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Spatio-Temporal Quincunx Sub-Sampling.. and how we get there David Lyon.

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Presentation on theme: "Spatio-Temporal Quincunx Sub-Sampling.. and how we get there David Lyon."— Presentation transcript:

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2 Spatio-Temporal Quincunx Sub-Sampling.. and how we get there David Lyon

3 Overview  Sampling in Television and Film  The problems of aliasing  Filtering requirements  Conversion between differing formats  Problems that can occur  How we can mitigate some of the problems and maintain or improve quality

4 Sampling Theory  Harry Nyquist – 1889 to 1976  “The number of independent pulses that can be put through a telegraph channel per unit time is limited to twice the bandwidth of the channel”

5 Sampling Theory  Harry Nyquist – 1889 to 1976  “The number of independent pulses that can be put through a telegraph channel per unit time is limited to twice the bandwidth of the channel”  Later Nyquist-Shannon  “Exact reconstruction of a continuous-time baseband signal from its samples is possible if the signal is bandlimited and the sampling frequency is greater than twice the signal bandwidth”

6 Sampling Theory Frequency Amplitude Fs

7 Sampling Theory  Audio:  20kHz bandwidth, Fs = 44.1kHz, 48kHz Frequency Amplitude Fs

8 Sampling Theory  Audio:  20kHz bandwidth, Fs = 44.1kHz, 48kHz  Video:  5.75MHz bandwidth, Fs = 13.5MHz  30MHz bandwidth, Fs = 74.25MHz Frequency Amplitude Fs

9 Aliasing Frequency Amplitude Fs Nyquist Frequency

10 Aliasing  Frequencies above Fs/2 are “reflected” into the lower portion of the spectrum and become entangled with the low-frequency signals Frequency Amplitude Fs Nyquist Frequency

11 Aliasing  Frequencies above Fs/2 are “reflected” into the lower portion of the spectrum and become entangled with the low-frequency signals  These signals CANNOT be removed afterwards Frequency Amplitude Fs Nyquist Frequency

12 Aliasing  Frequencies above Fs/2 are “reflected” into the lower portion of the spectrum and become entangled with the low-frequency signals  These signals CANNOT be removed afterwards  Filtering BEFORE sampling is needed Frequency Amplitude Fs Nyquist Frequency

13 Image Sampling Horizontal - pixels Vertical - lines Temporal – frames

14 Image Sampling  Horizontal resolution  Sampling rate of 720, 1280, 1920 or 2048 samples/picture width Resulting resolution of 360, 640, 960 or 1024 cycles/pw

15 Image Sampling  Horizontal resolution  Sampling rate of 720, 1280, 1920 or 2048 samples/picture width Resulting resolution of 360, 640, 960 or 1024 cycles/pw  Vertical resolution  Sampling rate of 480, 576, 720, 1080 samples/picture height Resulting resolution of 240, 288, 360 or 540 cycles/ph

16 Image Sampling  Horizontal resolution  Sampling rate of 720, 1280, 1920 or 2048 samples/picture width Resulting resolution of 360, 640, 960 or 1024 cycles/pw  Vertical resolution  Sampling rate of 480, 576, 720, 1080 samples/picture height Resulting resolution of 240, 288, 360 or 540 cycles/ph  Temporal resolution  Sampling rate of 24, 25, 30, 50, 60... samples/second Resulting resolution of 12, 15, 25, 30 cycles/sec

17 Re-sampling  Image size changes are common

18 Re-sampling  Image size changes are common  Simple example of interpolating a 1080 picture to 480: Input resolution is 540 cycles/ph Output resolution is 240 cycles/ph (division by 2.25) Vertical Frequency Amplitude 1080 Vertical Frequency Amplitude 480 Filter Potential Alias

19 Re-sampling  Interpolation is only one part of the problem  Filtering is needed to control the signal spectrum and avoid the introduction of aliases  Simple interpolators are generally poor filters

20 Re-sampling  Interpolation is only one part of the problem  Filtering is needed to control the signal spectrum and avoid the introduction of aliases  Simple interpolators are generally poor filters  Alias terms are “folded” about the Nyquist point  Inverted in frequency, inverted “movement”  Highly noticeable to the human eye, which references its own internal 3D model

21 Re-sampling  Interpolation is only one part of the problem  Filtering is needed to control the signal spectrum and avoid the introduction of aliases  Simple interpolators are generally poor filters  Alias terms are “folded” about the Nyquist point  Inverted in frequency, inverted “movement”  Highly noticeable to the human eye, which references its own internal 3D model  Alias terms left in the image will be shifted again in any subsequent operations  Potentially cumulative problems

22 3D Sampling Horizontal - pixels Vertical - lines Temporal – frames Restricted by practical limitations Linked by aspect ratio and pixel shape

23 Spatio-Temporal Sampling Spatial - lines Temporal – frames Temporal Frequency Spatial Frequency Frame Rate No of Lines Spectrum Potential alias

24 Spatio-Temporal Sampling  Filtering:  Spatial – optical LPF and lens MTF Spatial - lines Temporal – frames Temporal Frequency Spatial Frequency Frame Rate No of Lines Spectrum Potential alias

25 Spatio-Temporal Sampling  Filtering:  Spatial – optical LPF and lens MTF  Temporal – integration time of sensor system Spatial - lines Temporal – frames Temporal Frequency Spatial Frequency Frame Rate No of Lines Spectrum Potential alias

26 Spatio-Temporal Sub-Sampling Temporal – frames Temporal Frequency Spatial Frequency Frame Rate No of Lines Spectrum Spatial - lines  Where is the filter? Potential alias

27 Up-conversion Temporal Frequency Spatial Frequency Frame Rate No of Lines ? Spectrum Temporal Vertical Horizontal

28 Up-conversion Temporal Frequency Spatial Frequency Frame Rate No of Lines  Adaptive filtering ? Spectrum Temporal Vertical Horizontal

29 Up-conversion Temporal Frequency Spatial Frequency Frame Rate No of Lines  Adaptive filtering  Motion compensation ? Spectrum Temporal Vertical Horizontal

30 Format Interchange Temporal Frequency Spatial Frequency 1080p 720p Film 1080i 480i 1080p (24) 15c/s30c/s0c/s 0c/ph 250c/ph 500c/ph

31 Format Interchange Temporal Frequency Spatial Frequency  Conversion between formats requires care 1080p 720p Film 1080i 480i 1080p (24) 15c/s30c/s0c/s 0c/ph 250c/ph 500c/ph

32 Format Interchange Temporal Frequency Spatial Frequency  Conversion between formats requires care  Mixing formats such as film and video is to be avoided 1080p 720p Film 1080i 480i 1080p (24) 15c/s30c/s0c/s 0c/ph 250c/ph 500c/ph

33 Format Interchange Temporal Frequency Spatial Frequency  Conversion between formats requires care  Mixing formats such as film and video is to be avoided  1080p down- conversion might raise new challenges 1080p 720p Film 1080i 480i 1080p (24) 15c/s30c/s0c/s 0c/ph 250c/ph 500c/ph

34 Over-sampling  Commonly applied to audio – eg 96kHz down to 48kHz  Allows the use of a high performance digital filter: Frequency Amplitude 96 Filter Frequency Amplitude 48

35 Over-sampling  Commonly applied to audio – eg 96kHz down to 48kHz  Allows the use of a high performance digital filter:

36 Over-sampling  Commonly applied to audio – eg 96kHz down to 48kHz  Allows the use of a high performance digital filter:  1080p allows similar gains for outputs of 720p and 1080i  Good temporal filtering must introduce delay

37 Over-sampling  Commonly applied to audio – eg 96kHz down to 48kHz  Allows the use of a high performance digital filter:  1080p allows similar gains for outputs of 720p and 1080i  Good temporal filtering must introduce delay  Film sampling at >1080 lines/ph also allows controlled down-sampling

38 Conclusion  Spatio-temporal quincunx sub-sampling (aka interlace) is likely to be with us for some time

39 Conclusion  Spatio-temporal quincunx sub-sampling (aka interlace) is likely to be with us for some time  Modern cameras and processing can stress the format unless care is taken

40 Conclusion  Spatio-temporal quincunx sub-sampling (aka interlace) is likely to be with us for some time  Modern cameras and processing can stress the format unless care is taken  Imprinted alias is difficult (or impossible) to remove  Camera integration is an important filter for interlace

41 Conclusion  Spatio-temporal quincunx sub-sampling (aka interlace) is likely to be with us for some time  Modern cameras and processing can stress the format unless care is taken  Imprinted alias is difficult (or impossible) to remove  Camera integration is an important filter for interlace  Poor anti-alias filtering leads to additional compression concatenation artefacts

42 Conclusion  Spatio-temporal quincunx sub-sampling (aka interlace) is likely to be with us for some time  Modern cameras and processing can stress the format unless care is taken  Imprinted alias is difficult (or impossible) to remove  Camera integration is an important filter for interlace  Poor anti-alias filtering leads to additional compression concatenation artefacts  1080p down-conversion could make the stress worse


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