value under a preset exposure duration amplitude; for an ith gain value gi, i=1, 2,3,..m, the self-learning module respectively matches each of the exposure durations to form a single training reference under which s images are acquired and the mean value of each image is taken as dark field noise image data under the training reference, and for a training reference formed using the ith gain value gi and the jth exposure duration ej, j=1, 2,3,..n, the central control module records the dark field noise image data under the reference as I darkij The self-learning module repeats the steps to obtain m×n dark field image data;
step S13, the self-learning module uses a t-th order surface square by using the distribution of the three variables of the dark field image data, the gain and the exposure time in the three-dimensional spaceThe process fits to generate a continuous mapping relationship I of dark field noise relative to gain g and exposure time e dark =f (g, e) and is noted as dark mapping;
step S14, the self-learning module places the camera under a uniform light source environment and keeps the camera still, repeats the step S2 to obtain m multiplied by n original image data, and for a training reference formed by using the ith gain value gi and the jth exposure time ej, the central control module marks the original image data under the reference as I orgij The bright field noise image data under this reference is denoted as I lumij Setting I lumij ＝(I orgij -I darkij )-I goalij Wherein I goalij Is target image data under the training standard;
step S15, the self-learning module performs t times of surface fitting by using the distribution of the bright field noise image, the gain g and the exposure time e in the three-dimensional space to generate I lum Continuous mapping relation I relative to gain g and exposure time e lum =h (g, e) and is noted as a bright map.
Further, in the step S2, the central control module controls the detection module to sequentially detect the vertical line density P in the image information of each compensated test sample after completing the noise compensation of the single test sample, and determines a preliminary determination mode of whether the noise compensation for the image information is qualified according to the vertical line density P, where:
The first preliminary judgment mode is that the central control module judges that the noise compensation of the image information is qualified, and the marking module is controlled to mark the environment type and the qualification judgment result of the image; the first preliminary judgment mode meets the condition that the vertical line density P is smaller than or equal to a first preset vertical line density P1;
the second preliminary judgment mode is that the central control module judges that the noise compensation of the image information is unqualified, and judges whether to replace the mapping according to the brightness of the image information so as to carry out noise compensation processing on the image information again; the second preliminary judgment mode meets the condition that the vertical line density P is larger than the first preset vertical line density P1 and smaller than or equal to the second preset vertical line density P2;
the third preliminary judgment mode is that the central control module judges that the noise compensation of the image information is unqualified, and the marking module is controlled to mark the environment type and the qualification judgment result of the image; the third preliminary judgment mode meets the condition that the vertical line density P is larger than a second preset vertical line density P2;
the environment type comprises a field and a dark field, and the qualification judging result comprises qualification and disqualification.
Further, the central control module controls the detection module to detect the brightness of the image information in the second preliminary determination mode, and determines whether to replace a mapping according to the detected brightness so as to perform noise compensation on the image information again, wherein:
If the brightness in the image information is smaller than the preset brightness and the central control module uses the dark part mapping to perform noise compensation on the image information, or if the brightness in the image information is larger than or equal to the preset brightness and the central control module uses the bright part mapping to perform noise compensation on the image information, the central control module does not change the mapping to perform noise compensation on the image again and judges that the mapping of the image information is qualified;
and if the brightness in the image information is smaller than the preset brightness and the central control module uses the bright part mapping to perform noise compensation on the image information, or if the brightness in the image information is larger than or equal to the preset brightness and the central control module uses the dark part mapping to perform noise compensation on the image information, the central control module changes the mapping to perform noise compensation again on the image.
Further, when the marking module finishes marking all the image information, the central control module counts the ratio of the number of the image information marked as unqualified to the total number of the test samples, marks the ratio as an unqualified ratio, and determines an adjustment mode for each mapping mode according to the unqualified ratio, wherein:
The first adjustment mode is that the central control module judges that the mapping is qualified, and the mapping is not adjusted; the first adjustment mode meets the condition that the reject ratio is smaller than or equal to a first preset reject ratio;
the second adjusting mode is that the central control module judges that the mapping is unqualified, calculates a bright portion ratio Bl of the unqualified number of bright portion images and the total number of bright portion images in a bright field environment and a dark portion ratio Bd of the unqualified number of dark portion images and the total number of dark portion images in a dark field environment respectively, and adjusts parameters in the corresponding mapping according to Bl and Bd; the second adjusting mode meets the condition that the reject ratio is larger than a first preset reject ratio and smaller than or equal to a second preset reject ratio;
the third adjustment mode is that the central control module judges that the mapping is unqualified, and adjusts the step value of the exposure time length and the step value of the gain in each mapping to corresponding values according to the difference value of the unqualified ratio B and the second preset unqualified ratio; the third adjustment mode meets the condition that the reject ratio is larger than a second preset reject ratio.
Further, the central control module calculates a bright portion ratio Bl of the number of unqualified bright portion images to the total number of bright portion images in the bright field environment and a dark portion ratio Bd of the number of unqualified dark portion images to the total number of dark portion images in the dark field environment respectively in the second adjustment mode, and determines an adjustment type determination mode of the adjusted mapping type according to Bl and Bd, wherein:
The first type judgment mode is that the central control module judges to adjust parameters in the bright part mapping; the first type of adjustment mode satisfies that the bright portion ratio Bl is greater than the dark portion ratio Bd;
the second type of judgment mode is that the central control module judges to adjust parameters in the dark part mapping; the second type adjustment mode satisfies that the bright portion ratio Bl is smaller than or equal to the dark portion ratio Bd.
Further, the central control module determines a step value adjusting mode for adjusting a step value of the exposure time length and a step value of the gain according to a difference value between the reject ratio B and the second preset reject ratio in the third adjusting mode, wherein:
the first step value adjusting mode is that the central control module adjusts the step value by selecting a first adjusting coefficient alpha 1, and the adjusted step value s' =s0×α1 is set, wherein s0 is an initial step value before adjustment; the first step value adjusting mode meets the condition that the difference value is larger than or equal to a preset difference value;
the second step value adjusting mode is that the central control module selects a second adjusting coefficient alpha 2 to adjust the step value, and the adjusted step value s' =s0×alpha 2 is set; the second step value adjusting mode meets the condition that the difference value is smaller than a preset difference value.
Further, when the central control module completes the step value adjustment of the exposure time length, determining a one-way amplitude adjustment mode of the amplitude of the exposure time length according to the adjusted step value, wherein:
the first amplitude unidirectional regulation mode is that the central control module selects a first unidirectional regulation coefficient beta 1 to regulate the amplitude of the exposure time length, and the amplitude of the exposure time length after regulation is set to be G' =G0 multiplied by beta 1, wherein G0 is the amplitude of the exposure time length before regulation; the first amplitude unidirectional regulation mode meets the condition that the regulated stepping value is larger than a first preset stepping value;
the second amplitude unidirectional regulation mode is that the central control module selects a second unidirectional regulation coefficient beta 2 to regulate the amplitude of the exposure time length, and the amplitude of the exposure time length after regulation is set as G' =G0×beta 2; the second amplitude unidirectional regulation mode meets the condition that the regulated stepping value is smaller than or equal to a first preset stepping value.
Further, when the central control module completes the adjustment of the step value of the gain, the central control module determines a bidirectional amplitude adjustment mode for the amplitude of the gain according to the adjusted step value, wherein:
the first amplitude bidirectional regulation mode is that the central control module selects a first bidirectional regulation coefficient gamma 1 to regulate the amplitude of the gain, and the amplitude of the gain after regulation is set to be E' =E0×gamma 1, wherein E0 is the amplitude of the gain before regulation; the first amplitude unidirectional regulation mode meets the condition that the regulated stepping value is larger than a second preset stepping value;
The second amplitude bidirectional regulation mode is that the central control module selects a second bidirectional regulation coefficient gamma 2 to regulate the amplitude of the gain, and the amplitude of the gain after regulation is set to be E' =E0×gamma 1, wherein E0 is the amplitude of the gain before regulation; the first amplitude bidirectional adjustment mode meets the condition that the adjusted stepping value is larger than a second preset stepping value.
Further, when the central control module determines that the exposure time length and the amplitude of the gain are required to be adjusted, the ratio of the unqualified number of the bright part images to the total number of the test samples or the ratio of the unqualified number of the dark part images to the total number of the test samples is recorded as a single unqualified ratio, and a correction mode for correcting the adjusted amplitude is determined according to the single unqualified ratio, wherein:
the first correction mode is to select a first correction coefficient a1 for correcting the adjustment coefficient for the central control module, and set a corrected i-th unidirectional adjustment coefficient beta i '=beta i×a1, wherein beta i is the i-th unidirectional adjustment coefficient before correction, and a corrected i-th bidirectional adjustment coefficient gamma i' =gamma i×a1, wherein gamma i is the i-th bidirectional adjustment coefficient before correction; the first correction mode meets the condition that the single-part reject ratio is larger than or equal to a preset single-part reject ratio;
The second correction mode is that the central control module selects a second correction coefficient a2 to correct the adjusting coefficient, and the i unidirectional adjusting coefficient beta i '=beta i×a2 after correction is set, and the i bidirectional adjusting coefficient gamma i' =gamma i×a2 after correction; the second correction mode meets the condition that the single-part reject ratio is smaller than a preset single-part reject ratio.
Compared with the prior art, the invention has the beneficial effects that the central control module preliminarily judges whether the noise compensation of the image information accords with the standard according to the measured vertical line density, improves the control precision of the noise compensation effect, judges whether to replace the mapping according to the brightness of the image information to carry out noise compensation processing on the image information again when the noise compensation of the image information is preliminarily judged to be unqualified, or marks the environment type and the qualification judgment result of the image according to the brightness judgment mapping of the image information, improves the control precision of the mapping, and improves the efficiency of camera image processing when the fixed mode noise calculated for the environment with lower brightness can completely eliminate the vertical line;
the central control module counts the number of the image information marked as unqualified so as to adjust the mapping according to the number, the exposure time length and the step value of the gain, the control precision of the mapping is further improved, the fixed pattern noise calculated for the environment with lower brightness is ensured to completely eliminate vertical stripes, and the efficiency of camera image processing is further improved.
Furthermore, the invention further improves the control precision of mapping through the image data, the gain and the exposure time, realizes the effect that the fixed pattern noise calculated for the environment with lower brightness can completely eliminate the vertical stripes.
Further, the invention judges whether the noise compensation for the image information is qualified according to the vertical line density in the image information, improves the control precision of the noise compensation effect, and controls the marking module to mark the environment type and the qualification judgment result of the image when judging that the noise compensation for the image information is qualified, thereby improving the efficiency of the next image processing process.
Further, the invention judges whether to change the mapping according to the brightness of the image information to carry out noise compensation on the image information again, improves the control precision of the image information, and when judging that the mapping does not meet the standard, changes the mapping under the corresponding environment to carry out noise compensation on the image again, and further improves the efficiency of camera image processing while ensuring that the fixed mode noise calculated for the environment with lower brightness can completely eliminate vertical stripes.
Further, the invention judges the adjustment mode of each mapping through the ratio of the number of the image information marked as unqualified to the total number of the test samples, improves the control precision of the noise compensation effect under each brightness environment, adjusts the parameters in the corresponding mapping according to the ratio of the bright part and the ratio of the dark part when judging that the mapping is unqualified, or adjusts the step value of the exposure time length and the step value of the gain in each mapping to the corresponding value according to the difference value of the unqualified ratio and the second preset unqualified ratio, and further improves the efficiency of camera image processing while ensuring that the fixed mode noise calculated for the environment with lower brightness can completely eliminate the vertical stripes.
Further, the invention judges the type of the adjusted mapping according to the bright part ratio of the unqualified number of the bright part images and the total number of the bright part images and the dark part ratio of the unqualified number of the dark part images and the total number of the dark part images in the dark field environment, further improves the control precision of the mapping, adjusts the parameters in the bright part mapping according to the comparison result of the bright part ratio and the dark part ratio, and realizes that the fixed pattern noise calculated for the environment with lower brightness can completely eliminate vertical stripes.
Further, the invention judges the step value adjusting mode for adjusting the step value of the exposure time length and the step value of the gain according to the difference value of the unqualified ratio and the second preset unqualified ratio, improves the control precision of the step value of the exposure time length and the gain, ensures that the fixed pattern noise calculated for the environment with lower brightness can completely eliminate vertical stripes, and further improves the efficiency of camera image processing.
Further, the invention selects the corresponding unidirectional adjustment coefficient to carry out unidirectional adjustment on the amplitude of the exposure time according to the adjusted stepping value, improves the control precision of the amplitude of the exposure time, and realizes that the fixed pattern noise calculated for the environment with lower brightness can completely eliminate the vertical stripes.
Further, the invention selects the corresponding bidirectional adjusting coefficient to carry out bidirectional adjustment on the amplitude of the gain according to the adjusted stepping value, improves the control precision of the amplitude of the gain, and realizes that the fixed pattern noise calculated for the environment with lower brightness can completely eliminate the vertical stripes.
Furthermore, the invention corrects the regulated amplitude through the single reject ratio, improves the control precision of the amplitude, ensures that the fixed pattern noise calculated for the environment with lower brightness can completely eliminate the vertical stripes, and further improves the efficiency of camera image processing.
Drawings
FIG. 1 is a flow chart of a method for calculating and compensating fixed pattern noise according to the present invention;
FIG. 2 is a flow chart of the present invention for the step S1;
FIG. 3 is a flow chart of a preliminary determination method for determining whether noise compensation of image information is acceptable for the moire density according to the present invention;
fig. 4 is a flow chart of the adjustment method for each mapping method according to the present invention.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Fig. 1 is a flowchart of a method for calculating and compensating fixed pattern noise according to an embodiment of the invention.
The method for calculating and compensating the fixed pattern noise comprises the following steps:
step S1, a self-learning module acquires image data of a learning sample in a full black environment and a uniform light source environment, and generates a mapping relation according to the image data;
s2, processing a preset number of test samples by using a camera, performing noise compensation on image information of each test sample by using a noise elimination module according to the brightness of the test sample, and controlling a detection module to detect the vertical line density in each compensated image information by using a central control module when the noise compensation is completed so as to judge whether the noise compensation of each image information accords with a standard or not according to the vertical line density;
And S3, when finishing judging whether the noise compensation of each image information meets the standard, the central control module counts the judging result of whether the noise compensation of each image data meets the standard or not so as to control the noise elimination module to carry out self-learning again according to the judging result, and the corresponding learning parameters are adjusted to the corresponding values during self-learning.
According to the invention, the central control module preliminarily judges whether the noise compensation of the image information accords with the standard according to the measured vertical line density, so that the control precision of the noise compensation effect is improved, and judges whether to replace the mapping according to the brightness of the image information to carry out noise compensation processing on the image information again when the noise compensation of the image information is preliminarily judged to be unqualified, or the control marking module marks the environment type and the qualification judgment result of the image, judges whether the mapping is qualified according to the brightness of the image information, so that the control precision of the mapping is improved, and the efficiency of camera image processing is improved while the fixed mode noise calculated for the environment with lower brightness is ensured to completely eliminate the vertical line;
the central control module counts the number of the image information marked as unqualified so as to adjust the mapping according to the number, the exposure time length and the step value of the gain, the control precision of the mapping is further improved, the fixed pattern noise calculated for the environment with lower brightness is ensured to completely eliminate vertical stripes, and the efficiency of camera image processing is further improved.
Please refer to fig. 2, which is a flowchart of the present invention for the step S1.
Specifically, for the step S1, it includes:
step S11, placing the camera in a full black environment and keeping the camera still;
step S12, acquiring m gain values by using a preset gain step value in a preset dark field gain amplitude, and acquiring n exposure durations by using a preset exposure duration step value under a preset exposure duration amplitude; for an ith gain value gi, i=1, 2,3,..m, the self-learning module respectively matches each of the exposure durations to form a single training reference under which s images are acquired and the mean value of each image is taken as dark field noise image data under the training reference, and for a training reference formed using the ith gain value gi and the jth exposure duration ej, j=1, 2,3,..n, the central control module records the dark field noise image data under the reference as I darkij The self-learning module repeats the steps to obtain m×n dark field image data;
step S13, the self-learning module uses a t-degree surface equation to fit by using the dark field image data, the gain and the distribution of the exposure time in the three-dimensional space, so as to generate a continuous mapping relation I of dark field noise relative to the gain g and the exposure time e dark =f (g, e) and is noted as dark mapping;
step S14, the self-learning module places the camera under a uniform light source environment and keeps the camera still, repeats the step S2 to obtain m multiplied by n original image data, and for a training reference formed by using the ith gain value gi and the jth exposure time ej, the central control module marks the original image data under the reference as I orgij Bright field under the referenceNoisy image data is denoted as I lumij Setting I lumij ＝(I orgij -I darkij )-I goalij Wherein I goalij Is target image data under the training standard;
step S15, the self-learning module performs t times of surface fitting by using the distribution of the bright field noise image, the gain g and the exposure time e in the three-dimensional space to generate I lum Continuous mapping relation I relative to gain g and exposure time e lum =h (g, e) and is noted as a bright map.
According to the invention, the self-learning module is used for acquiring the original image data by placing the camera in a full black environment or a uniform light source environment, and acquiring the mapping relation according to the image data, the gain and the exposure time.
Referring to fig. 3, a flowchart of a preliminary determination method for determining whether noise compensation of image information is acceptable according to the present invention is shown.
Specifically, in the step S2, the central control module controls the detection module to sequentially detect the vertical grain density P in the image information of each compensated test sample after completing the noise compensation of the single test sample, and determines, according to the vertical grain density P, a preliminary determination mode of whether the noise compensation for the image information is qualified, where:
the first preliminary judgment mode is that the central control module judges that the noise compensation of the image information is qualified, and the marking module is controlled to mark the environment type and the qualification judgment result of the image; the first preliminary judgment mode meets the condition that the vertical line density P is smaller than or equal to a first preset vertical line density P1;
the second preliminary judgment mode is that the central control module judges that the noise compensation of the image information is unqualified, and judges whether to replace the mapping according to the brightness of the image information so as to carry out noise compensation processing on the image information again; the second preliminary judgment mode meets the condition that the vertical line density P is larger than the first preset vertical line density P1 and smaller than or equal to the second preset vertical line density P2;
The third preliminary judgment mode is that the central control module judges that the noise compensation of the image information is unqualified, and the marking module is controlled to mark the environment type and the qualification judgment result of the image; the third preliminary judgment mode meets the condition that the vertical line density P is larger than a second preset vertical line density P2;
the environment type comprises a field and a dark field, and the qualification judging result comprises qualification and disqualification.
In the embodiment of the invention, the first preset vertical line density is 3 pieces/piece, and the second preset vertical line density is 5 pieces/piece.
According to the invention, whether the noise compensation for the image information is qualified or not is judged according to the vertical line density in the image information, the control precision of the noise compensation effect is improved, and the environment type and the qualification judgment result of the image are marked by the control marking module when the noise compensation for the image information is judged to be qualified, so that the efficiency of the next image processing process is improved.
Specifically, the central control module controls the detection module to detect the brightness of the image information in the second preliminary determination mode, and determines whether to replace a mapping according to the detected brightness so as to perform noise compensation on the image information again, wherein:
if the brightness in the image information is smaller than the preset brightness and the central control module uses the dark part mapping to perform noise compensation on the image information, or if the brightness in the image information is larger than or equal to the preset brightness and the central control module uses the bright part mapping to perform noise compensation on the image information, the central control module does not change the mapping to perform noise compensation on the image again and judges that the mapping of the image information is qualified;
If the brightness in the image information is smaller than the preset brightness and the central control module uses the bright part mapping to perform noise compensation on the image information, or if the brightness in the image information is larger than or equal to the preset brightness and the central control module uses the dark part mapping to perform noise compensation on the image information, the central control module changes the mapping to perform noise compensation on the image again and detect the compensation effect of the image again.
In the embodiment of the invention, the preset brightness is 1 component of the pixel point.
The invention judges whether to change the mapping according to the brightness of the image information to carry out noise compensation on the image information again, improves the control precision of the image information, and when judging that the mapping does not accord with the standard, changes the mapping under the corresponding environment to carry out noise compensation on the image again, and further improves the efficiency of camera image processing while ensuring that the fixed mode noise calculated for the environment with lower brightness can completely eliminate vertical stripes.
Please refer to fig. 4, which is a flowchart illustrating an adjustment method for each mapping method according to the present invention.
Specifically, when the marking module finishes marking all the image information, the central control module counts the ratio of the number of the image information marked as unqualified to the total number of the test samples, marks the ratio as an unqualified ratio, and determines an adjustment mode for each mapping mode according to the unqualified ratio, wherein:
The first adjustment mode is that the central control module judges that the mapping is qualified, and the mapping is not adjusted; the first adjustment mode meets the condition that the reject ratio is smaller than or equal to a first preset reject ratio;
the second adjusting mode is that the central control module judges that the mapping is unqualified, calculates a bright portion ratio Bl of the unqualified number of bright portion images and the total number of bright portion images in a bright field environment and a dark portion ratio Bd of the unqualified number of dark portion images and the total number of dark portion images in a dark field environment respectively, and adjusts parameters in the corresponding mapping according to Bl and Bd; the second adjusting mode meets the condition that the reject ratio is larger than a first preset reject ratio and smaller than or equal to a second preset reject ratio;
the third adjustment mode is that the central control module judges that the mapping is unqualified, and adjusts the step value of the exposure time length and the step value of the gain in each mapping to corresponding values according to the difference value of the unqualified ratio B and the second preset unqualified ratio; the third adjustment mode meets the condition that the reject ratio is larger than a second preset reject ratio.
In the embodiment of the invention, the first preset disqualification ratio is 0.9, and the second preset disqualification ratio is 0.7.
The invention judges the regulation mode of each mapping by the ratio of the number of the image information marked as unqualified to the total number of the test samples, improves the control precision of the noise compensation effect under each brightness environment, regulates the parameters in the corresponding mapping according to the bright part ratio and the dark part ratio when judging that the mapping is unqualified, or regulates the step value of the exposure time length and the step value of the gain in each mapping to the corresponding value according to the difference value of the unqualified ratio and the second preset unqualified ratio, and further improves the efficiency of camera image processing while ensuring that the fixed mode noise calculated for the environment with lower brightness can completely eliminate vertical stripes.
Specifically, the central control module calculates a bright portion ratio Bl of the number of unqualified bright portion images to the total number of bright portion images in the bright field environment and a dark portion ratio Bd of the number of unqualified dark portion images to the total number of dark portion images in the dark field environment respectively in the second adjustment mode, and determines an adjustment type determination mode of the adjusted mapping type according to Bl and Bd, wherein:
the first type judgment mode is that the central control module judges to adjust parameters in the bright part mapping; the first type of adjustment mode satisfies that the bright portion ratio Bl is greater than the dark portion ratio Bd;
The second type of judgment mode is that the central control module judges to adjust parameters in the dark part mapping; the second type adjustment mode satisfies that the bright portion ratio Bl is smaller than or equal to the dark portion ratio Bd.
The invention judges the type of the adjusted mapping according to the bright part ratio of the unqualified quantity of the bright part images and the total quantity of the bright part images and the dark part ratio of the unqualified quantity of the dark part images and the total quantity of the dark part images in the dark field environment, further improves the control precision of the mapping, adjusts the parameters in the bright part mapping according to the comparison result of the bright part ratio and the dark part ratio, and realizes that the fixed pattern noise calculated for the environment with lower brightness can completely eliminate the vertical stripes.
Specifically, the central control module determines a step value adjusting mode for adjusting a step value of the exposure time length and a step value of the gain according to a difference value between the reject ratio B and the second preset reject ratio in the third adjusting mode, wherein:
the first step value adjusting mode is that the central control module adjusts the step value by selecting a first adjusting coefficient alpha 1, and the adjusted step value s' =s0×α1 is set, wherein s0 is an initial step value before adjustment; the first step value adjusting mode meets the condition that the difference value is larger than or equal to a preset difference value;
The second step value adjusting mode is that the central control module selects a second adjusting coefficient alpha 2 to adjust the step value, and the adjusted step value s' =s0×alpha 2 is set; the second step value adjusting mode meets the condition that the difference value is smaller than a preset difference value.
In the embodiment of the invention, α1 is 0.7, α2 is 0.75, and the preset difference is 0.2.
According to the invention, the step value adjusting mode of adjusting the step value of the exposure time length and the step value of the gain is judged according to the difference value of the reject ratio and the second preset reject ratio, the control precision of the step value of the exposure time length and the gain is improved, the fixed pattern noise calculated for the environment with lower brightness is ensured to completely eliminate vertical stripes, and the efficiency of camera image processing is further improved.
Specifically, when the central control module completes the adjustment of the step value of the exposure time length, the central control module determines a one-way amplitude adjustment mode of the amplitude of the exposure time length according to the adjusted step value, wherein:
the first amplitude unidirectional regulation mode is that the central control module selects a first unidirectional regulation coefficient beta 1 to regulate the amplitude of the exposure time length, and the amplitude of the exposure time length after regulation is set to be G' =G0 multiplied by beta 1, wherein G0 is the amplitude of the exposure time length before regulation; the first amplitude unidirectional regulation mode meets the condition that the regulated stepping value is larger than a first preset stepping value;
The second amplitude unidirectional regulation mode is that the central control module selects a second unidirectional regulation coefficient beta 2 to regulate the amplitude of the exposure time length, and the amplitude of the exposure time length after regulation is set as G' =G0×beta 2; the second amplitude unidirectional regulation mode meets the condition that the regulated stepping value is smaller than or equal to a first preset stepping value.
In the embodiment of the invention, G 'is the amplitude of the exposure time after adjustment, G0 is the amplitude of the exposure time before adjustment, and g0=gb-Ga is set for the amplitude G0 of the exposure time before adjustment, wherein Gb is the maximum value of the exposure time before adjustment, ga is the minimum value of the exposure time before adjustment, and the difference between the minimum value Ga of the exposure time before adjustment and the minimum value Ga' of the exposure time after adjustment satisfies the following conditions: Δga= (G '-G0)/2, Δgb= (G' -G0)/2, where the exposure time period minimum value is unchanged.
In the embodiment of the invention, β1 is 1.2, β2 is 1.3, and the first preset step value is 0.4.
The invention selects the corresponding unidirectional adjustment coefficient to carry out unidirectional adjustment on the amplitude of the exposure time according to the adjusted stepping value, improves the control precision of the amplitude of the exposure time, and realizes that the fixed pattern noise calculated for the environment with lower brightness can completely eliminate the vertical stripes.
Specifically, when the central control module completes the adjustment of the step value of the gain, the central control module determines a bidirectional amplitude adjustment mode of the amplitude of the gain according to the adjusted step value, wherein:
the first amplitude bidirectional regulation mode is that the central control module selects a first bidirectional regulation coefficient gamma 1 to regulate the amplitude of the gain, and the amplitude of the gain after regulation is set to be E' =E0×gamma 1, wherein E0 is the amplitude of the gain before regulation; the first amplitude unidirectional regulation mode meets the condition that the regulated stepping value is larger than a second preset stepping value;
the second amplitude bidirectional regulation mode is that the central control module selects a second bidirectional regulation coefficient gamma 2 to regulate the amplitude of the gain, and the amplitude of the gain after regulation is set to be E' =E0×gamma 1, wherein E0 is the amplitude of the gain before regulation; the first amplitude bidirectional adjustment mode meets the condition that the adjusted stepping value is larger than a second preset stepping value.
In the embodiment of the invention, E 'is the gain amplitude after adjustment, E0 is the gain amplitude before adjustment, and for the gain amplitude before adjustment E0, e0=eb-Ea is set, wherein Eb is the gain maximum before adjustment, ea is the gain minimum before adjustment, and the difference between the gain minimum Ea before adjustment and the gain minimum Ea' after adjustment satisfies: Δea= (E '-E0)/2, Δeb= (E' -E0)/2.
In the embodiment of the invention, γ1 is 1.25, γ2 is 1.35, and the second preset step value is 0.3.
According to the invention, the amplitude of the gain is bidirectionally adjusted by selecting the corresponding bidirectional adjusting coefficient according to the adjusted stepping value, so that the control precision of the amplitude of the gain is improved, and the fixed pattern noise calculated for the environment with lower brightness is realized, so that the vertical stripes can be completely eliminated.
Specifically, when the central control module determines that the exposure time length and the amplitude of the gain are required to be adjusted, the ratio of the unqualified number of the bright part images to the total number of the test samples or the ratio of the unqualified number of the dark part images to the total number of the test samples is recorded as a single unqualified ratio, and a correction mode for correcting the adjusted amplitude is determined according to the single unqualified ratio, wherein:
the first correction mode is to select a first correction coefficient a1 for correcting the adjustment coefficient for the central control module, and set a corrected i-th unidirectional adjustment coefficient beta i '=beta i×a1, wherein beta i is the i-th unidirectional adjustment coefficient before correction, and a corrected i-th bidirectional adjustment coefficient gamma i' =gamma i×a1, wherein gamma i is the i-th bidirectional adjustment coefficient before correction; the first correction mode meets the condition that the single-part reject ratio is larger than or equal to a preset single-part reject ratio;
The second correction mode is that the central control module selects a second correction coefficient a2 to correct the adjusting coefficient, and the i unidirectional adjusting coefficient beta i '=beta i×a2 after correction is set, and the i bidirectional adjusting coefficient gamma i' =gamma i×a2 after correction; the second correction mode meets the condition that the single-part reject ratio is smaller than a preset single-part reject ratio.
In the embodiment of the invention, a1 is 1.05, a2 is 1.07, and the preset single-part reject ratio is 0.8.
The invention corrects the regulated amplitude through the single reject ratio, improves the control precision of the amplitude, ensures that the fixed mode noise calculated for the environment with lower brightness can completely eliminate vertical stripes, and further improves the efficiency of camera image processing.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
The foregoing description is only of the preferred embodiments of the invention and is not intended to limit the invention; various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for calculating and compensating for fixed pattern noise, comprising:
step S1, a self-learning module acquires image data of a learning sample in a full black environment and a uniform light source environment, and generates a mapping relation according to the image data;
s2, processing a preset number of test samples by using a camera, performing noise compensation on image information of each test sample by using a noise elimination module according to the brightness of the test sample, and controlling a detection module to detect the vertical line density in each compensated image information by using a central control module when the noise compensation is completed so as to judge whether the noise compensation of each image information accords with a standard or not according to the vertical line density;
and S3, when finishing judging whether the noise compensation of each image information meets the standard, the central control module counts the judging result of whether the noise compensation of each image data meets the standard or not so as to control the noise elimination module to carry out self-learning again according to the judging result, and the corresponding learning parameters are adjusted to the corresponding values during self-learning.
2. The method for calculating and compensating for fixed pattern noise according to claim 1, comprising, for said step S1:
step S11, placing the camera in a full black environment and keeping the camera still;
step S12, acquiring m gain values by using a preset gain step value in a preset dark field gain amplitude, and acquiring n exposure durations by using a preset exposure duration step value under a preset exposure duration amplitude; for an ith gain value gi, i=1, 2,3,..m, the self-learning module respectively matches each of the exposure durations to form a single training reference under which s images are acquired and the mean value of each image is taken as dark field noise image data under the training reference, and for a training reference formed using the ith gain value gi and the jth exposure duration ej, j=1, 2,3,..n, the central control module records the dark field noise image data under the reference as I darkij The self-learning module repeats the steps to obtain m×n dark field image data;
step S13, the self-learning module uses a t-degree surface equation to fit by using the dark field image data, the gain and the distribution of the exposure time in the three-dimensional space, so as to generate a continuous mapping relation I of dark field noise relative to the gain g and the exposure time e dark =f (g, e) and is noted as dark mapping;
step S14, the self-learning module places the camera under a uniform light source environment and keeps the camera still, repeats the step S2 to obtain m multiplied by n original image data, and for a training reference formed by using the ith gain value gi and the jth exposure time ej, the central control module marks the original image data under the reference as I orgij The bright field noise image data under this reference is denoted as I lumij Setting I lumij ＝(I orgij -I darkij )-I goalij Wherein I goalij Is target image data under the training standard;
step S15, the self-learning module performs t times of surface fitting by using the distribution of the bright field noise image, the gain g and the exposure time e in the three-dimensional space to generate I lum Continuous mapping relation I relative to gain g and exposure time e lum =h (g, e) and is noted as a bright map.
3. The method for calculating and compensating noise in a fixed pattern according to claim 2, wherein in the step S2, the central control module controls the detection module to sequentially detect the vertical line density P in the image information of each compensated test sample after completing the noise compensation of the single test sample, and determines a preliminary determination mode for whether the noise compensation for the image information is acceptable according to the vertical line density P, wherein:
The first preliminary judgment mode is that the central control module judges that the noise compensation of the image information is qualified, and the marking module is controlled to mark the environment type and the qualification judgment result of the image; the first preliminary judgment mode meets the condition that the vertical line density P is smaller than or equal to a first preset vertical line density P1;
the second preliminary judgment mode is that the central control module judges that the noise compensation of the image information is unqualified, and judges whether to replace the mapping according to the brightness of the image information so as to carry out noise compensation processing on the image information again; the second preliminary judgment mode meets the condition that the vertical line density P is larger than the first preset vertical line density P1 and smaller than or equal to the second preset vertical line density P2;
the third preliminary judgment mode is that the central control module judges that the noise compensation of the image information is unqualified, and the marking module is controlled to mark the environment type and the qualification judgment result of the image; the third preliminary judgment mode meets the condition that the vertical line density P is larger than a second preset vertical line density P2;
the environment type comprises a field and a dark field, and the qualification judging result comprises qualification and disqualification.
4. The method for calculating and compensating for fixed pattern noise according to claim 3, wherein the central control module controls the detection module to detect the brightness of the image information in the second preliminary determination mode, and determines whether to replace a map to re-perform noise compensation on the image information according to the detected brightness, wherein:
If the brightness in the image information is smaller than the preset brightness and the central control module uses the dark part mapping to perform noise compensation on the image information, or if the brightness in the image information is larger than or equal to the preset brightness and the central control module uses the bright part mapping to perform noise compensation on the image information, the central control module does not change the mapping to perform noise compensation on the image again and judges that the mapping of the image information is qualified;
and if the brightness in the image information is smaller than the preset brightness and the central control module uses the bright part mapping to perform noise compensation on the image information, or if the brightness in the image information is larger than or equal to the preset brightness and the central control module uses the dark part mapping to perform noise compensation on the image information, the central control module changes the mapping to perform noise compensation again on the image.
5. The method for calculating and compensating for fixed pattern noise according to claim 4, wherein the central control module counts a ratio of the number of image information marked as failed to the total number of test samples when the marking module finishes marking all the image information, the central control module marks the ratio as a failed ratio, and determines an adjustment mode for each mapping mode according to the failed ratio, wherein:
The first adjustment mode is that the central control module judges that the mapping is qualified, and the mapping is not adjusted; the first adjustment mode meets the condition that the reject ratio is smaller than or equal to a first preset reject ratio;
the second adjusting mode is that the central control module judges that the mapping is unqualified, calculates a bright portion ratio Bl of the unqualified number of bright portion images and the total number of bright portion images in a bright field environment and a dark portion ratio Bd of the unqualified number of dark portion images and the total number of dark portion images in a dark field environment respectively, and adjusts parameters in the corresponding mapping according to Bl and Bd; the second adjusting mode meets the condition that the reject ratio is larger than a first preset reject ratio and smaller than or equal to a second preset reject ratio;
the third adjustment mode is that the central control module judges that the mapping is unqualified, and adjusts the step value of the exposure time length and the step value of the gain in each mapping to corresponding values according to the difference value of the unqualified ratio B and the second preset unqualified ratio; the third adjustment mode meets the condition that the reject ratio is larger than a second preset reject ratio.
6. The method for calculating and compensating for fixed pattern noise according to claim 5, wherein the central control module calculates a bright-part ratio Bl of a number of defective bright-part images to a total number of bright-part images in a bright-field environment and a dark-part ratio Bd of a number of defective dark-part images to a total number of dark-part images in a dark-field environment, respectively, in the second adjustment mode, and determines an adjustment type determination mode of an adjustment map type according to Bl and Bd, wherein:
The first type judgment mode is that the central control module judges to adjust parameters in the bright part mapping; the first type of adjustment mode satisfies that the bright portion ratio Bl is greater than the dark portion ratio Bd;
the second type of judgment mode is that the central control module judges to adjust parameters in the dark part mapping; the second type adjustment mode satisfies that the bright portion ratio Bl is smaller than or equal to the dark portion ratio Bd.
7. The method for calculating and compensating for fixed pattern noise according to claim 6, wherein the central control module determines a step value adjustment mode for adjusting a step value of an exposure time period and a step value of a gain according to a difference value between a reject ratio B and the second preset reject ratio in the third adjustment mode, wherein:
the first step value adjusting mode is that the central control module adjusts the step value by selecting a first adjusting coefficient alpha 1, and the adjusted step value s' =s0×α1 is set, wherein s0 is an initial step value before adjustment; the first step value adjusting mode meets the condition that the difference value is larger than or equal to a preset difference value;
the second step value adjusting mode is that the central control module selects a second adjusting coefficient alpha 2 to adjust the step value, and the adjusted step value s' =s0×alpha 2 is set; the second step value adjusting mode meets the condition that the difference value is smaller than a preset difference value.
8. The method for calculating and compensating for fixed pattern noise according to claim 7, wherein the central control module determines a one-way amplitude adjustment mode for the amplitude of the exposure time period according to the adjusted step value when the step value of the exposure time period is adjusted, wherein:
the first amplitude unidirectional regulation mode is that the central control module selects a first unidirectional regulation coefficient beta 1 to regulate the amplitude of the exposure time length, and the amplitude of the exposure time length after regulation is set to be G' =G0 multiplied by beta 1, wherein G0 is the amplitude of the exposure time length before regulation; the first amplitude unidirectional regulation mode meets the condition that the regulated stepping value is larger than a first preset stepping value;
the second amplitude unidirectional regulation mode is that the central control module selects a second unidirectional regulation coefficient beta 2 to regulate the amplitude of the exposure time length, and the amplitude of the exposure time length after regulation is set as G' =G0×beta 2; the second amplitude unidirectional regulation mode meets the condition that the regulated stepping value is smaller than or equal to a first preset stepping value.
9. The method for calculating and compensating for fixed pattern noise according to claim 8, wherein the central control module determines a bidirectional amplitude adjustment mode for the amplitude of the gain according to the adjusted step value when the step value adjustment for the gain is completed, wherein:
The first amplitude bidirectional regulation mode is that the central control module selects a first bidirectional regulation coefficient gamma 1 to regulate the amplitude of the gain, and the amplitude of the gain after regulation is set to be E' =E0×gamma 1, wherein E0 is the amplitude of the gain before regulation; the first amplitude unidirectional regulation mode meets the condition that the regulated stepping value is larger than a second preset stepping value;
the second amplitude bidirectional regulation mode is that the central control module selects a second bidirectional regulation coefficient gamma 2 to regulate the amplitude of the gain, and the amplitude of the gain after regulation is set to be E' =E0×gamma 1, wherein E0 is the amplitude of the gain before regulation; the first amplitude bidirectional adjustment mode meets the condition that the adjusted stepping value is larger than a second preset stepping value.
10. The method for calculating and compensating for fixed pattern noise according to claim 9, wherein when the central control module determines that the exposure time period and the gain amplitude are required to be adjusted, the ratio of the number of failed bright portion images to the total number of test samples or the ratio of the number of failed dark portion images to the total number of test samples is recorded as a single failure ratio, and a correction mode for correcting the adjusted amplitude is determined according to the single failure ratio, wherein:
The first correction mode is to select a first correction coefficient a1 for correcting the adjustment coefficient for the central control module, and set a corrected i-th unidirectional adjustment coefficient beta i '=beta i×a1, wherein beta i is the i-th unidirectional adjustment coefficient before correction, and a corrected i-th bidirectional adjustment coefficient gamma i' =gamma i×a1, wherein gamma i is the i-th bidirectional adjustment coefficient before correction; the first correction mode meets the condition that the single-part reject ratio is larger than or equal to a preset single-part reject ratio;
the second correction mode is that the central control module selects a second correction coefficient a2 to correct the adjusting coefficient, and the i unidirectional adjusting coefficient beta i '=beta i×a2 after correction is set, and the i bidirectional adjusting coefficient gamma i' =gamma i×a2 after correction; the second correction mode meets the condition that the single-part reject ratio is smaller than a preset single-part reject ratio.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310802301.5A CN116709046B (en) | 2023-07-03 | 2023-07-03 | Fixed pattern noise calculation and compensation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310802301.5A CN116709046B (en) | 2023-07-03 | 2023-07-03 | Fixed pattern noise calculation and compensation method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116709046A true CN116709046A (en) | 2023-09-05 |
| CN116709046B CN116709046B (en) | 2023-12-15 |
Family
ID=87823911
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310802301.5A Active CN116709046B (en) | 2023-07-03 | 2023-07-03 | Fixed pattern noise calculation and compensation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116709046B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117236568A (en) * | 2023-11-13 | 2023-12-15 | 山东九巨龙建设集团有限公司 | Method and system for mounting and constructing management of prefabricated wall panel |
| CN117252886A (en) * | 2023-09-11 | 2023-12-19 | 广东源恒软件科技有限公司 | Invoice identification method and system based on image segmentation |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6597428B1 (en) * | 1997-07-10 | 2003-07-22 | Fuji Photo Film Co., Ltd. | Method and apparatus for forming photographic images |
| US20040263648A1 (en) * | 2003-06-26 | 2004-12-30 | Chandra Mouli | Method and apparatus for reducing effects of dark current and defective pixels in an imaging device |
| CN107454388A (en) * | 2017-08-30 | 2017-12-08 | 上海兆芯集成电路有限公司 | Image processing method and the device using this method |
| CN107465874A (en) * | 2017-09-07 | 2017-12-12 | 维沃移动通信有限公司 | A kind of dark current processing method and mobile terminal |
| WO2019057807A1 (en) * | 2017-09-21 | 2019-03-28 | Connaught Electronics Ltd. | Harmonization of image noise in a camera device of a motor vehicle |
| CN112184591A (en) * | 2020-09-30 | 2021-01-05 | 佛山市南海区广工大数控装备协同创新研究院 | Image restoration method based on deep learning image Moire elimination |
| CN116029938A (en) * | 2023-02-24 | 2023-04-28 | 浙江双元科技股份有限公司 | Image flat field correction method and device based on linear fitting |
-
2023
- 2023-07-03 CN CN202310802301.5A patent/CN116709046B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6597428B1 (en) * | 1997-07-10 | 2003-07-22 | Fuji Photo Film Co., Ltd. | Method and apparatus for forming photographic images |
| US20040263648A1 (en) * | 2003-06-26 | 2004-12-30 | Chandra Mouli | Method and apparatus for reducing effects of dark current and defective pixels in an imaging device |
| CN107454388A (en) * | 2017-08-30 | 2017-12-08 | 上海兆芯集成电路有限公司 | Image processing method and the device using this method |
| CN107465874A (en) * | 2017-09-07 | 2017-12-12 | 维沃移动通信有限公司 | A kind of dark current processing method and mobile terminal |
| WO2019057807A1 (en) * | 2017-09-21 | 2019-03-28 | Connaught Electronics Ltd. | Harmonization of image noise in a camera device of a motor vehicle |
| CN112184591A (en) * | 2020-09-30 | 2021-01-05 | 佛山市南海区广工大数控装备协同创新研究院 | Image restoration method based on deep learning image Moire elimination |
| CN116029938A (en) * | 2023-02-24 | 2023-04-28 | 浙江双元科技股份有限公司 | Image flat field correction method and device based on linear fitting |
Non-Patent Citations (1)
| Title |
|---|
| 孙权;姚素英;郑炜;: "一种实时CIS暗电流校正方法及系统实现", 光电子.激光, no. 01 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117252886A (en) * | 2023-09-11 | 2023-12-19 | 广东源恒软件科技有限公司 | Invoice identification method and system based on image segmentation |
| CN117236568A (en) * | 2023-11-13 | 2023-12-15 | 山东九巨龙建设集团有限公司 | Method and system for mounting and constructing management of prefabricated wall panel |
| CN117236568B (en) * | 2023-11-13 | 2024-03-08 | 山东九巨龙建设集团有限公司 | Method and system for mounting and constructing management of prefabricated wall panel |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116709046B (en) | 2023-12-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116709046B (en) | Fixed pattern noise calculation and compensation method | |
| US7535511B2 (en) | Automatic exposure control method and automatic exposure compensation apparatus | |
| US6275600B1 (en) | Measuring image characteristics of output from a digital printer | |
| CN109870239B (en) | Self-adaptive calibration method for uncooled infrared focal plane detector | |
| KR102552012B1 (en) | Mura compensation system | |
| US5821993A (en) | Method and system for automatically calibrating a color camera in a machine vision system | |
| CN101325665B (en) | Phase adjustment device and digital camera | |
| KR101575803B1 (en) | Method and apparatus of generating high sensitivity image in dark environment | |
| US8243174B2 (en) | Defect pixel detection apparatus and method for detecting defect pixel | |
| KR100335529B1 (en) | Pixel defect detector for solid-state imaging device | |
| EP0132151A1 (en) | Method of and apparatus for automatically correcting position of TV camera | |
| CN114757853B (en) | Method and system for acquiring flat field correction function and flat field correction method and system | |
| US9161001B2 (en) | Image capturing apparatus that suppresses color deviation resulting from noise due to temperature and exposure time | |
| CN105872532B (en) | The detection method and system of a kind of imaging sensor | |
| CN112291553B (en) | Image line detection method of camera module | |
| CN113873222A (en) | Industrial camera linearity correction method and device | |
| CN111638042B (en) | DLP optical characteristic test analysis method | |
| US7102787B2 (en) | Image reading apparatus | |
| CN116668831A (en) | Consistency adjusting method and device for multi-camera system | |
| US20200191724A1 (en) | Optical detecting device and calibrating method | |
| US7551213B2 (en) | Method for detecting vertical transfer defects in image sensors | |
| CN111917971B (en) | Image capturing parameter optimization and adjustment system and method | |
| CN115242985B (en) | Image pickup apparatus correction method and image pickup apparatus correction apparatus | |
| JP3304152B2 (en) | Color unevenness inspection device | |
| CN113256872A (en) | Image sensor parameter configuration method and device, computer equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |