Criteria for Digital Camera Image Quality Recent Developments in Criteria for Digital Camera Image Quality

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  • Criteria for Digital Camera Image Quality Recent Developments in Digital Airborne Cameras

    11th Annual Z/I Imaging® Camera Conference Keystone, September 21, 2007

    Prof. Ralf Reulke, Dr. Andreas Eckardt

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    New possibilities & available technology becomes important for digital camera development and applications

    Digital sensors (VIS, IR, LIDAR, RADAR, hyperspectral systems) Direct geo-referencing (determination of EO for each camera

    frame or line) Direct coreferencing and alignment of high resolution stereo

    channels with the multispectral channels allows combined stereo & remote sensing

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    Absolute radiometry (remote sensing) Geometric & radiometric lab-calibration of the whole sensor

    (as function of air pressure & temperature)

    Real time processing capabilities Wireless data transmission New applications – Virtual glob

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    3D globe viewer

    3D globe viewer with elevations and satellite images (Virtual Globe) Major players in the Virtual Globe arena are Google Earth, Microsoft’s Virtual Earth and NASA World Wind Search for locations through queries and user-interface controls Add data onto the map, like roads, political boundaries and basic image overlays Find out information about local businesses, driving directions and other interesting thinks through this concept Through API’s and XML-based interfaces, developers and advanced users can create new functions and data products


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    Sensors Requirements Detector Arrays, Resolution (Improvement), Technology Terrestrial, Airborne and Space Borne Imaging Systems Quality assessment for imaging systems

    New Applications Sensor & Data Fusion Radiometry / Classification


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    Digital Camera-Systems

    Motion of the camera

    Optical system (& filter)

    Discretize element

    Continues (analogues) Object

    Discrete (digital) Image

    EO determination GPS & INS

    Continues (analog) filtered image + EO

    Digital photogrammetric camera-system


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    Requirements (Geometry)

    Number of pixel in each image direction Area to cover and object resolution E.g. A=2 ·2 km² & Δ=20 ·20 cm² ↔ 10,000 ·10,000 pixel = 100 MPixel

    Resolution = ground sampling distance (GSD) Sampling theorem, well suited optics

    Optical system requirement from Pixel distance (PD) Optics resolution [lp/mm] = 1000 / (2 · Pixel Distance [µm]) E.g. Δ=10µm → 50 lp/mm

    Image smear (optics, pixel size, airborne platform movement) can be described by Gaussian σ≈0.5..1 PD

    Airplane speed ≈ 70 m/s, GSD=10cm → 1ms integration time= 0.7·Δ smear

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    System Parameters

    Field of View (Degree) Swath width (km) Instantaneous FOV (micro radian) Number of spectral bands and spectral ranges Quantization (Dynamic Range)

    The Dynamic Range of the Detector is defined by the ratio of saturation output to RMS noise in the dark. The Dynamic Range for all pixels is in the range of 12-14 Bit

    MTF (Modulation Transfer Function) curves Weighted MTF for the Sensor at Nyquist frequency and at a fixed readout frequency

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    Optics Parameter

    Effective Focal length (mm) Aperture - F number Wavelength range (Nanometer) Aberration (spherical, coma, field curvature, astigmatism, distortion, lateral color) PSF / MTF

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    Focal plane / detector subsystem

    Detector types, number of pixels Effective Pixel distance (pitch) and pixel size (micron) Spectral sensitivity, spectral bands Charge saturation (electron) quantum efficiency (electron/photon), Scale factor, responsivity Pixel rate and line rate Shutter options and readout timing. Focal plane dimensions Temperature of Operation

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    Focal plane / detector subsystem

    Quantization levels and dynamic range (number of effective bits) Linearity Blooming (%) The sensor system shall have an anti blooming provision in across track direction Smear (%)

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    Sensor Design

    Detector array CCD-Matrix, CCD-line

    Optics Assembling

    Number of focal plane How to fill the gaps

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    High Resolution Detector-Arrays, CCD-Matrices

    High resolution matrices (> 100 MPixel) are available Commercial high resolution photo systems in a price range up to 10 T€

    have > 20 Mega-Pixel Matrices ≈100 Mpixel matrices seem to expansive for standard applications

    KAF-31600 6496 x 4872 6.8µm square pixel

    31.6Mpixel Kodak

    KAF-39000 7216 x 5412 39Mpixel Kodak

    FTF5066 5kx6.6k 7.2µm square pixel

    33Mpixel DALSA

    ???? 10.56x10.56k 111Mpixel DALSA

    CCD 595 9kx9k 81Mpixel Fairchild Imaging

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    Digitale Backs

    eyelike Jenoptik Hasselblad (former: Imacon) ( Leaf

    Leaf Aptus 75, 33 Mio. Pixel (Dalsa?)

    PhaseOne ( PHASE ONE’S 39 Mio. Pixel (Kodak?)

    Sinar ( Sinarback eMotion75 with 33 million pixels

    Digital backs for airborne systems

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    New Sensor Technologies The Feature: Sensors with very high frame rate

    Fairchild Imaging has produced 9k x 9k sensors for many years 2 f/s

    The Challenge: 8k x 8k @ 1000 f/s Most challenging requirement is 67 Gigapixel data rate Fairchild Imaging 1000 f/s sensors produced for many years

    Fairchild Imaging CCD 595 9k x 9k CCD

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    New Sensor Technologies Hybrid Low Light Level Applications

    Xinqiao (Chiao) Liu, Boyd A. Fowler, Steve K. Onishi, Paul Vu, David D. Wen, Hung Do, and Stuart Horna, CCD / CMOS Hybrid FPA for Low Light Level Imaging, Fairchild Imaging, Inc., & U.S. Army Night Vision and Electronic Sensors Directorate Combines CCD imaging characteristics (e.g. high quantum efficiency, low dark current, excellent uniformity, and low pixel cross talk) with High speed, low power and ultra-low read noise of CMOS readout technology

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    New Sensor Technologies Hybrid Low Light Level Applications

    Microscopy Live cell fluorescence Fixed cell Confocal

    X-ray Imaging Radiography Fluoroscopy X-ray crystallography

    Astronomy & Space Research Adaptive optic wave front sensor Startrackers Environmental sensing

    Night Vision Near Term -- aircraft, vehicle, fire control Medium Term -- manportable


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    New Sensor Technologies High Resolution RGB - Sensors

    In difference to film typical RGB-sensors has a filter raster on the chip

    Foveon X3 image sensors have three layers of pixel sensors Sigma SD9 (2268 x 1512 pixel)

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    dIGIcam-K14 Geometrische Auflösung

    red green blueColour

    31cm 22cm 28cm

    Parameter Hight a.g. 550m

    Pixel size 8μm Focal legth 28mm Scale 19000 GSD (theor.) 16cm Bayer pattern

    Colour interpolation Undersampling: full detail/colour not attained Blur filters to reduce aliasing artifacts

    Bayer pattern decomposition

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    High Resolution Detector-Arrays, CMOS-Detector

    Lower power usage Integration of additional circuit on-chip Lower system cost Direct pixel access Non-linear response characteristics

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    (Geometric) Resolution Improvement

    Subsempling techniques, only for still imaging JenScan- Camera (Kontron-Progress-Camera) Heimann

    Biometric Systems Typical CCD-matrix with much smaller pixel size, moving in a

    sub-pixel range From 3x3 up to 6x6 sub-sampling steps Problems: SNR & MTF / moving objects

    Using more than one array Problem: Filling the gaps

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    Resolution Improvement

    The JVC Camcorder GC-QX3U uses AIS (Accurate Image Shift). Lens features high quality optics including two aspherical lenses Image-shift technology that doubles the image data UXGA (1600 x 1200) 1.92 Megapixel Digital Stills with Pixel Shift


    See staggered array – SPOT 5

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    High Resolution Detector-Arrays, CCD-Lines

    Manufacturer Model Photopixel Size [µm²]

    Atmel TH7834 12000 6.5×6.5 Atmel c