EP1374565A1 - Method and device for fpn correction of image signals - Google Patents
Method and device for fpn correction of image signalsInfo
- Publication number
- EP1374565A1 EP1374565A1 EP02722269A EP02722269A EP1374565A1 EP 1374565 A1 EP1374565 A1 EP 1374565A1 EP 02722269 A EP02722269 A EP 02722269A EP 02722269 A EP02722269 A EP 02722269A EP 1374565 A1 EP1374565 A1 EP 1374565A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- image
- value
- correction coefficients
- coefficients
- cells
- 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.)
- Withdrawn
Links
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
- H04N25/63—Noise processing, e.g. detecting, correcting, reducing or removing noise applied to dark current
-
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/50—Control of the SSIS exposure
- H04N25/57—Control of the dynamic range
- H04N25/571—Control of the dynamic range involving a non-linear response
- H04N25/573—Control of the dynamic range involving a non-linear response the logarithmic type
Definitions
- the invention relates to a method and a device for FPN correction of image signals that are generated by image cells of an image sensor.
- the invention further relates to a digital camera with such a device.
- image sensors are increasingly being used as a replacement for conventional film material, which convert an optical intensity distribution into electronic image signals.
- Such image sensors have a regular arrangement of pixels ("pixels"), each of which is assigned one or more light-sensitive circuits made of semiconductor components, hereinafter referred to as image cells.
- image cells Each of these image cells generates an image signal, the voltage value of which is a function of the intensity of the light striking the image cell.
- each pixel In the case of image sensors for color reproduction, each pixel generally consists of a triple of image cells, each of which is covered by a color filter for one of the three spectral colors red, green and blue.
- Each image signal of such an image cell reproduces a brightness value related to the spectral color in question, so that the total of the three individual signals contains the color information for the relevant pixel.
- the FPN is only insufficiently corrected for brightnesses other than the reference brightness, i.e. at such brightnesses, the granular appearance of homogeneous surfaces remains largely unchanged.
- the characteristic curves of the individual image cells which indicate the relationship between the optical intensity (brightness) impinging on the image cell and the image signal generated, cannot be covered only by adding a difference value. Rather, the characteristics of the individual image cells also differ in terms of their slope, so that a correction in the reference brightness may be different in other brightnesses. significantly less impact.
- the correction of the FPN is particularly difficult because elaborate mathematical transformations as part of the correction are ruled out, at least for commercial applications, because of the high storage and computing capacities required and because of the real-time requirements.
- the object is achieved in a device of the type mentioned at the outset by:
- a discriminator for determining in which of at least two value ranges the value of an image signal of an image cell lies at a predetermined time
- a selection device for determining a corrected value for the image signal as a function of the result determined by the discriminator.
- the invention is based on the finding that a significant improvement in the FPN correction can be achieved in that the image signals are not corrected in a uniform manner over the entire range of values, but in different ways according to ranges of values. This makes it possible to achieve good correction results with simple transformations which place low demands on memory requirements and computing power.
- the actual characteristic curve of each image cell can be determined within the individual value ranges a mathematically simple approximation characteristic can be approximated, which allows the use of correspondingly simple transformations that can be carried out with little computing effort.
- the underlying transformation equations then require only a few coefficients, which means that the memory requirement is kept low.
- the corrected value for the image signal can be determined, for example, such that a number of corrected values corresponding to the number of value ranges is determined for each pixel using the transformation equations valid for this. A specific correction value assigned to this value range is then selected from these corrected values depending on the value range in which the value of the image signal actually lies at a predetermined point in time. Therefore, as many correction values as there are value ranges are to be determined for each image cell.
- the determination of the corrected value after step b) comprises the steps: bl) selecting correction coefficients from a plurality of sets of correction coefficients depending on the result after step a); and
- This procedure has the advantage that in each case only the calculation of a single corrected value is necessary, namely using those correction coefficients that are assigned to the value range. Instead of selecting one correction value from several correction values calculated in advance, this procedure only calculates one correction value using selected correction coefficients.
- the sets of correction coefficients are different for a plurality of image cells and / or for the different value ranges.
- image cells can be grouped together. However, individual correction coefficients are preferably used for each image cell.
- the at least two value ranges can be identical for all image cells.
- the circuitry structure required to carry out the method becomes very simple, since one or more individual threshold values for each image cell need not be read out from a memory and fed to a discriminator.
- the at least two value ranges are preferably different for a plurality of image cells.
- this additionally requires storing threshold values for each picture cell.
- this disadvantage is offset by the fact that a further considerable improvement in the FPN correction is achieved.
- the threshold values for the pixels can be stored in a threshold value memory, for example. It is also possible to calculate the threshold values from stored coefficients for the transformation equations, so that there is no additional storage requirement for the threshold values. If necessary, individual coefficients can also be used directly as a threshold.
- the transformation equations by an array of 'are Logikbau- stones in particular from adders and multipliers, to which the coefficients are fed from a memory.
- correction coefficients are determined for each image cell from a comparison of an actual characteristic curve, which indicates a relationship between an optical intensity impinging on the respective image cell and the image signal generated, with a target characteristic curve.
- the target characteristic curve can in principle be set arbitrarily. However, the definition should be made from the point of view that, with regard to the approximate equations for the actual characteristic curves, transformation equations are as simple as possible within the value ranges.
- the target characteristic curve is determined by forming the mean value from the actual characteristic curves of the image cells.
- This determination of the target characteristic curve means that the corrections to be made to the individual image signals are minimal overall.
- the at least two value ranges are defined in such a way that the actual characteristic curves and the target characteristic curve are each approximately linear to the logarithm of the optical intensity within the value ranges.
- the corrected value V c for the image signal from an actual value V r generated by the image cell according to a transformation equation of the form
- V " a • V + b
- a and b are correction coefficients of the transformation equation determined from a comparison of the actual characteristic curve with the target characteristic curve.
- Such a linear transformation equation results if the individual characteristic curve sections are approximated by straight lines.
- such a linear transformation equation can be achieved by a simple series connection. implement from a multiplier and an adder, whereby the order of these two logic modules is in principle irrelevant.
- V. a_ • log E + b j.
- V r a r • log E + b r
- the image signals of the individual image cells which are linear with respect to the logarithm of the brightness information, are thus described in each value range by linear approximation equations, the coefficients of which result from the relationship given the coefficients of the transformation equation. These coefficients are stored in a memory and are called up each time the image signal of the relevant image cell lies within the assigned value range.
- the coefficients a r and b r are preferably determined by the method of the smallest squares of deviation from actual characteristic curves of the image cells.
- the coefficients a_ and b_ are preferably determined by averaging the coefficients a r and b r over all image cells.
- an approximation equation for the target characteristic curve can be determined in a particularly simple manner in the individual value ranges.
- FIG. 1 shows a highly schematic representation of a digital camera according to the invention with an image sensor installed therein;
- FIG. 2 shows a basic circuit diagram of an electronic unit for further processing of image signals that are generated by the image sensor shown in FIG. 1;
- Fig. 3 shows a characteristic curve of a single logarithmically compressing image cell in which an output voltage is plotted against an optical intensity impinging on the image cell;
- FIG. 6 shows a representation of several characteristic curves corresponding to FIG. 4, in which a target characteristic curve is additionally entered;
- FIG. 7 shows a representation of a target characteristic curve and an actual characteristic curve in a representation as in FIG. 6, in which additional approximation lines are shown for individual value ranges;
- FIG. 9 shows a representation corresponding to FIG. 5 of the distribution of the output voltages which have been subjected to the FPN correction according to the invention.
- FIG. 10a-10f exemplary embodiments of an inventive device for FPN correction in a schematic representation.
- 1 shows a highly simplified schematic illustration of a digital camera 10, which can be a photo or a film camera.
- the digital camera 10 has an electronic image sensor 12, on the light-sensitive surface of which a motif 14 is imaged with the aid of a lens system 16 only indicated here.
- the images recorded by the image sensor 12 are digitally processed in an electronic unit 18 so that they can finally be read out via a camera output 20.
- the electronics unit 18 can be assigned an image memory (not shown in FIG. 1) in which the processed images can be stored. It is also possible to arrange only a part of the electronics unit 18 within the digital camera 10. The remaining parts are then implemented outside the digital camera 10, for example as software that can be executed on a personal computer.
- the image sensor 12 has a regular arrangement of pixels, each of which consists of three light-sensitive image cells 22 in a manner known per se. Each image cell 22 of a pixel is covered by different color filters, so that the output voltage generated by the respective image cell is a function of the intensity of the light of the spectral color that can pass through the filter in question. In the case of image sensors which are only suitable for black-and-white recordings, the image points each consist of only a single image cell.
- the image cells 22 used in the image sensor 12 are implemented as circuits of semiconductor components which, in the exemplary embodiment shown, generate an output voltage which approximately corresponds to the logarithm of the optical intensities incident thereon. corresponds to. The image cells 22 therefore generate logarithmically compressed image signals. Details of the structure of such picture cells 22 can be found in the aforementioned EP 632 930 B1.
- the image signals generated by the image cells 22 are read out row by row and column-wise and are combined in a read-out multiplexer 24 to form an overall signal.
- the overall signal thus contains the image signals assigned to the individual image cells 22 in chronological order. In the following, explanations of image signals therefore always refer to the image signal that is generated by a very specific image cell 22 in the image sensor 12.
- the image signals are digitized in an analog / digital converter 25, which can also be arranged on the image sensor 12 itself, and then corrected in an FPN correction unit 26 such that the falsifications of the captured image caused by the FPN are largely reduced.
- the structure of the FPN correction unit 26 is explained in more detail below using several exemplary embodiments.
- the FPN-corrected image signal is then further processed in a processing stage 32, e.g. to specifically change the brightness or color saturation and to carry out a ⁇ correction.
- the image signal prepared in this way can finally be read out via the output 20 and converted back into an image using an output device 34.
- 3 shows a characteristic curve 36 of an individual image cell 22 in a representation in which an output voltage V generated by the image cell 22 is plotted against a brightness E impinging on the image cell 22.
- the characteristic curve 36 has a first and a second section 38 and 40, in which the output voltage V is approximately linear to the logarithm of the brightness E.
- the output signal V of the image cell 22 increases logarithmically with the brightness E.
- the output voltage V of the image cell 22 is approximately independent of the brightness E.
- This approximately horizontal section of the characteristic curve 36 represents a dark current of the image cell 22, which is essentially due to the photodiode contained in the image cell.
- the dark current is generated there, among other things, due to thermal generation and recombination of free charge carriers via impurities that are present in the space charge zone of the photodiode.
- the characteristic curve 36 of an image cell 22 shown in FIG. 3 can be mathematically represented by an equation of the form
- V k • log ( ⁇ E + I D ) + c (1)
- I D denotes the dark current
- the quantity c is a quantity dependent on the temperature and the transistor geometry.
- the factor ⁇ gives the relationship between the current strength and the brightness E generated by the image cell 22 again.
- FIG. 4 shows a representation corresponding to FIG. 3 of several characteristic curves 44, 46, 48, 50 and 52, which are assigned to different image cells 22 of the image sensor 12. It can be seen in this illustration that the characteristic curves of the individual image cells differ not only with regard to their dark currents, but also with regard to the factors which indicate the slope of the characteristic curves at higher brightnesses. Because of these relatively large differences between the individual characteristic curves, adding or subtracting constant values, as is the case with conventional white balance, does not result in largely identical characteristic curves.
- the distribution (number N) of the output voltages V is indicated in FIG. 5 for two fixed brightnesses E_ and E 2 if, in FIG. 4, not only five but several hundred thousand characteristic curves are plotted which correspond to the individual image cells of the image sensor 12.
- the scatter of the output voltages measured for the individual image cells around the mean values V_ or V 2 are a measure of the strength of the FPN.
- a target characteristic curve 54 is entered in FIG. 6 for the five characteristic curves 44 to 52 from FIG. 4, which characteristic curve is determined by averaging the actual actual characteristic curves 44 to 52.
- the mean values V_ and V 2 from FIG. 5 are therefore on the target characteristic curve 54.
- the FPN would completely disappear if the actual characteristic curves 44 to 52 could be mapped to the desired characteristic curve 54 (or another arbitrarily defined desired characteristic curve) by means of a suitable transformation.
- a transformation of equation (1) is, however, mathematically very complex and therefore cannot be managed by an FPN correction unit in real time.
- the ordinate is divided into a first and a second value range 56 and 58, respectively, by determining a suitable threshold value V th for the output voltage.
- V th a suitable threshold value for the output voltage.
- the first value range 56 for the actual characteristic curve 52, the first section to be traced back to the dark current is approximated by an approximately horizontal first approximation line 60.
- the second value range 58 the characteristic curve 52 is approximated by a second, now inclined approximation line 62.
- the threshold value V th is chosen so that the actual characteristic curve 52 is approximated as well as possible by the two approximation lines 60 and 62.
- the approximation line 62 can be determined by an equation of the form
- V a r • log E + b r (2)
- V r is an output voltage on the actual characteristic curve and a r and b r are the coefficients of the linear equation (2).
- the two coefficients a r and b r can be determined in a manner known per se using the method of the least squares of deviation (regression analysis). For this purpose, a plurality of measurement values are recorded once for each image cell by the manufacturer over the entire brightness range, from which the two coefficients a r and b r are then determined within the second value range 58 using the method of the smallest squares of deviations.
- the coefficients of the first approximation line 60 are also determined for all image cells of the image sensor 12.
- the characteristic curve of each image cell is thus approximately represented by a total of four coefficients.
- a target characteristic curve 54 is first determined. This can be done, for example, by first determining an average for this brightness by averaging the measured values recorded for each image cell at a certain brightness. These mean values can then also be used to approximate a first and a second target approximation line 64 or 66 using the method of the least squares of deviation.
- the four coefficients of the two desired approximation lines 64 and 66 are preferably determined directly from the coefficient determined for each individual image cell, i.e. e.g. for the second approximation line 66
- V t a_ • log E + bi (3)
- V ⁇ the output voltage of the nominal characteristic curve 54
- a_ and b ⁇ the coefficients of the second nominal approximation lines 66 and a rk and b rk are the measured values recorded for each pixel in the second value range 58.
- n is the number of picture cells for which characteristic curves are recorded.
- Corresponding equations also apply to the first target approximation line 64 of the first value range 56.
- the threshold value V th which separates the two value ranges 56 and 58 from one another, can preferably be set independently for each of the image cells 22. Otherwise, as can easily be seen from FIG. 6, the approximately horizontal sections of the characteristic curves would in part still be approximated by the equations for the inclined sections and vice versa.
- a further improvement in the approximation can be achieved in that the ordinate is not divided into two, but into three or even more value ranges.
- a third value range 67 is inserted between the first value range 56 and the second value range 58 for the characteristic curve 52, which defines the transition section 42 of the characteristic curve 52 by a quadratic function of the shape
- V. p (log E - E 0 ) 2 + p c (5) approximates, where p, E 0 and p 0 are coefficients of the parabola equation (5). However, not only four, but a total of seven coefficients are then to be stored in the FPN correction unit 26 per image cell.
- the desired target characteristic is approximated in a first value range by a parabolic section-shaped approximation characteristic and in a second value range by a straight line. If the first range of values exactly covers the first two decades of brightness, there is a steady and particularly "soft" transition between the characteristic curve sections ⁇ . In addition, in this case the number of correction coefficients required can be reduced to a total of three per image cell, and the transformation of the real values of the image points to the approximation characteristic can be carried out simply and in real time.
- V 0 a • V r + b (6)
- V c designate the corrected output voltage
- a and b the coefficients of the transformation equation (6).
- the coefficients a and b are derived from the coefficients a r , b r , a_ and b_ of the approximate equations (2) and (3) through the relationship
- the FPN correction described above can optionally also be carried out only for a part of the image cells of an image sensor.
- 10a shows a schematic illustration of a first exemplary embodiment 26a for the construction of an FPN correction unit 26.
- the image signal of a specific image cell supplied at an input 68a is fed to a discriminator 70a which checks whether the image signal is above or below that in a threshold value memory 71a stored threshold value V th .
- the threshold value V th is identical for all picture cells in this exemplary embodiment.
- the result of this This check is passed to a multiplexer 72a.
- the multiplexer 72a can be used to read out values from a first memory 74a and a second memory 76a, each of which can be supplied with the address of the image cell whose output voltage is currently applied to the input 68a in digital form.
- Coefficients a_ and b x of the transformation equation (6) for the first value range 56 of all image cells of the image sensor 12 are stored in the first memory 74a.
- Coefficients a 2 and b 2 of the transformation equation (6) for the second value range 58 are stored in the second memory 76.
- the multiplexer 72a now reads the coefficients of the transformation equation belonging to the selected value range from one of the two memories 74a or 76a depending on the result transferred by the discriminator 70a.
- the coefficients a_ or a 2 are fed to a multiplier 78a in which the image signal present at the input 68a is multiplied by the factor a_ or a 2 supplied.
- the coefficients b_ or b 2 are fed to an adder 80a and added to the image signal changed in the multiplier 78a.
- the corrected image signal can be tapped off at an output 82a of the FPN correction unit 26a.
- the two memories 74a and 76a and the threshold value memory 71a can of course also be implemented as separate memory areas in a common memory element.
- the access time for the two memories 74a and 76a and the readout frequency it may also be expedient to use the FPN correction unit 26a as To implement a pipeline structure in whose data paths registers are inserted.
- the number of value ranges distinguishable by the discriminator 70a must be adjusted accordingly by specifying further threshold values. Additional memories must also be provided, from which coefficients can be read out by multiplexer 72a. If the transformation equation (6) is not a linear equation but has a different form, this can be taken into account by a different arrangement of the logic modules (multiplier 78a and adder 80a).
- a common threshold value V th is not provided for all image cells, as is the case with the FPN correction unit 26a from FIG. 10a. Rather, a separate threshold value V th is stored there for each picture cell in a threshold value memory 71b. As mentioned above, this significantly improves the accuracy of the FPN correction.
- the threshold value memory 71b is connected to an input 68b of the FPN correction unit 26b, so that it can be supplied with the address of the image cell whose output voltage is currently applied to the input 68b.
- a threshold value calculation unit 84c is provided, which independently uses the coefficients supplied from memories 74c and 76c to determine a threshold value for each image cell and makes it available to a discriminator 70c. Such a calculation is e.g. then makes sense if the costs for the storage space to be reserved for a threshold value memory are higher than the costs for the threshold value calculation unit 84c.
- the FPN correction unit 26d shown in FIG. 10d differs from the FPN correction unit 26b shown in FIG. 10b in that the coefficient a ⁇ ', which is calculated from the slope of the approximately horizontal (target) approximation line 60 and 64, respectively , is the same in the first range of values for all picture cells and is therefore not loaded from a memory 74d, but rather from a read-only memory 86d, which may also be contained in a multiplexer 72d or may be replaced by circuitry wiring.
- the coefficient b_ ' is fed as a threshold value to a discriminator 70d, so that a threshold value memory is also omitted here.
- the FPN correction unit 26e shown in FIG. 10e does not first select coefficients for the individual value ranges and then calculate the correction values V c , as is the case with the exemplary embodiments described above. Rather, at FPN Correction unit 26e calculates correction values in parallel for both value ranges, which can be tapped behind the adders 78e. A correction value is then selected from the two calculated correction values in a multiplexer 2e and made available to an output 82e.
- the multiplexer 72e is also controlled here by a discriminator 70e, which checks whether the image signal is above or below the threshold value V th stored in a threshold value memory 71e.
- the FPN correction unit 26f shown in FIG. 10f differs from the FPN correction unit 26e described above only in that the coefficient a_ is zero for all image cells, which corresponds to horizontal (target) approximation lines in the first value range. This eliminates one of the multipliers required in the FPN correction unit 26e according to FIG. 10e.
- the threshold values for the FPN correction units 26e and 26f can also be determined from the stored coefficients, as was described above for the FPN correction unit 26c.
- the individual components of the FPN correction units 26a to 26f described above can be constructed from digital or also from analog components (multipliers 78, adders 80 and multiplexers 72).
- analog-to-digital converter 25 on the input side is of course omitted.
- coefficients stored in the memories 74 and 76 must then be converted into analog signals with the aid of digital / analog converters.
Abstract
Description
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Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE10117833 | 2001-04-03 | ||
DE10117833A DE10117833C1 (en) | 2001-04-03 | 2001-04-03 | Fixed pattern noise correction method for image sensor signals selects transformation equation for calculation of correction value dependent on identified value range of image signal |
PCT/EP2002/003356 WO2002082804A1 (en) | 2001-04-03 | 2002-03-26 | Method and device for fpn correction of image signals |
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EP1374565A1 true EP1374565A1 (en) | 2004-01-02 |
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EP02722269A Withdrawn EP1374565A1 (en) | 2001-04-03 | 2002-03-26 | Method and device for fpn correction of image signals |
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US (1) | US7420599B2 (en) |
EP (1) | EP1374565A1 (en) |
JP (1) | JP2005509319A (en) |
DE (1) | DE10117833C1 (en) |
WO (1) | WO2002082804A1 (en) |
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DE10239994B4 (en) * | 2002-08-27 | 2006-12-14 | Robert Bosch Gmbh | Method for correcting irregularities of an image sensor system |
JPWO2006098374A1 (en) * | 2005-03-15 | 2008-08-28 | オムロン株式会社 | Imaging apparatus, signal processing apparatus, and signal processing method |
JP5588729B2 (en) * | 2010-04-28 | 2014-09-10 | 日立コンシューマエレクトロニクス株式会社 | Image signal processing device |
WO2013128817A1 (en) * | 2012-02-28 | 2013-09-06 | コニカミノルタ株式会社 | Solid-state image capture device |
KR102182870B1 (en) | 2014-04-08 | 2020-11-25 | 삼성전자주식회사 | Linear-logarithmic image sensor and electronic device including the same |
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2001
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2002
- 2002-03-26 WO PCT/EP2002/003356 patent/WO2002082804A1/en active Application Filing
- 2002-03-26 EP EP02722269A patent/EP1374565A1/en not_active Withdrawn
- 2002-03-26 JP JP2002580629A patent/JP2005509319A/en active Pending
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2003
- 2003-09-30 US US10/674,784 patent/US7420599B2/en not_active Expired - Fee Related
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WO2002082804A1 (en) | 2002-10-17 |
US20040100568A1 (en) | 2004-05-27 |
DE10117833C1 (en) | 2002-09-12 |
JP2005509319A (en) | 2005-04-07 |
US7420599B2 (en) | 2008-09-02 |
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