2 Why Attend this Presentation? After attending this presentation you can…compare the sensitivity of cameraswith respect to temporal and spatial noiseusing EMVA 1288 data sheets.You understand the role ofGain (doesn’t matter)Pixel size (doesn’t matter)Bright light (the key)Beware : All formulas in this presentation will drop out of the sky For details see the standard and the white papers.
4 Gain is not Sensitivity Example:Camera ACamera BCamera A yields an image twice as bright as camera BDoes that mean that camera A is twice as sensitive as camera B? No!Increase the Gain of camera B until the images have equal brightness (Gain=2)Does that mean camera B is now as sensitive as camera A ?No! Multiplying each pixel x2 in software has the same effect…The Gain has no effect on the sensitivity of a camera*).*) At least with today’s digital cameras
5 Sensitivity is the ability to deliver high image quality on low light. What is Sensitivity?Example:A : 10 ms exposureB : 20 ms exposureCamera A yields the same image quality as camera B.Camera A needs half the amount of light as camera B in order to achieve that.Camera A is twice as sensitive as camera B !Sensitivity is the ability to deliver high image quality on low light.
6 Defining Image Quality Image Quality = Signal-to-Noise Ratio (SNR)bright signal – dark signalnoiseSNR does not depend on Gain Gain increases signal as well as noise.SNR does not depend on Offset Offset shifts dark signal as well as bright signal.There are different kinds of noise:total noise = temporal noise + spatial noise=
7 Different Kinds of Noise Total NoiseVariation (= non-uniformity) between the grey values of pixels in a single frame.Spatial NoiseVariation between the grey values of pixels if the temporal noise is averaged out.Temporal NoiseVariation (=flicker) in the grey value of the pixels from frame to frame.x, yx, yx, y
9 Light is NoisyNp = 6 photonslight sourceexposure timeNp = Number of photons collected in a single pixel during exposure timeNp varies from measurement to measurement.Light itself is noisy.Physics of light yields:with mean number of photonsImage quality ~ amount of light
10 No camera can yield a higher SNR than the light itself. SNR DiagramDraw the SNR in a double-logarithmic diagram.Take the logarithm to a base of 2.SNRp yields a straight line with slope = ½.Real cameras live right below the light’s SNR curve.No camera can yield a higher SNR than the light itself.
11 Axes of the SNR DiagramCommon units for SNRSNR = x : 1SNRbit = log2 SNR = ln SNR / ln 2SNRdB = 20 log10 SNR = 6 SNRbitSpecial SNR valuesExcellent*) SNR = 40:1 = 5…6 bitAcceptable*) SNR = 10:1 = 3…4 bitThreshold SNR = 1:1 = 0 bitNumber of photons collected in one pixel during exposure timeGiven as logarithm to the base of 2Example µp = 1000 ~ 1024 = 210 10 on the scale+1 double exposure; -1 half exposure*) The definitions of “excellent” and “acceptable” SNR origin from ISO 12232
12 Quantum Efficiency (QE) = Not every photon hitting a pixel creates a free electron.number of electrons collectednumber of photons hitting the pixelQE heavily depends on the wavelength.EMVA 1288 gives QE as table or diagram.QE < 100% degrades the SNR of a cameraTypical max QE values : 25% (CMOS) … 60% (CCD)Quantum Efficiency (QE) = 100%QE [%]lambda [nm]blue green red
13 Quantum Efficiency in the SNR Diagram SNRe of the electronsSNRe is the SNRp curve is shifted to the right by |log2 QE|.Examples:QE=50% = 1/2 shift by 1QE=25% = 1/4 shift by 2A high quantum efficiency yields a sensitive camera.
14 *) Otherwise you get high fixed pattern noise at saturation. analog signal12 bit8bit subsetno Gainmin Gainmax GainA camera saturates…if the pixel saturatesif the analog-to-digital converter saturatesThe useful signal range lies between saturation and the noise floorAt minimum Gain the ADC saturates shortly before the pixel*)The number of electrons at saturation is the Saturation CapacityDo not confuse saturation capacity with full well capacity (pixel only).pixel saturates11128Gainuseful signal range81111noise floorThe saturation capacity depends on the Gain.All scales are log2*) Otherwise you get high fixed pattern noise at saturation.
15 *) You can if you use loss-less compression Quantization NoiseRule of thumb: the dark noise must be larger than 0.5Corollary: With a N bit digital signal you can deliver no more*) than N+1 bit dynamic range.Example : A102f camera with 11 bit dynamic range will deliver only 9 bit in Mono8 mode. Use Mono16!Have at least ±1.5 DN noise.*) You can if you use loss-less compression
16 Saturation in the SNR Diagram At saturation capacity SNRe becomes maximum.The corresponding number of photons saturating the camera is:Typical saturation capacity values are 30…100 ke- (“kilo electrons”).A high saturation capacity yields a good maximum image quality.
17 Dark Noise EMVA 1288 model assumption: Camera noise = photon noise + dark noise*)Dark noise = constantDark noise is measured by the standard deviation of the dark signal in electrons [e-]The model approximates real world cameras pretty good for reasonable exposure times and reasonable sensor temperature.Typical dark noise values are 7…110 e-*) Dark Noise is not to be confused with Dark Current Noise which is only a fraction of dark noise.
18 Dark Noise in the SNR Diagram SNR without photon noise:SNRd yields a straight line with slope = 1.The minimum detectable signal is found by convention at SNRd=1*) were signal=noise.A low dark noise yields a sensitive camera.*) In the double-logarithmic diagram SNR=1 equals log(SNR) = 0
19 The Complete SNR Diagram Overlaying photon noise and dark noise yields:withThe curve starts atand ends atAn EMVA 1288 data sheet provides all parameters to draw the curve, e.g. in Excel:Quantum efficiency QE [%] as a function of wavelengthDark noise sd [e-]Saturation capacity µe.sat [e-]
20 A high dynamic range is especially important for natural scenes. Limits within one imageThe brightest spot in the image is limited by µp.satThe darkest spot in the image is limited by µp.minDynamic Range = brightest / darkest spot*)A high dynamic range is especially important for natural scenes.*) This equation holds true only for sensors with a linear response.
22 Were Does the Data Come From? Example : At Basler a fully automated camera test tool ensures quality in productionEvery camera produced will be EMVA 1288 characterized (done for 1394 and GigE already)Customer benefitsGuaranteed qualityFull process controlParameters can be given typical + range rangeOther manufacturers have similar measuring devices in production
23 The Camera Comparer Select cameras A and B Select wavelength (white 545 nm = green)Select SNR want read #photon ratioSelect #photons have read SNR ratio
24 How many Photons do I Have? The hard way to get #photonsMeasure the radiance RCompute µpThe easy way to get #photonsUse EMVA1288 characterized camera to measure #photonsy : grey value in digital numbers [DN] read from viewerQE : quantum efficiency for given wavelength (white light is tricky…) get from data sheetK : conversion gain for operating point used for characterization (esp. Gain) get from data sheetSome ways to influence #photonsExposure time µp is proportional to Texp Typical values are 30fps) 30µs … 33ms 1:1000 10 bitLens aperture µp is proportional to (1/f#)^2 Typical f-stops are 16, 11, 8, 5.6, 4, 2.8, 2, 1.4 1 : 128 7 bitResolution µp is proportional to 1 / number of pixels 2MPixel : VGA 1 : 7 3 bitDistance to Scene µp is proportional to 1 / (distance to scene)^2
25 Larger Pixels DO NOT result in a more sensitive camera. The Pixel Size Myth…A patch on the object’s surface radiates lightThe lens catches a certain amount of light depending on the solid angleThe lens focuses the light to the corresponding pixel no matter how large the pixel isFor a fair comparison of cameras…keep the resolution constant larger pixels require larger focal lengthkeep the aperture diameter d = f / f# constant larger pixels have larger relative apertureLarger Pixels DO NOT result in a more sensitive camera.
26 Example Start pixel pitch a focal length f aperture diameter d relative aperture f# = f / ddistance to object ao = constaodaf#fdStep 1 : double pixel pitch a 2ayields four times the amount of lightbecause of quarter number of pixels2af#fStep 2 : double focal length f 2f while relative aperture f# = constback to original number of pixelsyields four times the amount of lightbecause of twice the aperture diameter2d2af#2fStep 3 : double relative aperture f# 2f#yields same amount of lightbecause of original number of pixelsbecause of original aperture diameter dalthough the pixel pitch is doubled (q.e.d.)d2a2f#2f
27 Don’t Get Confused - Pixel Size Matters a Lot*) For example smaller pixels…yield less aberrations because of near-axis opticsyield smaller and cheaper opticsallow larger number of pixelshave less problems with micro lensesFor example larger pixels…yield sharper images because less resolving power of the lens is requiredkeep you out of the refraction limit of the lenshave a better geometrical fill factor (area scan)have a larger full well capacityMore…*) Although not with respect to sensitivity
28 Comparing Sensitivity without Graphics Rules of ThumbFor low light (SNR1) compare µp.min = sd / QEFor bright light (SNR>>1) compare QEExampleA102f (CCD) : QE = 56%, sd = 9 e µp.min= 16 p~A600f (CMOS) : QE = 32%, sd = 113 e- µp.min= 353 p~For low light the A102f is 22 (=353/16) times more sensitive than the A600fFor bright light the A102f is 1.8 (=56/32) times more sensitive than the A600f
30 Principal model of a single pixel Spatial NoisePrincipal model of a single pixellightgrey valuegain++offsetThe offset differs from pixel to pixel add offset noise DSNUThe gain differs from pixel to pixel add gain noiseGain noise is proportional tothe signal itself.
31 Spatial Noise in the SNR Diagram Offset NoiseAdds to dark noiseGain NoiseNew kind of behaviorFlat line in SNR diagramResulting SNR formula
32 Spatial Noise is relevant esp. for CMOS cameras. Spatial Noise EffectsCCDCMOSSpatial Noise is relevant esp. for CMOS cameras.
33 operating point were the correction values have been taken Pixel CorrectionSpatial nose can be corrected inside a camera.Each pixel get it’s own offset to compensate for DSNU…..and it’s own gain to compensate for PRNUMost CMOS cameras have a pixel correctionDepending on the sensor even more correction types are requiredCCD without shadingCMOS with shadingoperating point were the correction values have been taken
34 Stripes EMI based stripes Structure based stripes High frequency disturbing signal is added to the video signalThe maxima of the disturbing signal are shifted between linesThis results in diagonal stripes which tend to move and pivot with temperatureStructure based stripesThere are multiple signal paths in the sensor/camera with slightly different parameters (gain, offset)This results in fixed horizontal or vertical stripesExample: even-odd-mismatch
35 The Spectrogram3 different camerasX-Axis : horizontal distance between stripes in [pixel]Y-Axis : amplitude at the corresponding frequency in #photonsThe ideal camera has white noise only flat spectrogramNoise floor height indicates minimum detectable signalPeaks indicate stripes in the image
36 Conclusion With EMVA 1288 data sheet you can… compare the sensitivity of cameraswith respect to temporal and spatial noiseRemember:Gain doesn’t matterPixel size doesn’t matterNothing beats having enough light Get Started:Get the camera comparer and play around with the parameters.Get a camera with EMVA1288 data sheet and determine the #photons in your application.
37 Thank you for your attention! Camera signals are interfaced to external circuitry via two connectors on the side of the camera.One connector is a standard IEEE-1394 socket. This is used to transmit video data and commands between the host computer and the camera.The second connector is a 9-pin, micro D connector. Two pins on the connector are an input for an external trigger signal. The external trigger can be used to trigger exposure start. The external trigger feature is part of the digital camera specification.Two pins on the connector are an output for the trigger ready signal and two pins are an output for the integrate enabled signal. These signals are unique to Basler cameras.We will discuss the use of the external trigger, trigger ready, and integrate enabled signals in more detail later in the presentation.The back of the camera also contains a green LED and a yellow LED. The green LED is used to signal power present and the yellow LED will blink if an error condition is present.More info : > Technologies > EMVA 1288Contact me :