CN109274907B - Signal processing method on CMOS image sensor - Google Patents

Signal processing method on CMOS image sensor Download PDF

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CN109274907B
CN109274907B CN201811392083.8A CN201811392083A CN109274907B CN 109274907 B CN109274907 B CN 109274907B CN 201811392083 A CN201811392083 A CN 201811392083A CN 109274907 B CN109274907 B CN 109274907B
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signal
image sensor
processing
value
sensor signal
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CN109274907A (en
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李明
刘戈扬
刘昌举
李毅强
任思伟
刘航
吕玉冰
周亚军
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CETC 44 Research Institute
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China Electronics Technology Group Corp Chongqing Acoustic Optic Electronic Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/70—SSIS architectures; Circuits associated therewith
    • H04N25/76—Addressed sensors, e.g. MOS or CMOS sensors
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T1/00—General purpose image data processing
    • G06T1/20—Processor architectures; Processor configuration, e.g. pipelining

Abstract

The invention belongs to the field of CMOS image sensor chip design and signal processing thereof, in particular to a signal processing method on a CMOS image sensor, which comprises the steps of carrying out binary inversion operation on an A/D bit signal of each bit of an image sensor signal processed by an A/D converter on the CMOS image sensor; carrying out nonlinear processing on the inverted image sensor signal by adopting a signal processing formula, and then carrying out iterative judgment until an optimal iterative value is determined; under the optimal iteration value, adding an enhancement factor in a signal processing formula to process the dark area of the image sensor signal; carrying out binary inversion operation on the processed image sensor signal; the invention implements the inverse operation on the image signal, which is beneficial to the subsequent processing of the signal, and then carries out the nonlinear and iterative processing on the signal after the inverse operation, thereby achieving the purposes of improving the signal-to-noise ratio and the dynamic state of the signal and realizing the compensation processing of the signal.

Description

Signal processing method on CMOS image sensor
Technical Field
The invention relates to the field of CMOS image sensor chip design and signal processing, in particular to a signal processing method on a CMOS image sensor chip.
Background
The current CMOS image sensor is widely applied to a plurality of fields as a visual perception part, but parameters influencing imaging quality such as signal to noise ratio and dynamic range of the CMOS image sensor cannot be further improved, and especially under a low-light-level environment, the image quality is worse. To obtain a high quality image when using a CMOS image sensor, dynamic expansion and improvement can be made on-chip of the CMOS image sensor without increasing the cost of external system hardware. The traditional image signal processing method has the problem that the image enhancement effect and the real-time property cannot be simultaneously considered.
Disclosure of Invention
The invention aims to solve the problems in the background art and provides an on-chip signal processing method which can be applied to a CMOS image sensor. The invention adopts the technical scheme that aiming at imaging in the environment of low light level and the like, a signal pipeline level processing idea is adopted to perform signal inversion operation and nonlinear processing on the collected photoelectric digital signals so as to realize dynamic expansion and signal enhancement of image signals, and the technical processing effect is better and is beneficial to on-chip integration.
The patent provides an on-chip dynamic expansion and signal processing method of a CMOS image sensor, which not only can better retain image details and greatly improve the visual effect of an image, but also is easy to realize on a chip and realizes the real-time processing of signals with higher efficiency. The method has good application and reference values for improving the quality of image signals in low-light environment such as low-light environment.
The invention relates to a signal processing method on a CMOS image sensor, which comprises the following steps:
s1, performing reverse processing on the image sensor signal processed by the A/D converter on the CMOS image sensor;
s2, carrying out nonlinear processing on the image sensor signal after the reverse processing by adopting a signal processing formula;
s3, carrying out iterative judgment on the image sensor signal after nonlinear processing until an optimal iterative value is determined;
s4, under the optimal iteration value, adding an enhancement factor in the signal processing formula, and processing the dark area of the image sensor signal;
and S5, performing inverse processing on the image sensor signal processed in the step S4.
Wherein, the inversion process means an inversion operation, that is, it means that the low level 0 in the signal is changed to the high level 1, and the high level 1 is changed to the low level 0.
And performing inverse operation, signal nonlinear processing, iterative value judgment and iterative processing and secondary inverse operation on the image data subjected to the on-chip A/D processing of the CMOS image sensor. The processing method has the advantages of good processing effect and contribution to on-chip integration of the image sensor.
In step S1, the quantization bit number of the image sensor signal processed by the a/D converter is defined as n, and the maximum gray scale level is 2nThe pixel value range of the image falls within {0, 2 }nAnd the A/D bit signal of each bit is subjected to binary inversion.
Further, for the image sensor signal under the low light environment condition, the nonlinear processing of the image sensor signal needs to adopt the signal processing formula of the formula step S2, which includes:
F(x)＝[(K(x)-A)/T(x)]+A
where f (x) is the processed image sensor signal, k (x) is the image sensor signal at low light level, t (x) is a nonlinear coefficient, and a is the signal maximum within the window.
Further, in a low light environment, the image output by the image sensor is k (x), and the maximum value of the signal in the image array is a, and in order to obtain the processed result f (x), the formula for calculating the nonlinear coefficient t (x) includes:
T(x)＝1-w×min{I[(x)]}
wherein, (x) represents a window function, I [ (x) ] represents a comparison function of the image signal in the window, and w represents an adjustment factor, and the value range of the adjustment factor is 0-1.
Further, since the maximum value of the image signal is usually caused by noise or pixel over-explosion at a certain position, and a processing error may occur when the maximum value is used as the estimated value of a, the step S3 specifically includes determining the maximum value of the image sensor signal in a window of the window function (x) in which the image sensor signal is associated with the gray level 2n-1Performing comparison judgment when the maximum value of the image sensor signal is equal to or greater than 2n-1When the image sensor signal is detected, the value of A is the maximum value of the image sensor signal, namely the optimal iteration value is the maximum value of the image sensor signal; when the maximum value of the image sensor signal is less than 2n-1When, A takes 2n-1The optimal iteration value is that A takes 2n-1。
Further, since f (x) does not significantly expand and increase in the dark region in the dynamic state of the image signal, an enhancement factor r (x) is added to the denominator in the f (x) formula, in step S4, an enhancement factor is added to the signal processing formula at the optimal iteration value, and the processing of the dark region of the image sensor signal specifically includes adding an enhancement factor r (x) to the denominator in the signal processing formula, that is, f (x) ═ k (x) -a)/t (x) xr (x) > + a; the enhancement factor r (x) has a value of 1 when t (x) is at (0, 0.5) and a value of m times t (x) when t (x) is at (0.5, 1), m ∈ (1, 3).
The invention has the beneficial effects that:
1. aiming at imaging in environments such as low light level and the like, the method adopts a signal pipeline level processing idea to perform inverse processing, nonlinear processing, iterative processing and dynamic compensation processing on the acquired image signal, has good processing effect, is beneficial to on-chip integration and occupies less resources;
2. the invention implements the inverse operation on the image signal, which is beneficial to the subsequent processing of the signal, and then carries out the nonlinear and iterative processing on the signal after the inverse operation, thereby achieving the purposes of improving the signal-to-noise ratio and the dynamic state of the signal and realizing the compensation processing of the signal;
3. the invention aims to improve the signal dynamic of the dark area of the image signal by carrying out enhancement factor processing on the dark area.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a schematic diagram of signal processing according to the present invention;
fig. 3 is a diagram of a window array of signal data in accordance with a preferred embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clearly and completely apparent, the technical solutions in the embodiments of the present invention are described below with reference to the accompanying drawings, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
The signal processing method on the CMOS image sensor of the invention, as shown in figure 1, comprises the following steps:
s1, performing reverse processing on the image sensor signal processed by the A/D converter on the CMOS image sensor;
s2, carrying out nonlinear processing on the image sensor signal after the reverse processing by adopting a signal processing formula;
s3, carrying out iterative judgment on the image sensor signal after nonlinear processing until an optimal iterative value is determined;
s4, under the optimal iteration value, adding an enhancement factor in the signal processing formula, and processing the dark area of the image sensor signal;
and S5, performing inverse processing on the image sensor signal processed in the step S4.
The design idea of the invention is to adopt a signal pipeline stage processing mode, and the signal processing process comprises the following steps: the image data after on-chip a/D processing of the CMOS image sensor is subjected to an inverse process, a signal non-linear process, enhancement factor determination and iteration, and a secondary inverse process, and the process flow is shown in fig. 2.
As a preferred embodiment, the image data output by A/D on CMOS image sensor chip, in this embodiment, defines the quantization bit number as n, where n is 10, and the maximum gray scale is 210The pixel value range of the image falls within {0, 2 }10The inverse process of the signal is to perform binary inverse operation on the a/D bit signal of each bit, i.e. 0 (low level) becomes 1 (high level) and 1 becomes 0 (low level), and the process does not change the quantization bit number of the data, and the maximum gray level is still 210。
For the image sensor signal under the low light environment condition, the formula f (x) [ (k (x) -a)/t (x) ] + a is adopted, wherein k (x) is the image signal under the low light, f (x) is the processed image signal, t (x) is a nonlinear coefficient, and a is the maximum value of the image signal in the selected window.
In a low light environment, the image output by the image sensor is K (x), the size of the window can be set according to needs, and the window array is set to be 6 × 6, such as H12Representing the 1 st row and the second column in the window arrayAs shown in fig. 3, the maximum value of the signal in the image window array is a, and in order to obtain the processed result f (x), the nonlinear coefficient t (x) is represented by the formula t (x) 1-w × min { I [ (x)]Where (x) is a window function, I [ (x)]The method is characterized in that a comparison function of image signals in a window is shown, min is to carry out minimum comparison on the image signals in the window, and when the value of an adjusting factor w is between 0.5 and 0.7, the processing effect is good.
In the window array of 6 × 6, first, the maximum value of the signal in the window of (x) is determined by comparing 36 signal data in the window, and then the sum of the maximum values of the signal is performed by 29(i.e., 512) a comparison is made, a being the maximum value when the signal maximum is equal to or greater than gray level 512 and 512 when the signal maximum is less than gray level 512. And carrying out nonlinear processing on the image signal iteration according to the judged A value.
Since f (x) does not expand and improve significantly in the darker region in the dynamic state of the image signal, an enhancement factor r (x) is added to the denominator in the formula f (x), when t (x) is (0, 0.5), the value of the enhancement factor r (x) is 1, when t (x) is (0.5, 1), the value of the enhancement factor r (x) is m times of t (x), and m ∈ (1, 3).
And performing signal inversion operation on the processed F (x) again to obtain the F (x) meeting the requirements of dynamic and signal-to-noise ratio, and outputting the F (x) to a subsequent component for processing.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable storage medium, and the storage medium may include: ROM, RAM, magnetic or optical disks, and the like.
The above-mentioned embodiments, which further illustrate the objects, technical solutions and advantages of the present invention, should be understood that the above-mentioned embodiments are only preferred embodiments of the present invention, and should not be construed as limiting the present invention, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (6)

1. A method of signal processing on a CMOS image sensor, the method comprising the steps of:
s1, performing inversion processing on the image sensor signal processed by the A/D converter on the CMOS image sensor by adopting binary inversion operation;
s2, carrying out nonlinear processing on the image sensor signal after the reverse processing by adopting a signal processing formula;
s3, carrying out iterative judgment on the image sensor signal after nonlinear processing until an optimal iterative value is determined;
s4, under the optimal iteration value, adding an enhancement factor in the signal processing formula, and processing the dark area of the image sensor signal;
and S5, performing inverse processing on the image sensor signal processed in the step S4.
2. The signal processing method of claim 1, wherein in step S1, the quantization bit number of the image sensor signal processed by the a/D converter is defined as n, and the maximum gray scale level is 2nThe pixel value range of the image falls within {0, 2 }nAnd the A/D bit signal of each bit is subjected to binary inversion.
3. The signal processing method of claim 1, wherein the signal processing formula of step S2 includes:
F(x)＝[(K(x)-A)/T(x)]+A
where f (x) is the image sensor signal after the non-linear processing, k (x) is the image sensor signal under low light, t (x) is the non-linear coefficient, and a is the signal maximum within the window.
4. The signal processing method of claim 3, wherein the formula for calculating the non-linear coefficient T (x) comprises:
T(x)＝1-w×min{I[(x)]}
wherein, (x) represents a window function, I [ (x) ] represents a comparison function of the image signal in the window, and w represents an adjustment factor, and the value range of the adjustment factor is 0-1.
5. The signal processing method of claim 3, wherein the step S3 specifically comprises determining a maximum value of the image sensor signal in a window of a window function (x) in which the image sensor signal is associated with a gray level of 2n-1Performing comparison judgment when the maximum value of the image sensor signal is equal to or greater than 2n-1When the value of A is the maximum value of the image sensor signal, the value of A is less than the gray level 2n-1When, A takes 2n-1。
6. The method of claim 3, wherein in step S4, under the optimal iteration value, the enhancement factor is added to the signal processing formula, and the processing of the dark region of the image sensor signal specifically includes adding an enhancement factor r (x) to the denominator of the signal processing formula, that is, f (x) ═ k (x) -a/t (x) xr (x) ] + a; the enhancement factor r (x) has a value of 1 when t (x) is at (0, 0.5) and a value of m times t (x) when t (x) is at (0.5, 1), m ∈ (1, 3).
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