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As with digitizing analog audio, digitization of video requires the appropriate choices for pixel depth and quantization, correct choice of sample rate, and care with anti-aliasing Oversampling is more difficult for video than it is for audio, because of the much higher sampling rates involved However, there are oversampling solutions available Brick wall filters are often applied to the video pass-band, in order to remove all unwanted higher frequency components, but because these are higher order filters, ringing and overshoot is a potential problem High order filters can introduce artifacts in the video signal that make it much harder to encode for streaming media As with audio, pass-band limiting can also be performed in the digital domain, after digitization.

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Video signals often suffer from chroma phase errors and ringing artifacts, due to the number of signal handling stages the video may have passed through from its initial creation to the digitization process Sometimes it is possible to correct these phase errors and overshoots in the digital domain, after the signal has been digitized As with audio, sometimes video sampled at one frame rate and sampling frequency must be resampled to another The general form of this conversion is called sample lattice conversion and it is roughly analogous to audio sample rate conversion, except that it can convert digitized images to images with different frame rates, pixels per line, and lines per frame Sample lattice conversion finds application in standards conversion (converting PAL to NTSC, for example), image cropping, image resizing and aspect ratio correction.

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Standards conversion, in particular, often benefits from motion-compensated and motion adaptive processing, in order to preserve the quality of the image when high motion content is present It is important to note that the quality of the sample lattice conversion process depends on the complexity and order of the algorithm used to perform the task Hence, not all sample lattice conversions are the same and the compressionist needs to understand the specifications of the one in use or else suffer image degradation In typical digital video production environments, video signals can be compressed and decompressed a number of times before they are repurposed for streaming media By the time the streaming media encoder sees the video signal, it may have been through several compress/decompress processes (as is the case when a television production plant, wired for MPEG-2 digital video production, wishes to transcode the video into MPEG-4 for streaming).

To avoid image degradation, it is important that the macro blocks of every compression stage are aligned Any shift in macro block alignment only serves to degrade image quality over successive compression/decompression cycles Unfortunately, to this.

author s knowledge, there are no streaming media encoders available today that are responsive to macro block alignment parameters Many MPEG-2 converters, however, allow for macro block alignment and these should be used throughout the video production chain if MPEG-2 is used Once the video signal has been digitized, the video can be further cleaned and enhanced using two-dimensional filtering techniques, such as low pass filtering and median filtering These intraframe filters are useful for removing various noise sources, such as speckle noise (a form of pink noise) that can be introduced by satellite transmission paths, for example These filters have the effect of softening the image, but in the case of low pass filtering, can introduce image smearing Hence, these filters must be applied judiciously Another class of two-dimensional video filter uses information from other frames of the video sequence to clean up the video image.

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