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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

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Dileepan joseph and steve collins department of engineering science university of oxford england

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
Outline illumination-dependent fixed pattern noise in logarithmic CMOS image sensors

  • Logarithmic image sensors

  • Pixel modelling

  • Fixed pattern noise (FPN)

  • Sensor calibration

  • Image correction

  • Summary and conclusions

IMTC, Budapest (IEEE)


Logarithmic image sensors
Logarithmic image sensors illumination-dependent fixed pattern noise in logarithmic CMOS 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

IMTC, Budapest (IEEE)


Pixel modelling

Physical model illumination-dependent fixed pattern noise in logarithmic CMOS image sensors

Abstract model

Pixel modelling

IMTC, Budapest (IEEE)


Fixed pattern noise fpn
Fixed pattern noise (FPN) illumination-dependent fixed pattern noise in logarithmic CMOS image sensors

  • Offset (aj) variation (1  j  N pixels)

  • Offset and gain (bj) variation

  • Offset, gain and bias (cj) variation

IMTC, Budapest (IEEE)


Sensor calibration
Sensor calibration illumination-dependent fixed pattern noise in logarithmic CMOS image sensors

  • Calibrate the sensor with images yij of M uniform illuminances xi (e.g. white paper)

  • Extract parameters by minimising the mean square error

IMTC, Budapest (IEEE)


Sensor calibration cont d
Sensor calibration cont’d illumination-dependent fixed pattern noise in logarithmic CMOS image sensors

  • Calibration error is 3.9, 1.9 and 0.9 for one, two and three parameter models

  • Calibration error versus illuminance differs markedly

IMTC, Budapest (IEEE)


Image correction
Image correction illumination-dependent fixed pattern noise in logarithmic CMOS image sensors

  • 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

IMTC, Budapest (IEEE)


Image correction cont d
Image correction cont’d illumination-dependent fixed pattern noise in logarithmic CMOS image sensors

IMTC, Budapest (IEEE)


Summary and conclusions
Summary and conclusions illumination-dependent fixed pattern noise in logarithmic CMOS image sensors

  • 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

IMTC, Budapest (IEEE)


Acknowledgements
Acknowledgements illumination-dependent fixed pattern noise in logarithmic CMOS image sensors

  • 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.

IMTC, Budapest (IEEE)