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Modelling, calibration and correction of nonlinear illumination-dependent fixed pattern noise in logarithmic CMOS image sensors. Dileepan Joseph and Steve Collins Department of Engineering Science University of Oxford, England. Outline. Logarithmic image sensors Pixel modelling - PowerPoint PPT Presentation
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Modelling, calibration and correction of nonlinear
illumination-dependent fixed pattern noise in logarithmic
CMOS image sensors
Dileepan Joseph and Steve Collins
Department of Engineering Science
University of Oxford, England
May 21-23, 2001 IMTC, Budapest (IEEE) 2
Outline
• Logarithmic image sensors
• Pixel modelling
• Fixed pattern noise (FPN)
• Sensor calibration
• Image correction
• Summary and conclusions
May 21-23, 2001 IMTC, Budapest (IEEE) 3
Logarithmic image sensors
• CMOS versus CCD image sensors– Electronics placed on same die as pixels– Cost, power consumption, size, weight– Quantum efficiency, yield, price pressure
• Logarithmic versus linear pixels– Continuous sensing, random access– High dynamic range, low bit rate– Resolution, sensitivity, frame rate
May 21-23, 2001 IMTC, Budapest (IEEE) 4
Pixel modelling
• Physical model • Abstract model
y)uncertaint (noise,error
leakage) e(photodiod bias
slope) old(subthreshgain
voltages)(thresholdoffset
response
eilluminanc
ln
c
b
a
y
x
xcbay
May 21-23, 2001 IMTC, Budapest (IEEE) 5
Fixed pattern noise (FPN)
• Offset (aj) variation (1 j N pixels)
• Offset and gain (bj) variation
• Offset, gain and bias (cj) variation
ijij xcbay lnˆ
ijjij xcbay lnˆ
ijjjij xcbay lnˆ
May 21-23, 2001 IMTC, Budapest (IEEE) 6
Sensor calibration
• Calibrate the sensor with images yij of M uniform illuminances xi (e.g. white paper)
• Extract parameters by minimising the mean square error
M
i
N
jijij yy
MNMSE
1 1
2ˆ1
May 21-23, 2001 IMTC, Budapest (IEEE) 7
Sensor calibration cont’d
• Calibration error is 3.9, 1.9 and 0.9 for one, two and three parameter models
• Calibration error versus illuminance differs markedly
M
i
N
jijij yy
DOF 1 1
22 ˆ1
May 21-23, 2001 IMTC, Budapest (IEEE) 8
Image correction
• Left to right: original plus one, two and three parameter FPN corrected images
• Top to bottom: apertures of 1.8, 4, 8 and 16 f-stops
• Inter-scene plus intra-scene dynamic range equals 67 dB
May 21-23, 2001 IMTC, Budapest (IEEE) 9
Image correction cont’d
May 21-23, 2001 IMTC, Budapest (IEEE) 10
Summary and conclusions
• Physical and abstract pixel model– Offset, gain, bias and error
• Parameter variation causes FPN– Calibration with uniform illuminance– Results indicate FPN is nonlinear
• FPN correction is necessary– Digital correction of images– More robust analogue circuits
May 21-23, 2001 IMTC, Budapest (IEEE) 11
Acknowledgements
• Many thanks to the Natural Sciences and Engineering Research Council of Canada and the Engineering and Physical Sciences Research Council of Britain for their generous support.