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Human vision

Human vision. The image is formed on retina (sítnice) The light is focused on retina by lens (čočka) Retina contains two types of receptors: rods (tyčinky) for grey-scale vision in darkness (about 100 mil.) cones (čípky) for color vision (about 6,5 mil.)

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Human vision

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  1. Human vision • The image is formed on retina (sítnice) • The light is focused on retina by lens (čočka) • Retina contains two types of receptors: • rods (tyčinky) for grey-scale vision in darkness (about 100 mil.) • cones (čípky) for color vision (about 6,5 mil.) • There are 3 types of cones for color vision (red, green, blue),the blue cones are substantially less sensitive than the other two • Each eye acquires 2D discrete color image • The final 3D image is formed from two 2D images (stereo vision)

  2. Camera vision Basic features of CCD cameras http://www.roperscientific.com/ccd/library_encyclopedia.shtml

  3. Quantum Efficiency (QE) • Example of the QE curve for two versions of a given camera

  4. Noise types (druhy šumu) • NR - Readout noise of the CCD (vyčítací šum) • NR [e-/pixel] = Nr = uncertainty in quantifying the electronic signal • Nr [e-/pixel] = readout noise specified by the producer • Depends on: • pre-amplifier design • post-amplifier electronics • CCD temperature (the lower, the lower the noise) • readout speed (the faster, the higher the noise) • ND – Dark current (Dark charge noise) (šum náboje ve tmě) • ND [e-/pixel] = SD1/2 = statistical fluctuations of SD • SD [e-/pixel] = Nd * time = dark charge signal • Nd [e-/pixel/sec] = dark charge specified by the producer • Depends on: CCD temperature (the lower, the lower the noise)

  5. Noise types (druhy šumu) • NP – Photon shot noise (fotonový šum) • NP [e-/pixel] = SP1/2 = statistical fluctuations of SP • SP [e-/pixel] = I * QE * time = measured signal • I [photons/pixel/sec] = photon flux (light intensity) • QE [e-/photon] = quantum efficiency specified by the producer • Depends on: only I, QE, time • NT – Total noise (celkový šum) • NT [e-/pixel] = (NR2 + ND2 + NP2)1/2 • Signal-to-noise ratio (SNR or S/N) • S/N = measured signal / total noise = SP / NT

  6. SNR Example • Example of different signal-to-noise ratio for given image

  7. Dynamic range (dynamický rozsah) • Dynamic range (camera) = number of bits in A/D converter • specified by the producer • 8 bit = 256 : 1 • 12 bit = 4096 : 1 • 16 bit = 65536 : 1

  8. Dynamic range (dynamický rozsah) • Dynamic range (real) = full well capacity / readout noise • specifies the real dynamic range • full well capacity depends on pixel size • readout noise depends on readout speed • high resolution (6.8 mm pixel size) & high speed (5 MHz): • 45 000 e- / 20 e- = 2 250 : 1  11,14 bit • high resolution (6.8 mm pixel size) & low speed (500 kHz): • 45 000 e- / 7 e- = 6 429 : 1  12,65 bit • low resolution (24 mm pixel size) & high speed (1 MHz): • 350 000 e- / 19 e- = 18 421 : 1  14,17 bit • low resolution (24 mm pixel size) & low speed (50 kHz): • 350 000 e- / 5 e- = 70 000 : 1  16,10 bit

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