CN104023185B - Automatic multi-level RTS noise real-time reestablishing method applied to CMOS image sensor - Google Patents

Abstract

The invention discloses an automatic multi-level RTS noise real-time reestablishing method applied to a CMOS image sensor to solve the technical problem that the noise signal detecting and reestablishing reliability is poor based on a multi-level RTS noise algorithm in an existing automatic CMOS image extracting sensor. According to the technical scheme, all noise signals are converted into triangular pulses with the equal amplitude, falling edge detecting is carried out on all the pulses, the calculated standard deviation amplitude is sampled, gain is carried out on the filtered triangular pulses, the triangular pulses are compared with the collected standard deviation, the average value is reset and calculation is carried out again every time RTS noise hop is detected, and the sampled average value signal is the amplitude of the RTS noise hop. According to the method, the real-time Gaussian noise standard deviation serves as the threshold value for judging the RTS noise, the threshold value is automatically collected, the RTS noise signal is reestablished, and the overall RTS noise signal detecting and reestablishing reliability is improved.

Description

It is applied to the automatic real-time reconstruction method of multistage RTS noise of cmos image sensor

Technical field

The present invention relates to a kind of automatic real-time reconstruction method of multistage RTS noise, more particularly to one kind is applied to cmos image The automatic real-time reconstruction method of multistage RTS noise of sensor.

Background technology

Document " V.Goiffon, G.R.Hopkinson, P.Magnan, F.Bernard, G.Rolland, and O.Saint-Pé,"Multilevel RTS in Proton Irradiated CMOS Image Sensors Manufactured in a Deep Submicron Technology",IEEE Trans.Nucl.Sci.,vol.56, No.4, pp.2132-2141, Aug.2009. " discloses a kind of calculation for automatically extracting multistage RTS noise in cmos image sensor Method.By formula

Process is filtered to original picture signal (including RTS noise), all saltus steps in primary signal are processed For the form of triangular pulse, the filter function can realize that filtered triangular pulse height is corresponding with primary signal Saltus step amplitude is equal, the faint saltus step of saltus step and background Gaussian noise including RTS noise signal, and wherein L represents filtering length Degree.The standard deviation of the noise amplitude of whole primary signal is calculated, by the standard deviation sigma of whole primary signal_sig, as judging that RTS makes an uproar The threshold value of sound, when the maximum saltus step amplitude in filtered signal is more than threshold value σ_sig, there is RTS noise in representing primary signal, it is no The primary signal is represented then in there is no RTS noise.

All triangular pulses and threshold value σ after it will filter_sigJudge specific RTS noise saltus step, these trianglees Amplitude change in the corresponding primary signal of pulse represents RTS noise, and other saltus steps can be considered Gaussian noise saltus step.Often Primary signal is divided into N by the triangular pulse of RTS saltus step_segSection, such each section of primary signal are all made an uproar not comprising RTS Sound saltus step, by each section of standard deviation difference σ_segI () is carried out averagely, obtain the standard deviation difference meansigma methodss of whole signal Gaussian noise σ_gn.By meansigma methodss M of each section of amplitude_segI () is compared, if gap is more than Gaussian noise standard deviation between the two Meansigma methodss σ_gn, then it is considered as two RTS noise levels, is otherwise considered as same one-level RTS noise.Amplitude after each section is processed connects To realize the reconstruction of RTS noise signal.

There are following shortcomings in this algorithm：

1. the algorithm need etc. all primary signals terminate could start to process, in all primary signals to be calculated such as needing Each section of standard deviation and meansigma methodss.

2. the algorithm proposes the standard deviation sigma using whole signal_sigAs the threshold value for judging that RTS signals are present.Cmos image The temperature of increase whole device of the sensor during work with the working time can rise, and cause Gaussian noise amplitude Change, even when in the face of extreme condition, (such as radiation environment etc.) can cause device inside defect, cause RTS noise amplitude Significantly change, and this change can cause the change of whole gaussian signal standard deviation, using the standard deviation of whole signal as threshold Value is obviously inaccurate.

The content of the invention

Existing automatically extract in cmos image sensor the detection of multistage RTS noise algorithm noise signal and rebuild to overcome The deficiency of credibility difference, the present invention provide a kind of automatic real-time reconstruction side of multistage RTS noise for being applied to cmos image sensor Method.Noise signal the triangular pulse of amplitude such as be all converted to the method first, then all of negative-going pulse is changed into All pulses are carried out trailing edge detection by direct impulse, control the mark to original noise with the trailing edge signal for detecting Quasi- difference is calculated, the standard deviation amplitude to calculating is sampled, then by filtered triangular pulse by gain with collect Standard deviation is compared, and using standard deviation as the threshold value for judging RTS signals, determines that triangular pulse corresponding saltus step in part is RTS Noise signal, whenever a RTS noise saltus step is detected, resets to mean value calculation, recalculates, by the RTS for detecting Signal controls the meansigma methodss for calculating are sampled and kept through time delay, and the average value signal for sampling is this section of RTS and makes an uproar The amplitude of sound saltus step.The inventive method, is adopted as the threshold value for judging RTS noise automatically according to the standard deviation of real-time Gaussian noise Collect threshold value and rebuild RTS noise signal.First, using the collection of real-time automatic signal and calculating, improve RTS noise reconstruction Speed and efficiency, have compared with tradition Processing Algorithm and have improve precision and efficiency of detecting；Second, using real-time gaussian signal mark Quasi- difference is compared more accurate as threshold value with the standard deviation of whole signal as threshold value, can effectively reduce temperature, space spoke The signal standardss that degeneration of the external environment condition to the signal noise amplitude for affecting and then causing of device working environment cause such as penetrate poor The change of (i.e. RTS noise decision threshold), can improve whole RTS noise signal detection with the credibility rebuild.

The technical solution adopted for the present invention to solve the technical problems：It is a kind of to be applied to the multistage of cmos image sensor The automatic real-time reconstruction method of RTS noise, is characterized in comprising the following steps：

The first step, when external noise signals arrive, through formula

Filter function, complete the transformation of noise signal, the saltus step in primary signal be all converted to into etc. the three of amplitude Angular pulse；

In formula, L represents whole filter length, a_iRepresent the rising width of triangular pulse, b_iRepresent under triangular pulse Drop width.Saltus step in primary signal is converted to equidirectional by the filter function, and etc. the triangular pulse of amplitude, including background is high Faint amplitude jump in this noise.

Second step, triangular pulse is calculated by absolute value, all of negative-going pulse is changed into direct impulse；

All pulses are carried out trailing edge detection by the 3rd step, whenever a trailing edge is detected indicate that raw noise The once generation of saltus step in signal, even in background Gaussian noise faint saltus step；

4th step, controls the standard deviation to original noise and calculates, whenever detection with the trailing edge signal for detecting To a trailing edge signal, standard deviation is recalculated to original noise just；

5th step, the standard deviation amplitude to calculating are sampled, because standard deviation is calculated carrying out always, lead to Cross trailing edge and detect signal standard deviation is gathered by delays time to control and be used as RTS judgment thresholds, the standard deviation Real-time Collection Record；

6th step, filtered triangular pulse is compared with the standard deviation for collecting by gain, using standard deviation as Judge the threshold value of RTS signals, determine that triangular pulse corresponding saltus step in part is RTS noise signal；

7th step, whenever a RTS noise saltus step is detected, resets to mean value calculation, recalculates；

8th step, by the RTS signals for detecting through time delay, controls the meansigma methodss for calculating are sampled and kept, adopts Sample to average value signal be the amplitude of this section of RTS noise saltus step.

The invention has the beneficial effects as follows：Noise signal the triangular pulse of amplitude such as be all converted to the method first, All of negative-going pulse is changed into into direct impulse again, all pulses are carried out with trailing edge detection, with the trailing edge letter for detecting Number control is calculated to the standard deviation of original noise, and the standard deviation amplitude to calculating is sampled, then by filtered three Angle pulse is compared with the standard deviation for collecting by gain, using standard deviation as the threshold value for judging RTS signals, determines part three The corresponding saltus step of angular pulse is RTS noise signal, whenever a RTS noise saltus step is detected, mean value calculation is reset, Recalculate, by the RTS signals for detecting through time delay, control the meansigma methodss for calculating are sampled and kept, sample Average value signal is the amplitude of this section of RTS noise saltus step.Standard deviation conduct of the inventive method according to real-time Gaussian noise Judge the threshold value of RTS noise, automatic data collection threshold value and rebuild RTS noise signal.First, using real-time automatic signal collection with Calculate, improve the speed and efficiency of RTS noise reconstruction, compared with tradition Processing Algorithm and improve precision and efficiency of detecting； Second, using real-time gaussian signal standard deviation as threshold value, compare more smart as threshold value with the standard deviation of whole signal Really, the signal noise that affect and then cause of the external environment conditions such as temperature, space radiation to device working environment can effectively be reduced The change of the signal standardss poor (i.e. RTS noise decision threshold) that the degeneration of amplitude causes, improves whole RTS noise signal detection With the credibility rebuild.

With reference to the accompanying drawings and detailed description the present invention is elaborated.

Description of the drawings

Fig. 1 is that the present invention is applied to the automatic real-time reconstruction method of multistage RTS noise of cmos image sensor in signal Schematic diagram after RTS noise system reconstructing.

Specific embodiment

With reference to Fig. 1.The present invention is applied to the automatic real-time reconstruction method of multistage RTS noise of cmos image sensor and specifically walks It is rapid as follows：

The first step, when external noise signals arrive, through formula

Filter function, complete the transformation of noise signal, the saltus step in primary signal be all converted to into etc. the three of amplitude Angular pulse；

In formula, L represents whole filter length, a_iRepresent the rising width of triangular pulse, b_iRepresent under triangular pulse Drop width.Saltus step in primary signal is converted to equidirectional by the filter function, and etc. the triangular pulse of amplitude, including background is high Faint amplitude jump in this noise.

Second step, triangular pulse is calculated by absolute value, all of negative-going pulse is changed into direct impulse；

All pulses are carried out trailing edge detection by the 3rd step, whenever a trailing edge is detected indicate that raw noise The once generation of saltus step in signal, even in background Gaussian noise faint saltus step；

4th step, controls the standard deviation to original noise and calculates, whenever detection with the trailing edge signal for detecting To a trailing edge signal, standard deviation is recalculated to original noise just；

5th step, the standard deviation amplitude to calculating are sampled, because standard deviation is calculated carrying out always, lead to Cross trailing edge and detect signal standard deviation is gathered by delays time to control and be used as RTS judgment thresholds, the standard deviation Real-time Collection Record；

6th step, filtered triangular pulse is compared with the standard deviation for collecting by certain gain, by standard As the threshold value for judging RTS signals, difference determines that triangular pulse corresponding saltus step in part is RTS noise signal；

7th step, whenever a RTS noise saltus step is detected, resets to mean value calculation, recalculates；

8th step, by the RTS signals for detecting through certain time-delay, controls the meansigma methodss for calculating are sampled and protected Hold, the average value signal for sampling is the amplitude of this section of RTS noise saltus step.

Fig. 1 is the multistage RTS noise automatic detection and reconstructing system that the inventive method is applied to cmos image sensor.Bag Containing filtering part, threshold level produces part and sampling holding part.Wherein filtering part is comprising filter function module and definitely Value computing module；Threshold level generating unit point includes gain module, declines detection module, and standard deviation computing module, high level are adopted Egf block and time delay module；Sampling holding part includes comparator module, mean value calculation module, rising edge sampling module and Time delay module.All saltus steps are filtered into the triangular pulse of the amplitude such as equidirectional by filter function module by primary signal, then All triangular pulses are arranged as pulse upwards by absolute value block.Filtered triangular pulse signal is carried out down Drop often detects a trailing edge and means that primary signal there occurs a saltus step along detection, and trailing edge is compared to rising edge The saltus step of signal has been completed, and amplitude is relatively more stable and reliable, is detected trailing edge and is controlled follow-up standard deviation calculating mould Block resets and recalculates, and the standard deviation that collection a period of time calculates in the effective module of high level judges RTS skip signals the most Threshold value.Filtered signal and standard deviation threshold method are compared, and this saltus step are assert for RTS noise, product more than threshold value Raw Pulse Width Control rising edge sampling module gathers corresponding meansigma methodss as the corresponding saltus step amplitude of this grade of RTS noise.Otherwise Regard as Gaussian noise saltus step.Wherein filtering part realizes the triangular pulse that saltus step in primary signal is filtered into different amplitudes Signal, threshold level generation part are realized and calculate Gaussian noise standard deviation conduct in primary signal in real time according to filtered signal Threshold value, holding part of sampling compare to determine out RTS saltus steps and gather corresponding RTS according to filtered signal and threshold level The amplitude of saltus step, completes the reconstruction of RTS signals.

The inventive method is according to the standard deviation of real-time Gaussian noise as the threshold value for judging RTS noise, automatic data collection threshold Value and rebuild RTS noise signal.First, using the collection of real-time automatic signal and calculating, improve the speed of RTS noise reconstruction And efficiency, compare with tradition Processing Algorithm and improve precision and efficiency of detecting；Second, using real-time gaussian signal standard deviation As threshold value, compare more accurate as threshold value with the standard deviation of whole signal, can effectively reduce temperature, space radiation etc. The signal standardss that degeneration of the external environment condition to the signal noise amplitude for affecting and then causing of device working environment causes are poor (i.e. RTS noise decision threshold) change, improve whole RTS noise signal detection with rebuild credibility.

Claims (1)

1. a kind of automatic real-time reconstruction method of multistage RTS noise for being applied to cmos image sensor, it is characterised in that include with Lower step：

The first step, when external noise signals arrive, through formula

$H\left(z\right)=\underset{i=0}{\overset{L/2-1}{\Σ}}\left(a_i{z}^{-i}\right)-\underset{j=L/2}{\overset{L-1}{\Σ}}\left(b_j{z}^{-j}\right)$

$\underset{i=0}{\overset{L/2-1}{\Σ}}{a}_i=1$

$\underset{j=L/2}{\overset{L-1}{\Σ}}{b}_j=1$

Filter function, complete the transformation of noise signal, the saltus step in primary signal such as be all converted at the triangle of amplitude Pulse；

In formula, L represents whole filter length, a_iRepresent the rising width of triangular pulse, b_jRepresent the decline width of triangular pulse Degree；

Second step, triangular pulse is calculated by absolute value, all of negative-going pulse is changed into direct impulse；

All pulses are carried out trailing edge detection by the 3rd step, whenever a trailing edge is detected indicate that original noise In once saltus step generation；

4th step, is controlled to calculate the standard deviation of original noise with the trailing edge signal for detecting, whenever detecting one Individual trailing edge signal, just recalculates standard deviation to original noise；

5th step, the standard deviation amplitude to calculating carry out real-time sampling, detect signal by a time delay control by trailing edge System collection standard deviation is used as RTS judgment thresholds；

6th step, filtered triangular pulse is compared with the standard deviation for collecting by gain, using standard deviation as sentencing The threshold value of disconnected RTS signals, determines that triangular pulse corresponding saltus step in part is RTS noise signal；

7th step, whenever a RTS noise saltus step is detected, resets to mean value calculation, recalculates；

8th step, by the RTS signals for detecting through time delay, controls the meansigma methodss for calculating are sampled and kept, samples Average value signal be the amplitude of this section of RTS noise saltus step.