How to Measure Anti-Blooming (2)

August 31st, 2015

This blog will focus on the measurement of the anti-blooming capabilities of a monochrome sensor.  As known, blooming occurs when a (group of) pixel(s) is overexposed and the photodiode can no longer store all generated charges.  With an anti-blooming structure inside the pixel, the excessively generated charges can be drained, e.g. excessive electrons can escape through the reset transistor to the power supply.  But every anti-blooming structure has its limitations, and with this measurement we try to find the limits of the anti-blooming structure present in a pixel.

What is checked with this measurement is simply the size of an overexposed sensor area.  If the illumination level is increased, ideally the size of such an overexposed area should stay constant even with an overexposure.  But in reality and while the illumination level is increasing, the size of the overexposed area will grow due to several mechanisms :

  • Diffraction at the various edges of the metal lines above a pixel will “guide” photons to neighbouring pixels,
  • Multiple reflections in the multi-level layer structure above the pixels can also “guide” photons to neighbouring pixels,
  • Fresnel reflections on the sensor surface and on the lens surface can result in ghosting structures,
  • Diffraction and reflections at the edges of the iris/diaphragm present in the optical system,
  • Optical and electrical cross-talk between the pixels,
  • Light piping underneath the metal lines and/or metal shields,
  • Blooming effects after the pixels are saturated and the anti-blooming is no capable of handling the excess charges.

All these effects are proportional to the amount of light that comes to the sensor.  In the measurements, the amount of light to the sensor is modulated by changing the exposure time.  That means that all these effects can be written down with a formula that contains a linear coefficient in relation to the exposure time.  This is true for all abovementioned effects, except for the blooming.  The blooming also has a linear relationship with exposure time, but with a particular threshold.  Below a certain exposure time, the pixel will not be saturated or the anti-blooming capabilities are performing well so that no blooming occurs.  Above a certain exposure time, the blooming effect will start and will be added to all other effects that grow the overexposure sensor area.  So the measurement will explore the size of an overexposure area as a function of exposure time and will try to find the knee point at which level the blooming effect occurs.

The measurement is performed as follows (to measure the anti-blooming along columns in vertical direction) :

  • The sensor is illuminated with a target that allows a black-white transition about half-way the sensor height, and the black-white transition horizontally crosses a column in the middle of the sensor (e.g. column 380 out of 752 active columns)
  • The location of the black-white transition is monitored in the images generated by the sensor.  To do so, the balck-white transition is defined at a level of 75 % of the white part of the test target (75 % is randomly chosen, any other value can do the job as well),
  • The illumination of the target is kept constant (white fluorescent DC light), and to get different light levels on the sensor, the exposure time of the imager is changed from very small values to very large values,
  • While changing the exposure levels, the location black-white transition is constantly calculated to monitor the growth of the overexposed area.

Figure 1 shows one of the images captured at the onset of saturation, Figure 2 illustrates the situation at 10 times overexposure, Figure 3 is the result while overexposing the sensor 100 times, and finally Figure 4 illustrates a factor of 1000 times overexposure.

 

Figure 1 : Image of the test target at the moment the sensor starts to saturate [0015].

 

Figure 2 : Image of the test target at the moment the sensor is 10 times overexposed [0019].

 

Figure 3 : Image of the test target at the moment the sensor is 100 times overexposed [0029].

 

Figure 4 : Image of the test target at the moment the sensor is 1000 times overexposed [0039].

A simple software tool is developed to check for every exposure time, on which row the horizontal black-white crossing is occurring in the images.  If the pixels are not saturated yet, the software tool simply outputs row number “500”, which actually does not exist.  As soon as at a particular illumination level the pixels in the white region reach 75 % of saturation, the measurement tool outputs the row number at which the black-white transition occurs.  If the overexposed area reaches the top of the image, like shown in Figure 4, the output of the measurement tool is equal to “0”.  The result of this analysis is shown in Figure 5.

 

Figure 5 : Position of the black-white transition (indicated as row number) as a function of exposure time.

In Figure 5, from left to right, the following information is available :

  • For small exposure times (< 1 ms), the white pixels are not yet reaching 75 % of saturation, this is indicated by the row value equal to “500”,
  • For an exposure value of 1.28 ms, saturation occurs (= 75 %) and the black-white transition is located at row number “224”,
  • From this moment onwards the large white area starts growing slowly due to all kind of optical artefacts, listed already earlier in this blog,
  • For exposure times larger than 200 ms, the area of the white spot grows very fast, as can be seen in the graph.  This change in “speed” is due to the blooming artefact that apparently occurs at very high exposure levels.

To calculate a number for the anti-blooming capabilities of the sensor, the same data as present in Figure 5 is shown again on a linear scale as illustrated in Figure 6.

 

Figure 6 : The same information is shown as already illustrated in Figure 5, but now on a linear scale.

The two important regions (saturated but no blooming and saturated with blooming) are approximated by means of a linear regression line.  And as can be seen, below 174 ms exposure time, blooming plays no important role, but above 174 ms exposure time, blooming is dominating over all other artefacts.  The exposure time of 174 ms seems to be a cross-over exposure time.

The anti-blooming capability is then defined as the ratio of the exposure time at which saturation is reached (texp = 1.28 ms) and the cross-over exposure time (texp = 174 ms), resulting in an anti-blooming capability of 136 times overexposure.

In conclusion : a long story to explain a relative simple measurement.  More anti-blooming stuff to follow.

Albert, 28-08-2015.

How (not) to Measure Anti-Blooming (1)

August 10th, 2015

After several months of silence, here is a new blog about measuring image sensors.  This time the blooming and/or anti-blooming of an imager is analyzed.  Actually in this first blog about blooming, it will be shown how NOT to measure blooming.

Blooming is the effect that is showing up in the case of strong overexposure of the image sensor.  If the pixels are seen as a buckets and the photon-generated electrons are seen as the water contained in these buckets, it is clear that the maximum amount of water that can be stored in the bucket is limited.  If more light is falling on the pixels, more water needs to be stored in the buckets.  But once a bucket is completely filled, any extra water is going to spill over to the neighbouring buckets.  The last effect is being known as blooming.  Any means in the pixel to prevent blooming is called anti-blooming.

The intention of the measurement reported in this blog, is to check out the anti-blooming capabilities of an image sensor.  Ideally this can be done by overexposing a single pixel and check any blooming in the neightbouring pixels, but that is not easy to realize.  An alternative way of measuring the anti-blooming capabilities is to use a colour sensor and illuminate the device with monochrome light. If the sensor is illuminated with blue light, the green and red pixels will have a smaller light sensitivity to blue light and the blue pixel will saturate much faster than the green and red pixels.  Once the blue pixel is saturated, its anti-blooming should become active.  Without anti-blooming, the blue pixel will spill over its charge into the green pixel (direct neighbours) and red pixel (diagonal neighbour).  If spilling occurs, the sensitivity of the green and/or red pixel will increase and this can be measured by monitoring the green and red output signal.

What is explained above is realized and the result is shown in Figure 1.

 Figure 1 : Response of the different colour planes (R, G, B) of a CMOS sensor under illumination with blue light (470 nm).

For the three colour planes, the regression line of the linear response is created as well.  The ratio between B and G response is 4347/1119 = 3.9.  The ratio between B and R response is 4347/140 = 31.  Unfortunately (for the measurement), no change in response can be seen in the G or R channel once the B channel is saturated.  Conclusion the anti-blooming towards direct neighbours is at least a factor 3.9, towards diagonal neighbours is at least a factor 31.

A similar measurement can be done with red light.  The result is illustrated in Figure 2.

 Figure 2 : Response of the different colour planes (R, G, B) of a CMOS sensor under illumination with red light (630 nm).

This time, the ratio between R and G response is 1169/243 = 4.8.  The ratio between R and B response is 1169/135 = 8.7.  Unfortunately (for the measurement), no change in response can be seen in the G or B channel once the R channel is saturated.  Conclusion the anti-blooming towards direct neighbours is at least a factor 4.8, towards diagonal neighbours is at least a factor 8.7.

Finally, the sensor was illuminated with green light, and the 3 colour channels were checked as shown in Figure 3.

 Figure 3 : Response of the different colour planes (R, G, B) of a CMOS sensor under illumination with green light (525 nm).

The ratio between G and B response is 1301/365 = 3.6, the ratio between G and R response is 1301/178 = 7.3.  Also for this situation no blooming artifacts can be found.

In conclusion : the anti-blooming capabilities are at least for direct neighbours a factor of 7.3, for diagonal neighbours a factor of 31.  These numbers are relatively small, but the measurement technique applied is not capable of doing better.  The numbers reported are limited by the characterization method and not by the sensor.  So actually, what is shown in this blog is how NOT to measure the anti-blooming of a sensor, unless your device-under-test has a very poor anti-blooming performance.

Albert, 10-08-2015.

Harvest Imaging Forum 2015 : 3D Imaging with ToF

July 29th, 2015

The first session (10/11 Dec.) of the 2015 Harvest Imaging Forum is SOLD OUT.  Apparently Time-of-Flight is still a hot topic in the field.

There are still seats available for the second session (14/15 Dec.).

Albert, 29-07-2015.

Harvest Imaging Forum : 3D Imaging with ToF

July 2nd, 2015

I just want to give an update on the status of registrations :

- for the first session (10/11 Dec. 2015) 2 seats are left,

- for the second session (14/15 Dec. 2015) several seats are still available.

Some people were asking why such a hurry for a forum that will take place in 6 months from now ?  The reason has to do with the hotel reservation : to get an acceptable rate for the meeting package and for the rooms, the cancellation options offered by the hotel are very limited.  So to make sure that I can give a final GO/NO GO to the hotel without extra financial penalties, early as well as firm participant registrations are needed.  Thanks for your understanding.

Albert, 02-07-2015.

International Image Sensor Workshop 2015 : Conversion Gain Engineering

July 2nd, 2015

Several IISW2015 papers dealt with the attempt to obtain a large conversion gain to bring down the noise floor (expressed in noise equivalent electrons) of the imagers.  With a noise floor down to 0.25 electrons, a “standard” CIS could be applied in single electron detection. [Deliberately I do not call it "single photon detection" because we never have a QE of 100 %, so by definition we do not detect every photon.  The intention of the conversion gain engineering is to detect a single electron present in the PPD and/or at the FD node.]

Tohoku University demonstrated how to extract the various components of the floating diffusion capacitance, and to further lower this capacitance.  Their mainn focus was lowering the concentration of the FD junction and working without LDD at the drain side of the source follower.  A conversion gain of 243 uV/electron is reported.  [LDD's are normally introduced to reduce the effect of hot carriers, what about the hot carriers in this structure without LDD ?]  In a second paper of the same group, the LDD-less FD structure was implemented in a real device.  To overcome the limitation of the small full well capacity with a large conversion gain, the pixel has applied the LOFIC technique in the pixel.

Dartmouth School of Engineering published their work on Multi-Bit Quanta Image Sensors by showing a measurement histogram indicating that single electron detection was realized.  The sensor used in the experiment had a conversion gain of 242 uV/electron (just 1 uV/electron lower than Tohoku Univ. !).  The paper is suggesting that a conversion gain of 1 mV/electron may be realized in the near future.  Is was not mentioned how this can be done.  But for sure very advanced CIS technologies of 65 nm or less are needed.

Also worthwhile to mention is the work of CEA, in which they use a p-type in-pixel readout structure to obtain a conversion factor of 185 uV/electron.  This is still not large enough to perform single electron detection, but is moving in the right direction.

Caeleste presented a small test array based on the pixel that was presented by the same group at ISSCC a couple of years ago.  The p-type source follower is swept between accumulation and inversion to make the 1/f noise uncorrelated between various multiple sampling moments.  Apparently there are still problems to solve in this structure, but besides that, a conversion factor around 400 uV/electron was reported for s 180 nm CIS technology.

A bit in the same direction as the papers described above, is the work reported by ON Semiconductor (former Truesense Imaging, former Kodak) describing an EM-CCD.  The overall concept is not new, but after TI and E2V, ON Semi is the next one to put EM-CCDs on the market.  With the EM concept, the primary goal is not to reach a large conversion gain, but to reach very low (equivalent) noise levels.  To continue along the EM-line, E2V published their work on EM-CMOS, fabricated in a 0.18um process.

Albert, 02-07-2015.

 

International Image Sensor Workshop 2015 : Stacked Imagers

June 23rd, 2015

The fight on stacking has began.  After Sony’s presentation at ISSCC, others are following on the stacked road.  Omnivision shows their architecture on stacking with the TSV’s outside the imaging array.  They claim to have the technology ready to start production of stacked imagers with a pixel pitch of 1 um.  Olympus showed their improved work over the one presented two years ago at ISSCC.  Olympus has a contact between the two silicon layers for every group of 2×2 pixels.  They created a 16M pixel device with 4M direct contacts, each with 7.6 um pitch.  Extra added to the ISSCC paper is the CDS capability buried in the second layer of silicon.  Also remarkable : all circuitry on the top level silicon is p-type !  Because a metal light shield is used between the two layers of silicon, a PLS of -180 dB is obtained.  Giant steps forward in their stacked wafer-to-wafer imager process.

Like Olympys, also  NHK showed a wafer-to-wafer bonding using Au contacts.  Nice to get also some information about the technology of the bonding itself.  TSMC had a paper about the photon emission in a stacked CIS.  Of course the second layer with the processing circuitry in a stacked image sensor is not designed/optimized for imaging purposes, and consequently during operation the circuitry present in this layer can generate some light that can be captured by the top layer.  This is no longer PLS but SLP, because the light is coming in the opposite direction.  Also the last paper in this session came from TSMC and dealt with dark FPN improvement by a stacked CIS process.  Focus was put on the decomposition of the FPN by biasing/switching the TG in an appropriate way.

Albert, 23-06-2015.

International Image Sensor Workshop 2015 : Image Sensors for Digital Photography

June 22nd, 2015

The first session of IISW2015 was devoted to larger devices intended for digital still photogrpahy.  Samsung presented a 28M APS-C sensor with BSI technology.  It is not common to go after BSI for these large dies, but apparently time and yield is ready to apply BSI to these larger devices as well.  Remarkable dark performance : 9 electrons/s dark current at 60 deg.C, 1.8 electron of random noise at 24 dB gain.  The architecture is charactereized by 1 ADC for 2 columns, double column busses and an optimized read sequence to allow for binning.

Canon described their sensor with phase-detection auto-focus pixels in EVERY pixel.  This solution allows for no light shield in the auto-focus pixels and no interpolation of the auto-focus pixels.  This sensor is already avaialable in Canon cameras, but it is the first time Canon publishes technical information about the device.  Because of the dual photodiode in every pixel, every pixel is provided with two readout structures, so every pixel has 8 transistors.  Random noise level of 1.8 electrons is reported at gain = 32 for a single photodiode.

Also Sony presented a CMOS imager with auto-focus functionality in every pixel.  This sensor is provided with a diagonal pixel orientation, so that the rows have alternatively G pixels and R/B pixels.  To make this sensor compatible with the installed software base, first of all the pixel stream is converted into Bayer RGB.  Also of interest for this sensor architecture with a dual PD in every pixel is the option for HDR by using 1 PD/pixel for a short exposure and 1 PD/pixel for a long exposure time.

Teledyne DALSA published one of the very few CCD papers at the workshop, mainly large area devices, e.g. 32M, 60M and 250M.  Remarkable is the ultra low dark current for these devices : 2 pA/cm2 at 60 deg.C.  These low values make these devices very well suited for extremely large expsoure times.

 

Albert, 22 juni 2015.

International Image Sensor Workshop 2015 : General Trends

June 19th, 2015

Some interesting trends in image sensor technology for consumer applications are :

- the incorporation of deep trench isolation (DTI) between the pixels to lower the optical and electrical cross talk.  Announced were already DTI defined from the front side (ST) as well as the back side (Samsung), but new at the workshop are the DTIs that do not completely go through the thinned BSI silicon,

- building “walls” between the colour filters (called “buried CFA”) is finding its way to production.  These walls limit optical and spectral cross-talk,

- very thin optical stacks, down to 1.5 um for BSI sensors,

- incoroporation of focus pixels for auto-focusing purposes.  These focus pixels can be incorporated in a regular pattern, but sometimes a semi-random pattern is used as well.  Moreover, the focus pixels do not need to be all of the same size,

- stacked imager are more and more introduced.  During IISW 2009, the buss word was BSI, now it is “stacked”.  Stacked imagers are going to solve all the problems ….

- the incorporation of W pixels continues, in more recent devices, up to 50 % of the pixels are W pixels.

In conclusion : no major new technologies were introduced, neither any pixel size below 1 um, but everything is getting better in performance and more compact in size.

Albert, 19/06/2015.

Third HARVEST IMAGING FORUM

June 13th, 2015

As already announced earlier, also in 2015 there will be a Harvest Imaging Forum.  All forum information is now on-line, including agenda and registration form.  More info can be found at  www.harvestimaging.com/forum.php

Albert, 13-06-2015.

 

Third HARVEST IMAGING FORUM in December 2015

May 5th, 2015

After a very successful forums in 2013 and 2014, a third one will be organized in December, 2015, in Voorburg (the Hague), the Netherlands.  The basic intention of the forum is to have a scientific and technical in-depth discussion on one particular imaging topic.  The audience will be strictly limited to enhance and stimulate the interaction with the speaker(s) as well as to allow close contacts between the participants.

The subject of the third forum will be :

“3D Imaging with Time-of-Flight :

Solid-State Devices, Circuits and Architectures”.

 A world-level expert in the field,

dr. David STOPPA,

is invited and agreed to address and explain the ins and out of this important topic.

The agenda of the forum will be published soon, registration for the forum will start after the IISW2015.

 

Albert, 5/5/2015.