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In the name of Allah In the name of Allah
the compassionate, the merciful
In the name of Allah In the name of Allah the compassionate, the - - PowerPoint PPT Presentation
In the name of Allah In the name of Allah the compassionate, the - - PowerPoint PPT Presentation
In the name of Allah In the name of Allah the compassionate, the merciful Digital Video Processing S. Kasaei S. Kasaei Room: CE 307 Department of Computer Engineering Sharif University of Technology E-Mail: skasaei@sharif.edu Web Page:
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Digital Video Processing
- S. Kasaei
- S. Kasaei
Room: CE 307 Department of Computer Engineering Sharif University of Technology
E-Mail: skasaei@sharif.edu Web Page: http://sharif.edu/~skasaei http://mehr.sharif.edu/~ipl
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Chapter 4 Chapter 4
Video Sampling Rate Video Sampling Rate Conversion Conversion
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Sampling Rate Conversion
Sometimes it is required to display:
A PAL signal on an NTSC TV system. A motion picture on film on PAL TV
broadcasting.
Made-for-TV material on a computer screen,
which uses progressive display (an interlaced raster into a progressive raster known as deinterlacing).
An MPEG2 video on a mobile phone (H263). A H.263 video format on H.264/MPEG4 devices
(transcoding).
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Conversion of Signals Sampled on Different Lattices
Once in the digital domain, we often need
to convert a digital video signal from one format (in terms of spatial & temporal) to another (from one lattice to another).
The solution depends on the relation
between two lattices.
This leads to up-conversion (interpolation)
- r down-conversion (decimation), or both.
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Conversion of Signals Sampled on Different Lattices
For up-conversion, we first zero-pad the lattice
points & then estimate the values of new points by interpolation.
For down-conversion, to avoid aliasing, we need
to pre-filter the signal to limit its bandwidth to the Voronoi cell of the reciprocal of the new lattice.
For arbitrary rate conversion, the third lattice
contains both lattices & the filter fulfills both interpolation & spectrum limitation.
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Conversion of Signals Sampled on Different Lattices
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UP-Conversion
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Down-Conversion
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Sampling Rate Conversion
- General procedure includes:
- 1. Determining the equivalent sampling
lattices of the input & output signals, & an intermediate lattice that covers the samples in both signals.
- 2. Determining the desired filter frequency
response (based on the Voronoi cells of the three lattices).
- 3. Designing a filter that approximates the
desired response.
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Sampling Rate Conversion
- In practice to reduce the computational
complexity one can:
- Use very low-tap filter (specially in the
temporal direction).
- Decompose spatiotemporal conversion
problem into spatial conversion followed by temporal conversion (or vise versa).
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Deinterlacing
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Deinterlacing
Practical interlacing:
Uses simpler filters. Vertical interpolation (averaging) within the same field
(line averaging).
To improve the performance, longer vertical
interpolation filters can be used.
A simple temporal interpolation is field merging (that
just copies the corresponding line from the top/bottom field).
To improve the performance, a symmetric filter can be
used (field averaging).
To achieve a compromise between the spatial &
temporal artifacts, both vertical & temporal interpolations are used (line & field averaging).
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Conversion between PAL & NTSC Signals
For direct conversion, because of the very
complicated shape of the reciprocal Voronoi cells, the filter is not easy to design.
In practice, the problem is more often
solved in several sequential steps.
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Conversion between PAL & NTSC Signals
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Conversion between PAL & NTSC Signals
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Conversion between PAL & NTSC Signals
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Conversion between PAL & NTSC Signals
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Motion-Adaptive Interpolation
In stationary regions, temporal
interpolation yields an accurate result.
In regions undergoing rapid temporal
changes, same spatial indices may correspond to different object regions.
In this case, spatial interpolation alone is
better (no temporal interpolation).
To overcome such problems, motion-
adaptive interpolation filters can be used.
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Motion-Adaptive Interpolation
With such a filter, one switches between
vertical & temporal interpolation at each pixel, depending on the output of a motion detector (motion vertical interpolation).
Motion detection can be performed locally. To further improve the performance,
motion-compensated interpolation can be investigated.
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